This is a searchable catalogue of AI tools used in and by governments.
This is a searchable catalogue of AI tools used in and by governments. It is based on the Public Sector Tech Watch dataset of digital tools used in the EU, which we curated to focus on AI tools and the applications that we thought were most relevant to South Africa and then expanded to include other examples from across the globe. We update this document twice a year as we find new local and global applications of AI in the public sector that we think are relevant to South Africa. The most recent update was in June 2026. The methodology and code used in compiling this data is described in our git repository, as well as a brief discussion of its limitations.
The dataset is also available for download at SunScholar. Recommended citation:
Manicom, G., Muzondidya, T. and Chikunichawa, T. 2026. A Catalogue of Artificial Intelligence Tools for Use by South African Policymakers [Dataset]. Policy Innovation Lab, Stellenbosch University. DOI: https://doi.org/10.25413/sun.26086003
Catalogue June 2026
| ID | Name | Website | Description | Geographical extent | Geographical coverage (country) | Geographical coverage (NUTS 2021) | Responsible Organisation | Responsible Organisation category | COFOG Level I | COFOG Level II | Status | Start Year | End Year | Process type | Application type | Cross Border | Cross Sector | Technology | Interaction | Improved Public Service | Personalised Services | Public (citizen)-centred services | Increase quality of PSI and services | More responsive, efficient, and cost-effective public services | New services or channels | Improved Administrative Efficiency | Cost-reduction | Responsiveness of government operation | Improved management of public resources | Increased quality of processes and systems | Better collaboration and better communication | Reduced or eliminated the risk of corruption and abuse of the law by public servants | Enabled greater fairness, honesty, equality | Open government capabilities | Increased transparency of public sector operations | Increased public participation in government actions and policy making | Improved public control and influence on government actions and policies | Source | AI Classification (I) | AI Classification Subdomain (II) (main) | AI Classification Subdomain (II) (Other I) | AI Classification Subdomain (II) (Other II) | AI Classification Subdomain (II) (Other III) | AI Keywords | Date-updated |
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| ID | Name | Website | Description | Geographical extent | Geographical coverage (country) | Geographical coverage (NUTS 2021) | Responsible Organisation | Responsible Organisation category | COFOG Level I | COFOG Level II | Status | Start Year | End Year | Process type | Application type | Cross Border | Cross Sector | Technology | Interaction | Improved Public Service | Personalised Services | Public (citizen)-centred services | Increase quality of PSI and services | More responsive, efficient, and cost-effective public services | New services or channels | Improved Administrative Efficiency | Cost-reduction | Responsiveness of government operation | Improved management of public resources | Increased quality of processes and systems | Better collaboration and better communication | Reduced or eliminated the risk of corruption and abuse of the law by public servants | Enabled greater fairness, honesty, equality | Open government capabilities | Increased transparency of public sector operations | Increased public participation in government actions and policy making | Improved public control and influence on government actions and policies | Source | AI Classification (I) | AI Classification Subdomain (II) (main) | AI Classification Subdomain (II) (Other I) | AI Classification Subdomain (II) (Other II) | AI Classification Subdomain (II) (Other III) | AI Keywords | Date-updated |
| PIL-1 | PROMPTS by Jacaranda Health | https://jacarandahealth.org/our-work/#our-model | PROMPTSÂ is an AI chatbot that speaks multiple African leanguages and is trained to empower women with information via SMS to make informed choices about their health care, ask questions during and after pregnancy, and receive targeted support and referral if a risk is identified during the exchange. | Regional | Kenya, Eswatini, Ghana | Jacaranda Health | Local Government | Health | R&D health. | Implemented | Public services and engagement | Information | Yes | No | Artificial Intelligence | G2C | x | x | x | x | x | x | x | x | x | x | https://jacarandahealth.org/our-work/#our-model | Communication | Natural language | Machine learning | chatbot | 02/12/2024 | |||||||||||||
| PIL-10 | ITIKI Drought Early-Warning System | https://urida.co.za | Combines indigenous knowledge and ML weather models to send SMS/USSD drought alerts to smallholders in South Africa, Kenya, and Mozambique. | Across countries | South Africa | The Unit for Research on Informatics for Droughts in Africa (URIDA) | Academic-Research | Environmental Protection | Agriculture | Climate risk management | Early warning system | Machine Learning, Indigenous Knowledge Systems | G2C | https://urida.co.za | Predictive Analytics | Climate Risk Modeling | drought early warning | 13/06/2025 | |||||||||||||||||||||||||||
| PIL-11 | Hi- Saai- family Farmers Chatbot | https://saai.org/en/saai-launches-artificial-intelligence-platform-for-family-farmers | The Southern African Agri Initiative (SAAI) has launched an AI-powered platform aimed at helping family farmers make informed decisions on weather, inputs, financial planning, and sustainability. The system uses localised data and machine learning to deliver cost-effective, personalised farming recommendations. | National | South Africa | SAAI (Southern African Agri Initiative) | Non-governmental | Economic Affairs | Agriculture | Operational | AI-enhanced decision support and planning tools for small-scale farmers | Farm operations optimisation, cost-saving support, market access | Machine Learning for crop planning and input optimisation, Natural Language Interfaces for farmer accessibility | https://saai.org/en/saai-launches-artificial-intelligence-platform-for-family-farmers | Predictive and Advisory AI | Farm Decision Support | chatbot | 13/06/2025 | |||||||||||||||||||||||||||
| PIL-12 | Flood risk detection tool | https://www.sansa.org.za/2022/04/flood-decision-support-tool/ | A new tool providing spatial information layers showing potential flood inundation scenarios alongside human settlement layers and allowing rapid visual assessment of areas most vulnerable to flood damage has been developed at the South African National Space Agency. The Flood inundation layers show areas that are likely to be flooded at 1 meter, 3 meter, and 5 meter rise in water levels in South Africa. These layers can be used to support early warning for floods and to identify settlements that are at risk of being flooded. | National | South Africa | South African National Space Agency (SANSA | Central-Government | Environmental Protection | Flood Protection | Disaster risk modelling and spatial decision support | Flood risk mapping, civil protection | Remote Sensing and Satellite Data, GIS and Spatial Data Layers | G2G | https://www.sansa.org.za/2022/04/flood-decision-support-tool/ | Geospatial and Predictive AI | Flood Inundation Forecasting | flood prediction | 13/06/2025 | |||||||||||||||||||||||||||
| PIL-13 | GovChat citizen-engagement platform | https://govchat.org | WhatsApp/USSD chatbot uses NLP and analytics to route service queries, log complaints and surface sentiment dashboards for 257 municipalities and national departments | National | South Africa | Department of Cooperative Governance and Traditional Leaders (CoGTA) | Consortium | General Public Services | Public Sector Management and Coordination | Citizen engagement | Conversational AI | Natural Language Processing, Sentiment Analysis, Service Mapping | G2C | https://govchat.org | Conversational AI | Sentiment Analysis | chatbot | 13/06/2025 | |||||||||||||||||||||||||||
| PIL-14 | Voice AI Integrated into play-based learning | https://ai-for-education.org/lbd-stellenbosch-university-and-trackosaurus/ | Stellenbosch University partnered with Trackosaurus to develop AI models to enable spoken interaction in maths and language assessment games for young children in South Africa. The games will be developed in Afrikaans, isiXhosa and siSwati. | National | South Africa | Stellenbosch University + Trackosaurus | Academic-Research | Education | Pre-Primary and Primary Education | Pilot | 2.023 | Early childhood education | Educational AI | Automatic Speech Recognition, Natural Language Understanding, Game-Based Learning | https://ai-for-education.org/lbd-stellenbosch-university-and-trackosaurus/ | Speech Recognition | Educational Voice AI | early learning AI | 13/06/2025 | ||||||||||||||||||||||||||
| PIL-15 | GovSearch | https://nationalstrathub.cogta.gov.za/data-tools/decision-support-tools/ | Powered by AI, this intelligent search engine centralizes reports, policies, and sector plans making it easier for public servants and policymakers to find the information they need, when they need it. | National | South Africa | Department of Cooperative Governance & Traditional Affairs (CoGTA) | Central-Government | General Public Services | Public Sector Management and Coordination | Planned | Knowledge management | Enterprise search | Natural Language Processing, Semantic Search, Knowledge Graphs | G2G | https://nationalstrathub.cogta.gov.za/data-tools/decision-support-tools/ | Information Retrieval | Semantic Search | intelligent search | 13/06/2025 | ||||||||||||||||||||||||||
| PIL-16 | Electronic Travel Authorisation (eTA) System (not yet implemented) | https://www.workpermitsouthafrica.co.za/another-positive-move-to-attract-more-tourists-to-sa/ | It will use artificial intelligence (AI) and automation to reduce the scope for corruption and enable rapid turnaround times for tourist visas. | National | South Africa | Department of Home Affairs | Central-Government | Public Order and Safety | Immigration Control | Planned | Border management | Automated decision system | Document Verification AI, Risk Scoring Algorithms, Biometric Matching | G2C | https://www.workpermitsouthafrica.co.za/another-positive-move-to-attract-more-tourists-to-sa/ | Process Automation | Document Fraud Detection | visa automation | 13/06/2025 | ||||||||||||||||||||||||||
| PIL-17 | Audrey | https://iol.co.za/sunday-tribune/news/2025-05-17-audrey-is-watching-ai-system-detects-financial-and-operational-anomalies-in-real-time/ | Audrey, monitors transactions and data in real time, flagging anomalies and potential compliance breaches within minutes. | National | South Africa | pending full confirmation | General Public Services | Public Sector Financial and Audit Management | Financial oversight | Anomaly detection | Machine Learning, Behavioral Analytics, Real-time Processing | https://iol.co.za/sunday-tribune/news/2025-05-17-audrey-is-watching-ai-system-detects-financial-and-operational-anomalies-in-real-time/ | Anomaly Detection | Financial Fraud Detection | fraud detection AI | 13/06/2025 | |||||||||||||||||||||||||||||
| PIL-19 | FruitPunch AI | https://www.fruitpunch.ai/blog-full-versions/ai-powered-wildlife-conservation-in-africa | Developed an edge computer vision model to detect poachers on thermal video streams via a fixed-wing drone, deployed in South African wildlife reserves. Similar AI-powered anti-poaching initiatives using drones and acoustic sensors are active across the continent, including in Kenya and Zimbabwe. | National | South Africa | FruitPunch AI + Conservation Partners | Consortium | Environmental Protection | Biodiversity and Landscape Protection | Wildlife protection | Computer vision surveillance | Edge AI, Thermal Imaging, Drone Surveillance | https://www.fruitpunch.ai/blog-full-versions/ai-powered-wildlife-conservation-in-africa | Computer Vision | Object Detection | poacher detection | 13/06/2025 | ||||||||||||||||||||||||||||
| PIL-2 | GRIT-GBV Zuzi chatbot | https://www.grit-gbv.org/ | Zuzi is a supportive, knowledgeable, African, and trauma-informed ChatBot for GBV survivors to speak to. It is is designed to provide critical information about the rights and legal services available to survivors of gender-based violence. Â As well as addressing sexual and reproductive health issues (SRH). | National | South Africa | GritGBV | Community led | Public order and safety | Law courts | Implemented | Enforcement | Information | No | No | Artificial Intelligence | G2C | x | x | x | x | x | x | x | x | https://www.grit-gbv.org/ | Communication | Natural language | Machine learning | chatbot | 02/12/2024 | |||||||||||||||
| PIL-23 | CSIR Body and number plate recognition system | https://www.csir.co.za/csir-developed-face-body-and-number-plate-recognition-system-tested-sa-army | The CSIR has developed an integrated face, body, and license plate recognition system for secure access control and surveillance, combining multiple biometric technologies for enhanced security. | National | South Africa | CSIR (Council for Scientific and Industrial Research) | Academic-Research | Public Order and Safety | Civil Defence | Pilot | 2.022 | Biometric surveillance and automated identity recognition | Secure access control and military surveillance | Computer Vision, Biometric Recognition, License Plate Recognition, Facial Recognition, Edge AI | https://www.csir.co.za/csir-developed-face-body-and-number-plate-recognition-system-tested-sa-army | Perceptual AI | Object and Face Recognition | facial recognition | 13/06/2025 | ||||||||||||||||||||||||||
| PIL-25 | UJ Facial Recognition | https://news.uj.ac.za/news/uj-implements-facial-recognition-for-a-secure-registration-a-first-for-a-south-african-university/ | University of Johannesburg implements facial recognition technology for identity verification during student registration, enhancing security and reducing fraud. This innovative system ensures a seamless, contactless process while setting a new standard for digital authentication in higher education. | Local | South Africa | University of Johannesburg (UJ) | Higher Education Institution | Public Order and Safety | Operational | 2.024 | Digital identity verification and fraud prevention | University registration and authentication | Facial Recognition, Biometric Identity Verification | G2C | https://news.uj.ac.za/news/uj-implements-facial-recognition-for-a-secure-registration-a-first-for-a-south-african-university/ | Perceptual AI | Facial Recognition & Digital Identity Recognition | facial recognition | 13/06/2025 | ||||||||||||||||||||||||||
| PIL-27 | SANRAL AI for Road Maintenance | https://sensorit.io/Projects/ai-revolution-in-road-maintenance/ | As part of a proof-of-concept (PoC), SANRAL and SensorIT piloted a road inspection system that uses computer vision and AI algorithms to automatically detect and classify defects such as potholes, cracks, and roadwear, enabling predictive maintenance and real-time reporting. | National | South Africa | SANRAL (South African National Roads Agency Limited) & SensorIt | Central-Government | Economic Affairs | Transport | Pilot | 2.023 | Predictive infrastructure maintenance and automation of inspection workflows | Transport infrastructure inspection and reporting | Computer Vision, Edge AI, Predictive Analytics | G2C | https://sensorit.io/Projects/ai-revolution-in-road-maintenance/ | Perceptual and Predictive AI | Road Defect Detection | predictive maintenance | 13/06/2025 | |||||||||||||||||||||||||
| PIL-28 | UCT Jamie Shuttle Smart Fleet Management System | https://sensorit.io/Projects/uct-jamie-shuttle | The University of Cape Town (UCT), in partnership with SensorIT, deployed a smart fleet monitoring system for the Jamie Shuttle using real-time GPS tracking, telematics, and AI-based driving behavior analytics to enhance safety, efficiency, and service quality. | Local | South Africa | University of Cape Town (in partnership with SensorIT) | Consortium | Economic Affairs | Transport | Operational | 2.022 | AI-enhanced fleet management and passenger transport optimisation | University transportation and mobility services | Telematics, Real-time GPS tracking, AI-driven behavior analysis | G2C | https://sensorit.io/Projects/uct-jamie-shuttle | Predictive and Perceptual AI | Driving Behavior Analytics | fleet management | 13/06/2025 | |||||||||||||||||||||||||
| PIL-29 | CSIR Meerkat WASS & GSCR Anti-Poaching Surveillance Systems | https://www.csir.co.za/surveillance-systems | The Meerkat Wide Area Surveillance System (WASS) and its upgrade, the Ground-based Surveillance and Classification Radar (GSCR), were developed by the CSIR to combat rhino poaching. These systems combine radar detection, AI-based classification, and electro-optical sensors (including the Rino and Tyto cameras) to detect, classify, and track humans and animals across vast terrain with minimal human intervention. They feed real-time georeferenced intelligence to command centres and are being adapted for broader uses like border and infrastructure security. | National | South Africa | CSIR | Academic-Research (CSIR) + Non-governmental (Peace Parks) + Central-Government (SANParks & DSI) | Public Order and Safety | Environmental Protection and Anti-Poaching | Operational | Automated surveillance and target classification | Wildlife crime prevention and protected area monitoring | Radar detection and classification (GSCR), AI-based object classification (human vs. animal) | G2G | https://www.csir.co.za/surveillance-systems | Perceptual and Embedded AI | Human-Animal Classification via Radar | anti-poaching AI | 13/06/2025 | ||||||||||||||||||||||||||
| PIL-3 | Planvillage Nuru | https://bigdata.cgiar.org/digital-intervention/plantvillage-nuru-pest-and-disease-monitoring-using-ai/ | PlantVillage has created Nuru, an AI assistant for farmers. Nuru has three components to its artificial intelligence: 1) human expert level crop disease diagnostics using computer vision; 2) above human capabilities in anomaly detection and forecasting based on ground and satellite derived data; and 3) human language comprehension and automated responses to questions posed by farmers. Our AI works with extension services, governments and the UN. | Regional | India, Kenya, Tanzania | PlantVillage | Academic-Research | Environmental Protection | Agriculture, forestry, fishing | Implemented | Analysis, monitoring and evaluation | Information | Yes | No | Artificial Intelligence | G2C | x | x | x | x | x | x | x | x | x | x | x | x | https://bigdata.cgiar.org/digital-intervention/plantvillage-nuru-pest-and-disease-monitoring-using-ai/ | Perception | Machine learning | Computer vision | classifier | 02/12/2024 | |||||||||||
| PIL-30 | PolicyEngine USA | https://policyengine.org/us | The most widely adopted free and open-source engine to write rules as code Government departments, lawmakers and civil society finally share a common language to debate and activate social and fiscal policies: OpenFisca enables collaboratively modelling laws and regulations and making them computable over open APIs for developers, datascientists and researchers. OpenFisca is a leading Rules as Code solution, but it is primarily aimed at microsimulation. Microsimulation is where you create a data model that represents small elements of a population, like people and households, and then encode the effects of different tax and benefit regimes. You can then load data that is representative of your actual population, and look at the effects on those individuals or groups in aggregate. Or, you can load a smaller number of specific examples and see how those particular fact scenarios are affected by the rules. It uses OpenFisca OSS software framework. OpenFisca is a policy simulation framework that utilizes various techniques from data science and computer science to model and analyze the impact of social and fiscal policies. While OpenFisca does not rely on Artificial Intelligence (AI) as its primary component, it does employ some AI-related techniques and concepts to enhance its capabilities. AI-related techniques used in OpenFisca: 1) Machine Learning (ML): OpenFisca uses ML algorithms to estimate the effects of policies on specific outcomes, such as poverty rates or government revenues. For example, it can employ regression analysis to model the relationship between policy parameters and outcomes. 2) Decision Trees: OpenFisca's policy modeling engine uses decision trees to represent complex policy rules and regulations. Decision trees are a type of ML model that can be used to classify inputs and make predictions. 3) Optimization Techniques: OpenFisca's scenario analysis capabilities utilize optimization techniques, such as linear programming, to find the optimal policy parameters that achieve specific goals, like minimizing poverty rates or maximizing government revenues. 4) Data Mining: OpenFisca's data integration and analysis capabilities involve data mining techniques to extract insights from large datasets and identify patterns in policy-relevant data. | National | United States | AI-enhanced policy support | Policymaking | Predictive Analytics | X | https://policyengine.org/us | Predictive and Decision Support AI | Predictive analytics | policy simulation | 20/06/2025 | |||||||||||||||||||||||||||||||
| PIL-31 | MomConnect | https://www.health.gov.za/momconnect/ | MomConnect is a national mobile health programme of the South African National Department of Health that provides maternal and child health information via SMS/WhatsApp, supports pregnant women and new mothers until the child turns two, and offers guidance through an automated chatbot and a human-operated helpdesk. Over 5 million mothers have been registered since 2014 across 95%+ of public facilities. | National | South Africa | 2.014 | Digital health communication; public health behaviour change; mobile health (mHealth) programme | SMS & WhatsApp chatbot; automated helpdesk; human-operated helpdesk | No | Yes | G2C | AI-enabled rule-based and NLP-supported chatbot; Automated maternal health information service (Note: historically rule-based, but modern WhatsApp implementation blends conversational AI technologies.) | Conversational Systems / Chatbots | ||||||||||||||||||||||||||||||||
| PIL-32 | Ask-a-Metric (AAM) – AI Data Analyst on WhatsApp | https://www.idinsight.org/article/ask-a-metric-your-ai-data-analyst-on-whatsapp/ | Ask-a-Metric (AAM) is an open-source, LLM-powered WhatsApp tool developed by IDinsight's Data Science & Engineering team that allows government officials and NGO staff to query M&E databases in natural language, in their preferred language, without dashboard access or technical skills. Designed for low-connectivity environments across Kenya, India, Ghana, and other low- and middle-income countries. | Across countries | Kenya | 2.023 | Data analytics automation; public-sector digitisation; AI-enabled decision support | AI analytic assistant / conversational query interface | Yes | Yes | G2C | Conversational AI / analytics assistant; LLM-powered database query system | Natural Language Processing (NLP) | ||||||||||||||||||||||||||||||||
| PIL-33 | Lesedi AI Platform | https://www.palindromedata.com/lesedi-ai-platform/ | Lesedi AI is a machine-learning platform used in healthcare settings to provide predictive analytics, risk scoring, patient microsegmentation, and AI-driven care recommendations. It integrates with electronic medical record (EMR) systems to support healthcare workers, case managers, program officers, and policymakers. Developed by Palindrome Data (South Africa) and deployed across 30+ sites in Nigeria, South Africa, and Tajikistan, it has reduced HIV treatment interruptions by 3.8% in Nigeria and improved differentiated service delivery in South Africa | Across countries | Nigeria | 2.022 | Predictive analytics pipeline; AI-enabled decision support; EMR-integrated risk modelling | Predictive AI platform / Machine-Learning Health Decision Support System | Yes | Yes | G2G | Predictive analytics engine Machine learning risk scoring system AI decision support for healthcare | Predictive Modelling / Machine Learning | ||||||||||||||||||||||||||||||||
| PIL-34 | Ghana Entrepreneurship Policy Chatbot (GEPbot) | https://www.gepbot.com | AI-powered chatbot providing entrepreneurs with instant access to Ghana’s entrepreneurship policy, regulatory guidance, procedures, programmes, and simplified navigation of the startup and SME ecosystem. Launched at GDIW 2025. | National | Ghana | 2.024 | Digital transformation; AI-enabled public service delivery | AI Chatbot / Digital Policy Assistant | No | Yes | G2C | Conversational AI System / Question-Answering System | Natural Language Processing (NLP) | ||||||||||||||||||||||||||||||||
| PIL-35 | Ghana mobile operator for natural disasters | https://www.datatopolicy.org/use-case/ghana-mobile-operator-for-natural-disasters | A long-term public–private partnership between Ghana Statistical Service, Telecel Ghana, NADMO, Flowminder, and Data for Good that uses pseudonymized mobile operator Call Detail Records (CDR) combined with geospatial hazard and vulnerability data to produce dynamic mobility insights, displacement estimates, and risk maps for disaster preparedness and response. The system improves early warnings, crisis coordination, and evidence-based decision-making. | National | Ghana | 2.017 | Present | Decision-support; Risk assessment; Crisis coordination; Early warning enhancement | Mobility analytics, Population displacement estimation, Dynamic hazard/risk mapping, Emergency response planning | No | Yes | G2G; G2B | https://www.datatopolicy.org/use-cases | Decision-Support / Predictive Analytics AI | Mobility analytics for risk prediction and crisis response | ||||||||||||||||||||||||||||||
| PIL-36 | Data for jobs: Youth and the future of work in Iraq | Iraq | A national multi-stakeholder initiative to address Iraq’s fragmented labour market data ecosystem and youth unemployment by integrating AI-powered crowdsourced survey data, web-scraped labour market data, and a data ecosystem mapping framework. The initiative brings together the Government of Iraq, KAPITA Research, the Open Data Institute (ODI), ProsperIA, GIZ (ProDIGI and Data2Policy), UNDP and private-sector actors. The initiative supports evidence-based policymaking to improve youth employment and build Iraq’s digital economy. | National | Iraq | 2.024 | Data ecosystem mapping AI-enabled data collection and analysis Labour market intelligence generation Policy decision-support Evidence-building & digital economy diagnostics | AI-integrated survey for job seekers Web-scraping of job market platforms API-based data ingestion Analytical dashboard for ministries | No | Yes | G2C; G2G; G2B | https://www.datatopolicy.org/use-cases | AI for Policy Decision-Support AI-enabled Data Collection & Analysis | AI-driven labour market intelligence | |||||||||||||||||||||||||||||||
| PIL-37 | Germany boosts data capacity with Government-wide data labs | https://www.datatopolicy.org/use-case/germany-boosts-data-capacity-with-government-wide-data-labs | Germany implemented a whole-of-government initiative to strengthen data capacity through the creation of data laboratories (“data labs”) in every federal ministry. These labs were introduced as part of the Federal Data Strategy (2021–2026) to overcome data silos, improve data literacy, foster evidence-informed policymaking, and accelerate digital transformation. Data labs function as compact specialist units focusing on (1) development of data and AI products including LLM-based assistants, dashboards, and cloud-integrated systems; (2) training public servants in data literacy and AI use; (3) building shared data infrastructure and data spaces; and (4) promoting interministerial collaboration and knowledge-sharing. The initiative is funded under the German Recovery and Resilience Plan (DARP), supported by the EU’s NextGenerationEU programme. | National | Germany | 2.021 | Organisational transformation Capacity building Knowledge management Digital innovation lifecycle Data governance system strengthening | LLM-based knowledge management systems AI assistants for government staff Data literacy & AI training modules Data product development (dashboards, analytics, cloud integration) Shared data spaces | No | Yes | G2C; G2G; G2B | https://www.datatopolicy.org/use-cases | AI for internal government capacity-building AI for knowledge management and organizational decision-support | LLM-based organisational intelligence / knowledge management systems | |||||||||||||||||||||||||||||||
| PIL-38 | Leveraging the power of data for agricultural resilience | https://www.datatopolicy.org/use-case/india-transforming-agriculture | A multi-phase agritech and digital public infrastructure initiative in India, centred in Telangana, that uses the AI for Agricultural Innovation (AI4AI) framework to scale digital agriculture. The Government of Telangana, with the World Economic Forum and partners, created agricultural digital public infrastructure including the Agricultural Data Exchange (AdeX), a rights-based Agricultural Data Management Framework (ADMF), and the AgriJSON standard. These enable secure, standardized sharing of government and private-sector agri data (e.g. soil, weather, crop, market data) to power AI- and data-driven agritech services for smallholder farmers, such as early pest prediction, price information, credit access, and value-chain optimization through Project Saagu Baagu. | Regional | India | 2.021 | Value-chain transformation (e.g. Project Saagu Baagu) Digital public infrastructure design & deployment (AdeX, ADMF, AgriJSON) Data governance and policy design AI-/data-enabled decision-support and service delivery | Agricultural Data Exchange (AdeX) platform Agri-specific digital public infrastructure (data exchange, policies, sandbox) AI-powered agritech services for farmers (pest prediction, advisory, pricing, credit access) | Yes | Yes | G2C; G2G; G2B | https://www.datatopolicy.org/use-cases | AI for sectoral transformation and resilience (Agriculture) Decision-support and advisory AI (value chain, risk, productivity) | decision support | |||||||||||||||||||||||||||||||
| PIL-39 | Addressing care infrastructure for women’s economic empowerment through data | https://www.datatopolicy.org/use-case/mexico-women-and-care-part-2 | Mexico City’s Government and the Ministry for Women (SEMUJERES), together with GIZ, ProsperIA, and civil society partners, created a data-driven approach to design and improve the city’s care infrastructure. Using IncluIA—a geospatial intelligence platform integrating administrative data, census data, satellite imagery, and crowdsourced information—policymakers can identify areas with existing, minimum, or potential care clusters. These clusters consolidate childcare, elder care, disability services, community centres, food banks, extended-hour primary schools, and social services within a 1.6 km radius. The platform uses NLP and voice technologies to process crowdsourced insights, enabling the city to determine priority zones for new services and infrastructure. The approach advances gender equality by redistributing unpaid care work and strengthening economic inclusion for women. | Regional | Mexico | 2.024 | Ongoing | Geospatial intelligence analysis Data integration across administrative, census, satellite, and crowdsourced sources Service planning and resource allocation tool Policy decision-support Gender-focused infrastructure mapping | NLP-enabled data collection and classification Geospatial mapping for care clusters Platform-based decision-support (IncluIA) Infrastructure planning for social services | No | Yes | G2C; G2G; G2B | https://www.datatopolicy.org/use-cases | AI for gender equity and social inclusion AI for policy and service planning | Natural Language Processing (NLP) for social data analysis | ||||||||||||||||||||||||||||||
| PIL-4 | ABIS – Automated Biometric Identification System | https://www.dha.gov.za/index.php/civic-services/abis | AI-powered matching of fingerprints, faces & palm prints across 70 m+ records for e-passports, Smart ID cards and border control | National | South Africa | Department of Home Affairs (DHA) | Central-Government | General Public Services | Civil Registration and Identification | Operational | Identity verification, Border security | Biometric Recognition System | G2C; G2G | https://www.dha.gov.za/index.php/civic-services/abis | Identity Analytics | Facial Recognition, Fingerprint/Palmprint Matching | Border Control Automation | biometric matching | 13/06/2025 | ||||||||||||||||||||||||||
| PIL-40 | Lisbon harnesses AI to map and scale solar installations | https://www.datatopolicy.org/use-case/lisbon-harnesses-ai-to-map-and-scale-solar-installations | Lisbon, a signatory of the Global Covenant of Mayors and participant in the EU’s AI4PublicPolicy initiative, developed an AI-enabled workflow to map photovoltaic (PV) installations across the city. Using satellite imagery, historical data and open municipal data, the municipality deployed a computer vision pipeline (YOLOv8 + image segmentation) to detect, geolocate, and estimate the surface area of rooftop solar panels. Integrating this data into the city’s climate action planning accelerates monitoring of PV expansion, supports targeted campaigns in energy-poor neighbourhoods, and strengthens Lisbon’s Sustainable Energy and Climate Action Plan (SECAP) and CAP 2030 goals. The AI-assisted method dramatically improves efficiency compared to manual assessments and contributes to Lisbon’s goal of expanding solar capacity and reducing emissions by 2030. | Local | Portugal | 2.021 | AI-assisted geospatial analysis Climate and energy planning Infrastructure mapping Automated detection and monitoring of solar installations | Computer vision for PV detection Image segmentation for PV surface area estimation Dashboard-based geospatial visualization (AI4PublicPolicy environment) | No | Yes | G2C; G2G; G2B | https://www.datatopolicy.org/use-cases | AI for environmental sustainability / climate action Geospatial AI for infrastructure mapping | Computer vision for infrastructure detection (PV panels) | |||||||||||||||||||||||||||||||
| PIL-41 | Data-driven water infrastructure maintenance enabled by AI | https://www.datatopolicy.org/use-case/data-driven-water-infrastructure-maintenance-enabled-by-ai | The Municipality of Burgas (Bulgaria), in collaboration with EKSO S.R.L (the water supply and sewerage operator), implemented an AI-powered leak detection and water-infrastructure maintenance system as part of the European Union’s AI4PublicPolicy initiative. Using vibration sensors, water-pipe monitoring data, laboratory tests, and machine learning models, the system identifies abnormal vibration patterns associated with leaks and predicts failures in near real time. The AI model achieved up to 99.88% accuracy, significantly improving detection speed, enabling optimized maintenance scheduling, reducing water losses, and improving operational efficiency. The pilot establishes the foundation for scaling across Burgas’ water network and potentially other types of pipelines. | Local | Bulgaria | 2.021 | Predictive maintenance Real-time sensor monitoring ML-driven anomaly detection Infrastructure lifecycle optimisation | Vibration-based leak detection ML models for alert generation and classification Dashboard-based monitoring (pilot UI) | No | Yes | G2C; G2G; G2B | https://www.datatopolicy.org/use-cases | AI for infrastructure management / utilities optimisation AI for predictive maintenance | Machine learning for anomaly detection (leak identification) | |||||||||||||||||||||||||||||||
| PIL-42 | Amplifying Women’s Voices for Economic Participation by Addressing Access to Childcare | https://www.datatopolicy.org/use-case/mexico-women-and-care | Mexico City’s Government and the Women’s Ministry (SEMUJERES), together with BMZ, GIZ, the White Ribbon Alliance, Equidad Organización Feminista, ProsperIA and Ethos Innovación en Políticas Públicas, created an AI- and data-driven platform (IncluIA) to determine where new childcare infrastructure would best boost women’s economic participation. The platform integrates administrative data, census data, satellite imagery, crowdsourced survey responses from women processed with NLP/voice technologies, and existing childcare infrastructure maps. Natural Language Understanding converts women’s open and multiple-choice responses about care burdens, employment and health into spatially referenced indicators. Overlaid with socio-economic and labour data, this produces a city-wide map that identifies priority zones for new public childcare centres. The initiative focuses on reducing unpaid care burdens, enabling women to access decent work, and directing public investment towards the most underserved communities. | Local | Mexico | 2.022 | 2023 | Data ecosystem mapping for care & gender equality NLU / NLP processing of crowdsourced women’s survey data Spatial decision-support for childcare infrastructure planning Policy recommendation and prioritisation process | Intelligent map platform (IncluIA) combining: Census & administrative data Satellite imagery Existing childcare/care-centre locations Crowdsourced survey data processed via NLP/NLU | No | Yes | G2C; G2G | https://www.datatopolicy.org/use-cases | AI for gender equality and social inclusion AI for spatially-aware public service planning | Natural Language Processing / Understanding (NLU) for social survey analysis and needs mapping | ||||||||||||||||||||||||||||||
| PIL-43 | Building Trust in Data: Camden’s Ethical Data Practices | https://www.datatopolicy.org/use-case/camden-london-uk | The London Borough of Camden established a resident panel and co-designed a Data Charter to increase transparency, trust and ethical oversight for data and AI use in public services. Through public engagement sessions, expert inputs, case studies and ongoing events (“Camden Talks Data”), the Council ensures ethical data governance, transparency and public participation in decisions involving data and artificial intelligence. | Local | United Kingdom | 2.021 | Participatory Governance / Ethical Oversight / Data Governance | Governance / Policy Innovation / Public Engagement Platform | No | Yes | G2C | https://www.datatopolicy.org/use-cases | AI Governance & Ethical Frameworks | Public Engagement in AI Governance / Responsible AI Principles | |||||||||||||||||||||||||||||||
| PIL-44 | Making Care Needs Visible with Care Indicators | https://indicadoresdegenero.semujeres.cdmx.gob.mx/indicadores/indicadores-de-cuidados | Mexico City’s Women’s Secretariat, with the Open Data Charter and partners, adapted Buenos Aires’ Care Indicators System to create an online platform that integrates more than 80 indicators on the supply and demand of care. Using open and administrative data, the system visualises who needs care, who provides it (state, households, community, market) and where gaps exist. It aims to make care work visible, inform gender-sensitive care policies and provide a replicable open-data framework (the “Open Up Guide for the Care Sector”) for other governments. | Local | Mexico | 2.022 | Data integration & indicator development / Policy design support / Open data governance | Decision-support dashboard / Policy planning tool / Open data platform | Yes | Yes | G2G | https://www.datatopolicy.org/use-cases | |||||||||||||||||||||||||||||||||
| PIL-45 | Tackling Climate Change in the Maldives: A Hyperlocal Approach | https://www.datatopolicy.org/use-case/maldives-tackling-climate-change | The UNDP Accelerator Lab in the Maldives, in collaboration with Maafaru Island Council and UNESCAP, conducted a participatory mapping experiment to generate hyperlocal data for disaster risk reduction (DRR) and climate change adaptation (CCA). Local volunteers used digital mapping tools, satellite imagery, drone images and street-level photography to produce a detailed GIS base map and a Hazard, Vulnerabilities and Capacities (HVCA) map of the island. The project demonstrates how citizen-generated geospatial data can fill critical data gaps, support local risk planning and feed into national climate and disaster datasets for impact-based decision-making. | Local | Maldives | 2.023 | 2023 | Participatory mapping / Data collection / Climate risk assessment | Geospatial disaster risk planning tool / Data portal integration | Yes | Yes | G2C | https://www.datatopolicy.org/use-cases | disaster risk management | |||||||||||||||||||||||||||||||
| PIL-46 | Breaking Barriers: Reinforcing Gender Data Analysis and Use with the Gender Data Lab Initiative | https://www.datatopolicy.org/use-case/gender | The Gender Data Lab (GDL) initiative—led by PARIS21, UNDP’s Chief Digital Office and GIZ—strengthens the availability, quality and use of gender data globally. The initiative works with National Statistics Offices (NSOs) and government ministries to build institutional capacity, consolidate gender-disaggregated data, enhance gender-responsive statistical practices and promote evidence-based policymaking. The GDL model includes establishing lab teams within NSOs, developing innovative analytical tools (such as reproducible analytical pipelines with NLP capabilities), generating new gender indicators and fostering collaboration with academia and civil society. The initiative aims to close persistent gender data gaps and combat gender bias in public policy. | Across countries | Global | 2.023 | Capacity development; Institutional strengthening; Gender data integration; Policy support | Gender data lab model; Reproducible analytical pipelines; Gender-disaggregated indicator system | Yes | Yes | G2G | https://www.datatopolicy.org/use-cases | AI-Augmented Data Analysis (Only applies because of NLP-enabled analytical pipelines; otherwise: “Non-AI—Data Capacity Strengthening”) | NLP for automated reporting / Gender-sensitive data analytics | |||||||||||||||||||||||||||||||
| PIL-47 | Understanding Policy Effectiveness Using New Data Sources – Lessons Learned From COVID-19 in Maharashtra | https://www.datatopolicy.org/use-case/india | During Maharashtra’s severe second wave of COVID-19, researchers from the Development Data Partnership used private-sector datasets—including smartphone mobility data from Outlogic and satellite-based economic activity indices from SpaceKnow—to analyse policy impacts in real time. By comparing 2021 mobility and economic activity trends against pre-pandemic baselines, they assessed how population movement and sectoral economic output responded to lockdowns, restrictions and the emergence of the Delta variant. The study demonstrates how emerging data sources can complement traditional surveys and provide policymakers with granular, near real-time insights during fast-moving crises. | Regional | India | 2.021 | 2021 | Data analysis; Emerging data integration; Crisis policy evaluation; Big data research | Policy evaluation tool; Mobility & economic monitoring dashboard (research-focused) | Yes | Yes | G2G | https://www.datatopolicy.org/use-cases | AI-adjacent / Data analytics using ML-processed satellite imagery | Machine-learning derived satellite indices; Mobility analytics for crisis response | ||||||||||||||||||||||||||||||
| PIL-48 | Leveraging Big Data to Build Sustainable and Connected Cities: The Quito Case | https://www.datatopolicy.org/use-case/ecuador | The Municipality of Quito partnered with the Inter-American Development Bank (IDB), Telefónica and Waze to integrate big data, citizen-generated insights and AI-supported analytics into its urban development and mobility planning. These tools support a smart-city strategy aligned with the city's Metropolitan Development Plan, enabling evidence-based urban planning, reduced congestion, improved transit infrastructure and increased citizen engagement. | Local | Ecuador | 2.021 | Big data analytics integration; Real-time mobility monitoring; Smart city systems; Citizen participation platforms; Public–private data collaboration | Mobility analytics system; Real-time traffic orchestration platform; Citizen engagement portal | No | Yes | G2C; G2B | https://www.datatopolicy.org/use-cases | AI-enabled analytics (AI used in mobility modelling and pattern detection) | Mobility pattern analysis; Predictive urban planning; Transport optimisation | |||||||||||||||||||||||||||||||
| PIL-49 | Mapping Zambian Urbanisation Using Geospatial Data | https://www.datatopolicy.org/use-case/zambia | To support sustainable urban development in Lusaka, one of Africa’s fastest-growing cities, the Zambian Ministry of Local Government & Rural Development collaborated with the Ministry of Lands and Natural Resources, Ordnance Survey, the International Growth Centre (IGC) and the Commonwealth Association of Architects (CAA) to generate a high-resolution digital base map derived from satellite and aerial imagery. Using AI-based feature extraction, the base map identifies buildings, transportation networks, natural surfaces, sealed surfaces, vegetation and water bodies. This geospatial dataset enables policymakers to analyse the extent, growth and density of informal settlements, assess infrastructure gaps and support evidence-based decisions for urban planning, sanitation, water access, transportation and future infrastructure expansion. | Local | Zambia | 2.021 | Geospatial mapping; Digital base map creation; AI-based feature extraction; Urban policy analysis | Urban planning decision-support system; Infrastructure mapping tool | No | Yes | G2G | https://www.datatopolicy.org/use-cases | AI-supported (AI used for feature extraction from imagery) | Computer vision for geospatial analysis; Urban morphology detection; Remote sensing AI tools | |||||||||||||||||||||||||||||||
| PIL-5 | Smart Safety Technology Suite (CCTV analytics, gun-shot detection, LPR, drones) | https://www.capetown.gov.za/Media-and-news/Cape%20Town%20using%20gunshot%20detection,%20drones%20to%20pinpoint%20gang%20violence | Computer-vision models detect shots fired, recognise licence plates & track crime hot-spots in real time; feeds city command centre | Local | South Africa | City of Cape Town | Local Government | Public Order and Safety | Police Services | Real-time urban surveillance and public safety response coordination | Smart city policing and violence prevention | Computer Vision, Acoustic Gunshot Detection,Aerial surveillance using drones | G2G | https://www.capetown.gov.za/Media-and-news/Cape%20Town%20using%20gunshot%20detection,%20drones%20to%20pinpoint%20gang%20violence | Perceptual AI | CCTV and Drone Surveillance | smart surveillance | 13/06/2025 | |||||||||||||||||||||||||||
| PIL-50 | Unlocking Success in Rainfed Farming | https://www.datatopolicy.org/use-case/niger | Niger faces a severe food security crisis, with climate change and declining rainfall threatening rainfed staple crops like pearl millet and sorghum. Through the Data Powered Positive Deviance (DPPD) approach, GIZ Data Lab, UNDP Niger Accelerator Lab, GIZ PromAP Niger and the University of Manchester combined Earth observation, remote sensing and biophysical data (soil, rainfall, water, land cover) to identify communities whose rainfed yields significantly outperform expectations under similar climatic and environmental conditions. Using Sentinel-2–derived SAVI indices and ensemble modelling (regression, boosting trees, neural networks), the team mapped “positive deviant” communities and then conducted field research with 179 farmers in 18 villages. They documented practical agronomic techniques linked to higher yields, such as zaï holes, stone bunds, improved fertiliser practices, soil-cover retention and assisted natural regeneration. These locally grounded findings inform targeted agricultural support, climate adaptation strategies and scalable interventions to improve food security. | Regional | Niger | 2.021 | 2022 | Data Powered Positive Deviance (DPPD); Remote sensing–based performance analysis; Field validation; Farmer knowledge elicitation; Policy-oriented research | Decision-support analytics for agricultural policy; EO-based yield performance mapping; Targeting tool for climate-resilient farming interventions | No | Yes | G2G | https://www.datatopolicy.org/use-cases | AI / Machine Learning | yield prediction | ||||||||||||||||||||||||||||||
| PIL-51 | From Data to Action: Creating Safer Public Spaces for Women in Mexico City | https://www.datatopolicy.org/use-case/mexico | Mexico City faces widespread violence and harassment against women in public spaces, limiting their freedom of movement and participation in public life. Some areas of the city, however, show lower-than-expected levels of gender-based violence in public. The Women’s Secretariat of the Mexico City Government, together with the GIZ Data Lab and the UNDP Accelerator Lab, applied a Data Powered Positive Deviance (DPPD) approach to understand what makes these spaces relatively safer. Using crime statistics, satellite imagery, and other open data on infrastructure, mobility, land use and socio-economic conditions, the team built statistical models at neighbourhood (AGEB) level to identify “positive deviant” areas where violence against women was lower than predicted. These quantitative findings were complemented by qualitative fieldwork and interviews with women, producing actionable recommendations on how to design, govern and manage public spaces to improve safety for women and girls. The results are being used to reinforce and sharpen existing urban safety and gender-equality strategies across city agencies. | Local | Mexico | 2.021 | 2022 | Policy analysis & design; evaluation and diagnostics; urban safety strategy design; gender mainstreaming using analytics | Risk mapping / hotspot analysis; decision-support for urban planning; analytical study and recommendations; DPPD methodology application | No | Yes | G2G | https://www.datatopolicy.org/use-cases | Advanced Analytics (no core/black-box AI) | Spatial and statistical modelling for crime/safety; social outcome analytics | ||||||||||||||||||||||||||||||
| PIL-52 | Diia: Digital State | https://kitsoft.ua/projects/diia-digital-state | National digital government platform of Ukraine offering over 100 online public services and digital documents; used by 19M+ citizens. Developed by Kitsoft for the Ministry of Digital Transformation of Ukraine. | National | Ukraine | 2.020 | Ongoing | Public administration; service delivery; digital document issuance | Digital public service platform; e-government portal and mobile app; digital identity | No | Yes | G2C | https://kitsoft.ua/projects | AI-enabled Digital Government / Digital Public Infrastructure | Government Service Automation | ||||||||||||||||||||||||||||||
| PIL-53 | eMalyatko | https://kitsoft.ua/projects/emalyatko | Comprehensive online service within the Diia platform allowing parents to register a newborn and access up to 10 related administrative services through one digital application. The service integrates multiple state registries, automates data exchange, reduces administrative burden, and supports rapid issuance of documents. | National | Ukraine | 2.020 | Ongoing | Birth registration; civil registration; integrated social and administrative services | Online one-stop shop for newborn registration; multi-service digital application; registry-integrated workflow | No | Yes | G2C | https://kitsoft.ua/projects | Digital Public Infrastructure (AI-enabled workflow automation) | Government Process Automation | ||||||||||||||||||||||||||||||
| PIL-54 | Kyiv Digital — Online City Services Ecosystem | https://kitsoft.ua/projects/kyiv-digital | Kyiv Digital is a unified ecosystem of municipal online services for Kyiv residents, accessible via mobile application and online platforms. Kitsoft developed multiple digital services for the ecosystem, including electronic petitions, online kindergarten registration, school enrollment, and an e-cabinet for military defenders. The platform enhances local democracy, transparency, and public participation while eliminating paperwork and queues through digital workflows and secure authentication. | Local | Ukraine | 2.021 | Ongoing | Local administration digitalization; citizen participation; service delivery; education enrollment; social protection services | Multi-service digital municipal platform (mobile + web); e-democracy platform; e-registration systems | No | Yes | G2C | https://kitsoft.ua/projects | Digital Government Platform (AI-enabled components optional) | E-democracy & Citizen Engagement | ||||||||||||||||||||||||||||||
| PIL-55 | EcoSystem — Online Environmental Services Platform | https://kitsoft.ua/projects/online-services-ecology | EcoSystem is a national digital platform developed for the Ministry of Ecology and Natural Resources of Ukraine to digitize environmental services, automate permitting processes, integrate ecological registries, enable data-driven environmental management, and provide transparent public access to environmental information. Built on a BPMN-based architecture inspired by Diia, EcoSystem supports online permits, waste declarations, transborder waste transport, emissions certificates, logging permits, and automated verification of environmental documents, while serving businesses, government, and the public. | National | Ukraine | 2.020 | Ongoing | Permitting; licensing; regulatory compliance; environmental monitoring; registry integration | Digital permitting platform; registry-integrated workflows; business-facing environmental services portal; public transparency portal | Yes | Yes | G2C | https://kitsoft.ua/projects | AI-enabled Regulatory Process Automation / Digital Government Infrastructure | Environmental Regulation Automation | ||||||||||||||||||||||||||||||
| PIL-56 | Mukachevo Smart City Platform | https://kitsoft.ua/projects/city-platform-mukachevo | A comprehensive smart city platform developed by Kitsoft for the Mukachevo City Council to improve communication between the administration and residents, provide transparent access to city information, deliver digital public services, support e-participation, automate administrative processes, and attract investors and tourists. The platform includes modules for local government information, events timeline, dynamic statistics, media galleries, online applications, land and property listings, and investment promotion. Mukachevo received the awards “Best Mobile City” and “Best Digital City” at the Kyiv Smart City Forum 2020. | Local | Ukraine | 2.019 | Ongoing | Smart city management; e-services; citizen reporting; investment promotion; digital communication | Municipal digital services platform; public website; mobile-friendly city portal; e-participation system | No | Yes | G2G | https://kitsoft.ua/projects | Digital Municipal Services Platform | Smart City Governance | ||||||||||||||||||||||||||||||
| PIL-57 | e-Entrepreneur — Digital Business Services on Diia | https://kitsoft.ua/projects/e-entrepreneur | e-Entrepreneur is a comprehensive online business services platform within Diia, enabling users to access up to 10 key business-related administrative services in one digital application. It supports registration of private entrepreneurs (IEs) and LLCs, taxation registration, permits, declarations, food operator registration, vacancies submission, and more. Built on Kitsoft’s Liquio low-code BPMN platform, it integrates with 10 national registries to automate data exchange, eliminate repeated steps, minimize human error, and drastically reduce the time to start or update a business from weeks to minutes. | National | Ukraine | 2.023 | Business registration; permitting; tax registration; multi-service automation; business-onboarding | Integrated business services platform; multi-service workflow; low-code BPMN-based public service system | No | Yes | G2B | https://kitsoft.ua/projects | AI-enabled Digital Business Infrastructure | Business Process Automation (BPMN-driven) | |||||||||||||||||||||||||||||||
| PIL-58 | uResidency — Electronic Residency System of Ukraine | https://kitsoft.ua/projects/uresidency | uResidency is a comprehensive digital system on Diia enabling foreign citizens to remotely obtain e-resident status, register a business in Ukraine, open bank accounts, and pay taxes online. Developed by Kitsoft, the system integrates with multiple government agencies including the Ministry of Foreign Affairs, State Tax Service, National Bank of Ukraine, Ministry of Internal Affairs, and Security Service of Ukraine. The service automates identity checks, tax ID assignment, business registration, and bank integration, allowing foreigners to operate businesses in Ukraine from anywhere in the world. | National | Ukraine | 2.023 | E-residency onboarding; foreign entrepreneur registration; identity verification; tax registration | Cross-border e-residency platform; foreign entrepreneur online services; integrated multi-agency workflow | Yes | Yes | G2C | https://kitsoft.ua/projects | AI-enabled Cross-Border Digital Services | Identity Verification & Risk Screening Automation | |||||||||||||||||||||||||||||||
| PIL-59 | Unified Whistleblower Reporting Portal | https://kitsoft.ua/projects/unified-whistleblower-reporting-portal | A national digital portal developed by Kitsoft for the National Agency on Corruption Prevention (NACP) to confidentially report corruption offenses, grant whistleblower status, ensure legal protection, and automate communication with authorized bodies. The system enables anonymous or identified reporting, provides unique identifiers for case tracking, supports secure QES-based access for officials, and integrates analytics tools to monitor corruption reporting across thousands of government organizations. More than 7.5k institutions have joined, and over 5k corruption reports have been submitted since launch. | National | Ukraine | 2.023 | Anti-corruption reporting; whistleblower protection; procedural automation; case management | Reporting portal; secure case tracking system; analytics module | No | Yes | https://kitsoft.ua/projects | Digital Integrity & Anti-Corruption Systems | Whistleblowing & Compliance Automation | ||||||||||||||||||||||||||||||||
| PIL-6 | SARS “AI Assistant” chatbot | https://www.sars.gov.za | Natural-language bot answers tax, customs & traveller queries 24/7 and feeds training data back into SARS’ ML risk-engine | National | South Africa | South African Revenue Service (SARS) | Central Government | Economic Affairs | Taxation | Operational | Public-facing virtual assistance and back-end training data generation | Taxpayer support and compliance | Natural Language Processing (NLP), Conversational AI, Integration with ML risk engines | G2C | https://www.sars.gov.za | Generative and Conversational AI | Taxpayer Assistance | chatbot | 13/06/2025 | ||||||||||||||||||||||||||
| PIL-7 | Voice-AI Early-Grade Reading Assessment (EGRA-AI) | https://ai-for-education.org/lbd-egra-ai/ | Voice-recognition model auto-scores learners’ oral reading in African languages | South Africa | AI for Education Foundation Organisation | Consortium | Education | Pre-Primary and Primary Education | Educational assessment | Voice recognition/AI scoring | Automatic Speech Recognition (ASR), Natural Language Processing | G2C | https://ai-for-education.org/lbd-egra-ai/ | Speech Recognition | Automatic Speech Assessment | early grade reading | 13/06/2025 | ||||||||||||||||||||||||||||
| PIL-8 | AI-assisted TB screening vans (CAD4TB / Qure.ai) | https://www.qure.ai/impact_stories/how-ai-is-turning-the-tide-against-tuberculosis-in-south-africa | Portable X-ray units score images with AI; KZN pilot found 187 extra TB cases in 6 months | Regional | South Africa | Qure.ai | Consortium | Pilot | Automated diagnostic screening | Public health diagnostics and outreach | Computer-Aided Diagnosis (CAD), Deep Learning for chest X-ray interpretation | G2C | https://www.qure.ai/impact_stories/how-ai-is-turning-the-tide-against-tuberculosis-in-south-africa | Diagnostic AI | Chest X-ray Interpretation (CAD) | tuberculosis detection | 13/06/2025 | ||||||||||||||||||||||||||||
| PIL-9 | Cape Town Digital Water-Control Room | https://www.capetown.gov.za/Media-and-news/Cape%20Town%20launches%20digital%20hub%20for%20live%20tracking%20of%20water%20and%20sanitation%20infrastructure%20performance | Telemetry & predictive analytics reduce false alarms and speed leak/overflow response | Local | South Africa | City of Cape Town Water & Sanitation Directorate | Local Government | Environmental Protection | Water Waste Management | Utility operations management | Predictive maintenance | IoT Sensors, Predictive Analytics, Digital Twins | G2G | https://www.capetown.gov.za/Media-and-news/Cape%20Town%20launches%20digital%20hub%20for%20live%20tracking%20of%20water%20and%20sanitation%20infrastructure%20performance | Predictive Analytics | Anomaly Detection | predictive maintenance | 13/06/2025 | |||||||||||||||||||||||||||
| PSTW-10 | Camera System - Mobile phone usage on vehicles | https://baseline.vias.be/storage/minisites/methodological-guidelines-kpi-distraction.pdf | Traffic institute Vias is currently testing a new camera system that registers whether a motorist behind the wheel is on the phone with the phone in hand. Using Artificial Intelligence, the system filters the photos showing that the driver is using a smartphone. Other photos are deleted and faces are made unrecognizable. If the police establishes a violation based on that selection, they can issue a fine. | Local | Belgium | BE | Traffic Institute Vias | Local Government | Public order and safety | Police Services | Pilot | 2.020 | Enforcement | Smart Recognition processes | No | No | Artificial Intelligence | G2G | x | x | x | https://www.vias.be/nl/newsroom/succesvolle-test-met-camerasysteem-om-gsm-gebruik-achter-het-stuur-te-detecteren-/ | Perception | Computer vision | Machine learning | Automated reasoning | 06/10/2023 | ||||||||||||||||||
| PSTW-1003 | InA– The Chatbot at the Office of Integration | https://www.schleswig-holstein.de/DE/landesregierung/themen/digitalisierung/kuenstliche-intelligenz/KI_Strategie/_documents/ki__ai_strategy_download.pdf?__blob=publicationFile&v=1 | The Office of Integration of the Ministry for Social Affairs, Health, Family, Youth, and Senior Citizens integrated a chat bot into its website in February 2020. This chat bot is being further developed in a follow-on project. Using the chat bot, people can call up general information, arrange for callbacks, and determine time windows for contact purposes. It is also possible to use the chat bot to submit an initial application for accompanying assistance. | Regional | Germany | DEF0 | Office of Integration of the Ministry for Social Affairs, Health, Family, Youth, and Senior Citizens of Schleswig-Holstein | Regional Government | Social protection | Social protection n.e.c. | Implemented | 2.020 | Public services and engagement | Service personalisation (various) | No | No | Artificial Intelligence | G2C | x | x | x | x | x | x | Bendszusn, R. (2022). Make-or-buy in the area of Artificial Intelligence: Insights from AI use cases in the German public sector (master's thesis). Hertie School, Berlin. | Communication | Natural language processing | AI Services | chatbot | 30/08/2023 | |||||||||||||||
| PSTW-101 | ModEst - Student Flow Modeling | https://www.lasige.pt/project/modest/ | The goals of the ModEst (Student flow modeling in the Portuguese educational system) project are to produce reliable estimates of the relevant variables describing the student movements on the Portuguese educational system, at the NUTS 3 granularity level. The prediction models will be decomposed into several segments corresponding to the 6 stages of education available for the students. Some common estimates in all the segments will be admissions, progressions, dropouts, all on a yearly basis. Data is isolated and augmented with contextual variables of socio-economic data, available at the National Institute of Statistics (INE) and at Pordata, that can be useful for defining policies as well as to take specific corrective measures. | National | Portugal | PT | Directorate-General for Education and Science Statistics | Central-Government | Education | Education n.e.c. | Pilot | 2.019 | 2022 | Analysis, monitoring and regulatory research | Information analysis processes | No | No | Artificial Intelligence | G2G | x | x | x | x | https://www.lasige.pt/project/modest/ | Reasoning | Automated reasoning | Planning and Scheduling | 02/11/2023 | |||||||||||||||||
| PSTW-1015 | Artificial Intelligence for traffic signals - KI4LSA | https://bmdv.bund.de/SharedDocs/DE/Artikel/DG/mfund-projekte/ki4lsa.html#:~:text=Ziel%20des%20Projektes%20%E2%80%9E%20KI4LSA%20%E2%80%9C%20war,Simulation%20trainiert%20und%20anschlie%C3%9Fend%20ausgewertet. | The increasing inner-city traffic leads to environmental pollution (noise, exhaust fumes), long journey times and increased fuel consumption for road users. An essential lever for improving the flow of traffic in inner-city areas lies in the optimization of traffic signal systems (LSA). The aim of the " KI4LSA " project was therefore to use reinforcement learning (RL) - a method of artificial intelligence - to control the LSA in such a way that the traffic flow is optimized. For this purpose, the AI was trained in a simulation and then evaluated. | Local | Germany | DEA | Municipalities of Bielefeld, Gütersloh, Lemgo, Neuss, Rheine and Soest | Local Government | Economic Affairs | Transport | Pilot | 2.022 | Enforcement | Smart Recognition processes | No | No | Artificial Intelligence | G2G | x | x | Bendszusn, R. (2022). Make-or-buy in the area of Artificial Intelligence: Insights from AI use cases in the German public sector (master's thesis). Hertie School, Berlin. | Perception | Computer vision | 29/08/2023 | |||||||||||||||||||||
| PSTW-1022 | AI Beach Capacity Monitoring | https://www.calellabarcelona.com/en/news/the-city-council-will-control-the-capacity-of-the-beach-with-an-artificial-intelligence-system/, https://ajuntament.barcelona.cat/digital/en/blog/barcelona-promotes-the-ethical-use-of-artificial-intelligence | The City Council has re-contracted the services of the company DatActions to implement the DasEyes application, whose function is to sectorize the beaches in multiple virtual areas in order to detect the number of people in each sector. There will also be a webcam that will allow you to have a zenithal image. All this data will be treated, as last year, completely anonymously and scrupulously respecting the data protection law. On weekends, when there is more confluence and traffic on the beach, municipal agents will be provided with tools to monitor capacity; these agents will patrol to make sure there are no problems and ensure order in the areas. In addition, to make it easier for them, Artificial Intelligence methods make it possible to predict when the beaches will be filled. Depending on the data, the agents will open and close the different sections to the public in such a way that there will always be a safe capacity in all areas. | Local | Spain | ES51 | Calella Municipality | Local Government | Public order and safety | R&D public order and safety. | Implemented | 2.020 | Enforcement | Smart Recognition processes | No | No | Artificial Intelligence | G2G | x | x | https://gouai.cidob.org/atlas/, https://ajuntament.barcelona.cat/digital/en/blog/barcelona-promotes-the-ethical-use-of-artificial-intelligence | Perception | Computer vision | Image processing | 05/07/2023 | ||||||||||||||||||||
| PSTW-1023 | AI to support decision-making processes in social services | https://ajuntament.barcelona.cat/digital/en/blog/barcelona-promotes-the-ethical-use-of-artificial-intelligence | The municipal social services deal with an average of 50,000 initial visits every year ranging through a variety of issues (from financial or addiction problems to gender-based violence) and are handled by a team of over 700 professionals. An algorithm provides the staff with digital support in the decision-making process. Having been trained with a corpus of 300,000 interviews, it suggests the appropriate resources for each case. It's a recommendation algorithm, hence, the algorithm is an aid for the decision-making process, the decision is ultimately made by the professional handling the case. The algorithm was audited by an external third party. | Local | Spain | ES51 | Barcelona City Council | Local Government | Social protection | Social protection n.e.c. | Implemented | 2.021 | Public services and engagement | Service personalisation (various) | No | No | Artificial Intelligence | G2G | x | x | x | https://isocial.cat/en/dpr-a-smart-tool-to-facilitate-the-work-of-primary-care-social-service-professionals/ | Learning | Machine learning | 05/07/2023 | ||||||||||||||||||||
| PSTW-1024 | Robotic Automation Plan | https://ajuntament.barcelona.cat/imi/en/projects/robotics-process-automation-rpa | The Robot Automation Plan has created a new service for robotic process automation. The aim behind the project is to provide the City Council with innovative solutions, such as increasing the quality of citizen help and information services and reducing human error in processes that are repetitive and with little added value, increasing the Council’s production capacity, for example in processing licences for café terraces, and increasing the guarantee and transparency of processes and ensuring coherency in the data processed. The purpose of this initiative is to free up the time that workers currently spend on manual, repetitive tasks that are of little added value, so they can devote their time to providing real value to the organisation and reduce the time it takes to respond to requests. | Local | Spain | ES51 | Barcelona City Council | Local Government | General public services | General public services n.e.c. | Implemented | 2.019 | Internal management | Internal support processes | No | No | Artificial Intelligence | G2G | x | x | https://ajuntament.barcelona.cat/imi/en/projects/robotics-process-automation-rpa | Integration and Interaction | Robotics and Automation | 05/07/2023 | |||||||||||||||||||||
| PSTW-1026 | ELASTIC Autonomous Transport Network | https://elastic-project.eu/ | The ELASTIC project was a European collaborative initiative aimed at developing a software architecture for advanced mobility systems and autonomous transport networks. The first pilot was trialled and deployed in Florence's tramway network until June 2022. AI sensors were installed in three tram vehicles and tram stops. Sensors feature cameras, Inertial Measurement Units (IMUs), Radar and Lidar, amongst others. The data generate during each journey was processed through AI methods, from which valuable knowledge in real-time regarding the tram position, the presence of obstacles along the tram line and tram stops, and the movement of citizens and vehicles is extracted. The images were processed in real time, the information extracted was passed along, while the images were discarded. No personal information such as facial recognition or plate identification was processed. | Regional | Italy | ITI1 | Florence Metropolitan City | Local Government | Public order and safety | Police Services | Pilot | 2.020 | 2022 | Analysis, monitoring and regulatory research | Information analysis processes | No | No | Artificial Intelligence | G2G | x | x | https://elastic-project.eu/about/objectives | Perception | Computer vision | object recognition | 06/07/2023 | |||||||||||||||||||
| PSTW-1027 | Nantes Social Water Pricing | https://metropole.nantes.fr/tarification-eau#serviceTocEntry1 | Nantes Métropole guarantees accessibility to water for all with a single tariff applied in the 24 municipalities of the conurbation. Social Water pricing allows some households not to devote more than 3% of their income to the water bill. Nantes Métropole has developed an algorithm that determines eligibility for aid for drinking water. This algorithm concerns the declarative component of social water pricing which targets very specific beneficiaries. The calculation of this aid takes into account household income and family composition. Users make their request at the town hall. The agents collect their supporting documents and enter the information required by the algorithm in software developed by Nantes Métropole (Deltas software). Users are immediately notified of the result by the agent at the town hall. | Local | France | FRG0 | Nantes Métropole & Ville | Local Government | Social protection | Social protection n.e.c. | Implemented | 2.020 | Adjudication | Taking decisions on benefits | No | No | Artificial Intelligence | G2C | x | x | x | x | x | https://data.nantesmetropole.fr/pages/algorithmes_nantes_metropole/ | Learning | Machine learning | automatic classification | 06/07/2023 | |||||||||||||||||
| PSTW-1028 | Nantes Solidarity Transport Pricing | https://data.nantesmetropole.fr/pages/algorithmes_nantes_metropole/ | Nantes Métropole developed an algorithm that determines eligibility for a partial or absolute reduction on travel expenses on the Nantes metropolitan transport network. The calculation of this aid takes into account household income and family composition. Users make their request at the town hall. The agents collect their supporting documents and enter the information required by the algorithm in software developed by Nantes Métropole (Deltas software). Users are immediately notified of the result by the agent at the town hall. | Local | France | FRG0 | Nantes Métropole & Ville | Local Government | Social protection | Social protection n.e.c. | Implemented | 2.020 | Adjudication | Taking decisions on benefits | No | No | Artificial Intelligence | G2C | x | x | x | x | x | https://data.nantesmetropole.fr/pages/algorithmes_nantes_metropole/ | Learning | Machine learning | automatic classification | 06/07/2023 | |||||||||||||||||
| PSTW-1030 | Carbon Intelligent City - Paris | https://ai4cities.eu/pilots/energy-c-incity | This pilot is part of the AI4Cities Project. C-in.City is the new generation of GHG information system, a service to monitor and manage all urban emissions (housing, commercial, public institutions, transportation, industries, power production) at 3 actionable scales (city, district, building/street) that helps city managers, citizens, NGOs and businesses to better understand local emissions, take individual and collective action, and implement transparent and science-based impact monitoring. The research on emissions monitoring is visualised in a panel of datasets available thanks to AI in one tool. The AI deployed is used for two main purposes: extracting activity signals from AOIs (Areas Of Interests) and inferring CO2 emissions from these signals. In short, the algorithms automatically detect when an industrial site is active (i.e. detecting fumes above a waste burning plant thanks to satellite imagery) and can infer from it the associated emissions. | Local | France | FR10 | Greater Paris | Local Government | Environmental Protection | Pollution abatement. | Pilot | 2.020 | Analysis, monitoring and regulatory research | Information analysis processes | No | No | Artificial Intelligence | G2C | x | x | x | x | x | x | https://ai4cities.eu/pilots/energy-c-incity | Perception | Computer vision | sensor network | 06/07/2023 | ||||||||||||||||
| PSTW-1031 | Carbon Intelligent City - Copenhagen | https://ai4cities.eu/pilots/energy-c-incity | This pilot is part of the AI4Cities Project. C-in.City is the new generation of GHG information system, a service to monitor and manage all urban emissions (housing, commercial, public institutions, transportation, industries, power production) at 3 actionable scales (city, district, building/street) that helps city managers, citizens, NGOs and businesses to better understand local emissions, take individual and collective action, and implement transparent and science-based impact monitoring. The research on emissions monitoring is visualised in a panel of datasets available thanks to AI in one tool. The AI deployed is used for two main purposes: extracting activity signals from AOIs (Areas Of Interests) and inferring CO2 emissions from these signals. In short, the algorithms automatically detect when an industrial site is active (i.e. detecting fumes above a waste burning plant thanks to satellite imagery) and can infer from it the associated emissions. | Local | Denmark | DK01 | City of Copenhagen | Local Government | Environmental Protection | Pollution abatement. | Pilot | 2.020 | Analysis, monitoring and regulatory research | Information analysis processes | No | No | Artificial Intelligence | G2C | x | x | x | x | x | x | https://ai4cities.eu/pilots/energy-c-incity | Perception | Computer vision | sensor network | 06/07/2023 | ||||||||||||||||
| PSTW-1032 | IX3 - Mobility Pilot Project in Paris | https://ai4cities.eu/pilots/mobility-ix3 | IX3, part of the AI4Cities project, is an auxiliary optimising system for traffic light management, which reduces unnecessary stopping and waiting in red lights. Reducing the amount of stopping and re-accelerating a vehicle in traffic has a surprisingly large impact on emissions. Tests and piloting over earlier AI4Cities phases have proven that city-wide adoption of the IX3-system has a reduction impact of around 2% on traffic related emissions. The system combines real-time machine vision sensoring to traffic light controllers and thus enables optimising traffic management logic. The system has been developed in collaboration with machine vision expert MarshallAI and Dynniq who has decades long experience in traffic management. Moreover, The system collects only anonymous traffic data with no personal identifiers. The video footage itself is not saved other than for quality assurance purposes. | Local | France | FR10 | Greater Paris | Local Government | Housing and community amenities | Street lighting. | Pilot | 2.020 | Enforcement | Smart Recognition processes | No | No | Artificial Intelligence | G2C | x | x | https://ai4cities.eu/pilots/mobility-ix2 | Perception | Computer vision | object recognition | 06/07/2023 | ||||||||||||||||||||
| PSTW-1033 | IX3 - Mobility Pilot Project in Helsinki | https://ai4cities.eu/pilots/mobility-ix3 | IX3, part of the AI4Cities project, is an auxiliary optimising system for traffic light management, which reduces unnecessary stopping and waiting in red lights. Reducing the amount of stopping and re-accelerating a vehicle in traffic has a surprisingly large impact on emissions. Tests and piloting over earlier AI4Cities phases have proven that city-wide adoption of the IX3-system has a reduction impact of around 2% on traffic related emissions. The system combines real-time machine vision sensoring to traffic light controllers and thus enables optimising traffic management logic. The system has been developed in collaboration with machine vision expert MarshallAI and Dynniq who has decades long experience in traffic management. Moreover, The system collects only anonymous traffic data with no personal identifiers. The video footage itself is not saved other than for quality assurance purposes. | Local | Finland | FI1B | City of Helsinki | Local Government | Housing and community amenities | Street lighting. | Pilot | 2.020 | Enforcement | Smart Recognition processes | No | No | Artificial Intelligence | G2C | x | x | https://ai4cities.eu/pilots/mobility-ix3 | Perception | Computer vision | object recognition | 06/07/2023 | ||||||||||||||||||||
| PSTW-1034 | BerDiBa Project: Berlin Digital Railway Operation | https://www.berlin.de/sen/web/presse/pressemitteilungen/2021/pressemitteilung.1102446.php | Belin Digital Railway Operations (BerDIBA) project aims to develop automated rail driving. Over a 4 year period, a consortium of 12 partners will work to develop and test technologies to equip automated trains with AI able to detect obstacles and to analyse the state of rail infrastructure. As part of the established technology and innovation funding programme ProFIT, the state of Berlin is funding application-oriented research in the field of digital rail operations as another innovative component of the large-scale Siemensstadt project. The aim is to research and test new technologies for automated rail travel under real operating conditions, e.g. artificial intelligence for detecting obstacles in the track, hazards to passengers on the train and monitoring changes in the rail infrastructure. The basis for this are high-performance sensor systems for environment perception on and in the train. | Local | Germany | DE30 | City of Berlin | Local Government | Public order and safety | Police Services | In development | 2.021 | Enforcement | Smart Recognition processes | No | No | Artificial Intelligence | G2G | x | x | https://www.berlin.de/sen/web/presse/pressemitteilungen/2021/pressemitteilung.1102446.php | Perception | Computer vision | object recognition | 06/07/2023 | ||||||||||||||||||||
| PSTW-1035 | Signalen - AI Categorization of Public Space Reports | https://signalen.org/ | Signalen is an open-source process and task system from, by and for municipalities, which automatically categorizes and routes reports about public space for processing by the appropriate handler. Signalen's software code is public, API-driven and generically applicable to any municipality in the Netherlands. With it a number of Dutch municipalities serving more than 2 million residents process more than 600,000 reports per year. Some of these municipalities are: Amsterdam, Woensdrecht, Zundert, Hertogenbosch, Alphen aan den Rijn, Almere, Heerlen, Urk, Groninger, Den Hoag, Utrecht, Bergen op Zoom and Waadhoeke. Personal data is not required or mandatory to report. On the other hand, someone reporting can leave their contact details if they wish civil servants inform them later on of the progress. This information is not used by the algorithm. On non-discrimination, given the algorithm recognises mainly Dutch words, if someone uses another language, another department will assess the report. | Local | Netherlands | NL | City of Amsterdam and other dutch municipalities | Local Government | General public services | General services. | Implemented | 2.020 | Public services and engagement | Engagement management | No | No | Artificial Intelligence | G2C | x | x | x | x | x | x | https://signalen.org/ | Communication | Natural language processing | information retrieval | 06/07/2023 | ||||||||||||||||
| PSTW-1036 | Energy Optimization of Buildings | https://cphsolutionslab.dk/en/news/kunstig-intelligens-skal-reducere-energiforbruget-i-koebenhavns-kommune | Copenhagen Solutions Lab and Copenhagen City Properties, Facility Management and Procurement are collaborating to reduce energy consumption in the municipality's buildings using AI and data-supported tools. This will help reduce CO2 emissions and the municipality's heating and electricity bills, while maintaining a good indoor climate in the buildings. The final result of the project will be concrete AI tools to optimize energy-efficient operation and indoor climate, while taking into account fluctuating loads in the supply network. | Local | Denmark | DK01 | City of Copenhagen | Local Government | Economic Affairs | Fuel and energy | Pilot | 2.021 | Analysis, monitoring and regulatory research | Information analysis processes | No | No | Artificial Intelligence | G2C | x | x | https://cphsolutionslab.dk/en/news/kunstig-intelligens-skal-reducere-energiforbruget-i-koebenhavns-kommune | Learning | Machine learning | probabilistic model | 06/07/2023 | ||||||||||||||||||||
| PSTW-1038 | AI4Cities project - HOLONI | https://ai4cities.eu/pilots/energy-holoni | HOLONI is an AI4Cities project that enables municipalities, local sustainable brands and energy retailers to assess the true potential of city solar, exchange local green energy and, at the same time, reinvent their community and commercial relationships to prosumers towards collective sustainable impact. HOLONI uses AI to predict and analyze solar surplus potential across the city. | Local | Denmark | DK01 | City of Copenhagen | Local Government | Economic Affairs | Fuel and energy | Pilot | 2.020 | Analysis, monitoring and regulatory research | Prediction and planning | No | No | Artificial Intelligence | G2C | x | x | x | x | https://ai4cities.eu/fileadmin/user_upload/Holoni_case_study.pdf | Learning | Machine learning | 06/07/2023 | |||||||||||||||||||
| PSTW-1039 | Spike, Energy Pilot Project - Copenhagen | https://ai4cities.eu/pilots/energy-spike | SPIKE is a pilot from the AI4Cities project, a scalable “plug&play” kit of devices that can be installed in every building to fine-tune energy usage in real-time, allowing 20% (on average) operational savings and over 90% in-comfort time for occupants, without any drastic changes to the existing HVAC. The company's most recent solution is an all-in-one-platform, implementing the concept of “Energy as a Service”, which helps orchestrate energy loads and renewable energy production within energy communities. SPIKE aims to become the world’s first enabler for easily creating a Virtual Power Plant (VPP) at urban level. | Local | Denmark | DK01 | City of Copenhagen | Local Government | Economic Affairs | Fuel and energy | Pilot | 2.020 | Analysis, monitoring and regulatory research | Prediction and planning | No | No | Artificial Intelligence | G2C | x | x | x | https://ai4cities.eu/fileadmin/user_upload/Spike_case_study.pdf | Learning | Machine learning | 06/07/2023 | ||||||||||||||||||||
| PSTW-104 | WISDom - Water Intelligence Data | https://arquivo.pt/wayback/20190323223813mp_/https://www.fct.pt/noticias/docs/Nelson_Carrico.pdf | The WISDOM project aims to develop algorithms to extract relevant information from Water Intelligence System Data in order to support decisions, improve network management, reduce water losses, and ensure a proper water supply in quantity and quality. The project consists of five major tasks: (1) exploratory data analysis; (2) predictive analysis of water consumption; (3) spatial location of breaks; (4) identification and anticipation of anomalous events; and (5) development of a prototype system for user recommendations and decision support. | National | Portugal | PT | Polytechnic Institute of Setúbal | Central-Government | Housing and community amenities | Water supply. | Implemented | 2.019 | 2021 | Analysis, monitoring and regulatory research | Prediction and planning | No | No | Artificial Intelligence | G2G | x | x | x | x | x | https://arquivo.pt/wayback/20190323223813mp_/https://www.fct.pt/noticias/docs/Nelson_Carrico.pdf | Reasoning | Automated reasoning | Planning and Scheduling | decision support | 02/11/2023 | |||||||||||||||
| PSTW-1040 | Spike, Energy Pilot Project - Amsterdam | https://ai4cities.eu/pilots/energy-spike | SPIKE is a pilot from the AI4Cities project, a scalable “plug&play” kit of devices that can be installed in every building to fine-tune energy usage in real-time, allowing 20% (on average) operational savings and over 90% in-comfort time for occupants, without any drastic changes to the existing HVAC. The company's most recent solution is an all-in-one-platform, implementing the concept of “Energy as a Service”, which helps orchestrate energy loads and renewable energy production within energy communities. SPIKE aims to become the world’s first enabler for easily creating a Virtual Power Plant (VPP) at urban level. | Local | Netherlands | NL32 | City of Amsterdam | Local Government | Economic Affairs | Fuel and energy | Pilot | 2.020 | Analysis, monitoring and regulatory research | Prediction and planning | No | No | Artificial Intelligence | G2C | x | x | x | https://ai4cities.eu/fileadmin/user_upload/Spike_case_study.pdf | Learning | Machine learning | 06/07/2023 | ||||||||||||||||||||
| PSTW-1043 | LAIban - A chatbot for children | https://laiban.helsingborg.se/ | The City of Helsingborg uses LAIban in the municipal day care centres, responding to childrens’ daily questions about meals, playtime, pick-up times and more. It is designed to complement the teachers’ role, enabling children to develop independently. LAlban is used in all 80 public preschools in Helsingborg. To ensure inclusion of and for children, children have been directly included in the design process for LAlban’s applications and updates. For instance, children often ask the AI chatbot new questions and offer suggestions on additional features, enabling designers to update LAlban with abilities and insights that are useful for the primary users. LAlban also uses up-to-date data on the demographics of its users to help provide answers in a variety of languages so that no child risks being excluded. The chatbot understands and can formulate responses in Swedish, Arabic, English, French, Russian, Turkish, Spanish, Mandarin, Japanese, Danish and Finnish. To provide transparency, explainability, and accountability for children, LAlban is programmed to explain to children what an AI chatbot is. | Local | Sweden | SE22 | Helsingborg Municipality | Local Government | Education | Pre-primary and primary education. | Implemented | 2.020 | Public services and engagement | Service personalisation (various) | No | No | Artificial Intelligence | G2C | x | x | x | x | x | x | https://www.unicef.org/globalinsight/media/2346/file | Communication | Natural language processing | AI Services | chatbot | 06/07/2023 | |||||||||||||||
| PSTW-1044 | AI Safety Perception Patterns | https://www.senseablestockholm.org/sv/projects/kartlaggning-av-upplevd-trygghet-med-ai-1.1143132 | Senseable Stockholm Lab (a collaboration between KTH, MIT Massachusetts Institute of Technology and the city of StockholmI) used a combination of data sources to use AI to create a map of safety in Stockholm. The ultimate goal of the research was to develop a prototype for a long-term measurement platform using AI that can be reproduced. The results can be displayed in the City of Stockholm's GIS platform so that planners and architects can benefit from the results and knowledge for planning and designing new projects. The algorithms and web surveys can be replicated with the exact same code year after year, so that the city can understand the effect of interventions. | Local | Sweden | SE11 | City of Stockholm | Local Government | Public order and safety | R&D public order and safety. | Pilot | 2.021 | 2022 | Analysis, monitoring and regulatory research | Innovating Public Policy | No | No | Artificial Intelligence | G2B | x | x | https://www.senseablestockholm.org/projects/kartlaggning-av-upplevd-trygghet-med-ai-1.1143132 | Learning | Machine learning | 06/07/2023 | ||||||||||||||||||||
| PSTW-1045 | AVENUE Pilot Project - Tallin | https://ai4cities.eu/pilots/mobility-avenue | VENUE aims to align shared mobility policies with GHG emission reduction targets. It has developed an AI-powered decision support tool that allows cities to measure and monitor the reduction of the carbon footprint derived from different shared mobility regulatory frameworks and policy strategies. The initiative seeks to respond to the pressing need of city leaders and policymakers of a data-driven solution that can help them take measurable and up-to-date decisions related to the implementation of smart mobility systems from a climate change mitigation perspective. The AVENUE project exploits the information provided by two existing solutions for collecting and leveraging geolocated big data: Nommon’s Mobility Analytics solution, which processes the registers from anonymised mobile network data and other geolocated sources to provide actionable insights about people’s activity and mobility patterns, and Populus’ Mobility Manager, which enables cities to gather and analyse the data that mobility operators share with authorities to manage the enforcement of regulatory measures. The combination of this information with other data sources available by cities will be used to develop demand prediction models capable of simulating the modal choice process around shared mobility services and the way these modal choices can be influenced by different regulatory strategies. The outcome of these models will serve to evaluate the carbon footprint effects of different possible measures. | Local | Estonia | EE00 | Tallinn Municipality | Local Government | Environmental Protection | Pollution abatement. | Pilot | 2.022 | Analysis, monitoring and regulatory research | Innovating Public Policy | No | No | Artificial Intelligence | G2B | x | x | x | x | https://ai4cities.eu/fileadmin/user_upload/Avenue_case_study.pdf | Learning | Machine learning | decision support | 06/07/2023 | ||||||||||||||||||
| PSTW-1046 | AVENUE Pilot Project - Stavanger | https://ai4cities.eu/pilots/mobility-avenue | VENUE aims to align shared mobility policies with GHG emission reduction targets. It has developed an AI-powered decision support tool that allows cities to measure and monitor the reduction of the carbon footprint derived from different shared mobility regulatory frameworks and policy strategies. The initiative seeks to respond to the pressing need of city leaders and policymakers of a data-driven solution that can help them take measurable and up-to-date decisions related to the implementation of smart mobility systems from a climate change mitigation perspective. The AVENUE project exploits the information provided by two existing solutions for collecting and leveraging geolocated big data: Nommon’s Mobility Analytics solution, which processes the registers from anonymised mobile network data and other geolocated sources to provide actionable insights about people’s activity and mobility patterns, and Populus’ Mobility Manager, which enables cities to gather and analyse the data that mobility operators share with authorities to manage the enforcement of regulatory measures. The combination of this information with other data sources available by cities will be used to develop demand prediction models capable of simulating the modal choice process around shared mobility services and the way these modal choices can be influenced by different regulatory strategies. The outcome of these models will serve to evaluate the carbon footprint effects of different possible measures. | Local | Norway | NO04 | City of Stavanger | Local Government | Environmental Protection | Pollution abatement. | Pilot | 2.022 | Analysis, monitoring and regulatory research | Innovating Public Policy | No | No | Artificial Intelligence | G2G | x | x | x | x | https://ai4cities.eu/fileadmin/user_upload/Avenue_case_study.pdf | Learning | Machine learning | decision support | 06/07/2023 | ||||||||||||||||||
| PSTW-1047 | MPAT - Mobility Pilot Project - Tallin | https://ai4cities.eu/fileadmin/user_upload/MPAT_tool_case_study.pdf | The MPAT tool (Mobility Policy Auto Tuner) is an engine to optimize the CO2 emission-reduction potential of city mobility policies, beginning with shared micro-mobility. By understanding the geographies where a trip on an electric-powered shared bicycle, scooter, or moped is most likely to create an emissions saving (ie, to replace an internal combustion engine vehicle trip), the tool is able to make recommendations for areas to implement new policies (ex, subsidies on rides, or removals of fleet caps). The impact of these policies can be monitored with a specific view on CO2 emissions savings. MPAT’s calculates shared mobility’s CO2 savings potential, also anticipating its growth and change. By using AI to forecast where demand for low-carbon micro-mobility trips will grow, it goes beyond currently existing practices for modelling the decarbonization potential of mode shift and can directly inform policy making to realise that potential. | Local | Estonia | EE00 | Tallinn Municipality | Local Government | Environmental Protection | Pollution abatement. | Pilot | 2.020 | Analysis, monitoring and regulatory research | Innovating Public Policy | No | No | Artificial Intelligence | G2G | x | x | https://ai4cities.eu/fileadmin/user_upload/MPAT_tool_case_study.pdf | Learning | Machine learning | 06/07/2023 | |||||||||||||||||||||
| PSTW-1048 | MPAT - Mobility Pilot Project - Amsterdam | https://ai4cities.eu/fileadmin/user_upload/MPAT_tool_case_study.pdf | The MPAT tool (Mobility Policy Auto Tuner) is an engine to optimize the CO2 emission-reduction potential of city mobility policies, beginning with shared micro-mobility. By understanding the geographies where a trip on an electric-powered shared bicycle, scooter, or moped is most likely to create an emissions saving (ie, to replace an internal combustion engine vehicle trip), the tool is able to make recommendations for areas to implement new policies (ex, subsidies on rides, or removals of fleet caps). The impact of these policies can be monitored with a specific view on CO2 emissions savings. MPAT’s calculates shared mobility’s CO2 savings potential, also anticipating its growth and change. By using AI to forecast where demand for low-carbon micro-mobility trips will grow, it goes beyond currently existing practices for modelling the decarbonization potential of mode shift and can directly inform policy making to realise that potential. | Local | Netherlands | NL32 | City of Amsterdam | Local Government | Environmental Protection | Pollution abatement. | Pilot | 2.020 | Internal management | Internal primary processes | No | Yes | Artificial Intelligence | G2G | x | x | https://ai4cities.eu/fileadmin/user_upload/MPAT_tool_case_study.pdf | Learning | Machine learning | 22/03/2024 | |||||||||||||||||||||
| PSTW-1049 | Milli, AI Chatbot for Mental Health | https://www.unicef.org/globalinsight/media/2081/file | Milli is an AI-powered chatbot that helps adolescents in Finland learn about mental health issues. Milli is the result of collective research between interdisciplinary experts and practitioners (psychologists, mental health experts, nurses, AI and design engineers), and has been designed to continuously improved through an iterative and inclusive process involving users. Milli fields 500-1,200 queries weekly. It allows users to anonymously ask questions about the mental health issues they may be facing, then connects them with mental health information or medical providers. The chatbot has been trained to discern between adolescent and adult users and tailors its responses accordingly. Milli can also ascertain if a user is experiencing a health emergency, for instance, situations of self-harm, and effectively directs the user to reach out to emergency services, authority figures or trusted adults – depending on the severity of the situation. Furthermore, if users enter any identifying information, Milli automatically deletes it. This ensures that children’s data and privacy are secure. Also committed to transparency and accountability, Milli provides detailed responses if a user enquires about how their data is used, while explaining how their messages are stored anonymously to support the development of the app. It also offers detailed explanations on how AI works, who developed the chatbot, and how it learns through each discussion. In the future, the team behind Milli hopes to focus on prioritizing fairness and non-discrimination by ensuring the virtual assistant meets European Union accessibility requirements, as well as rolling out gender-sensitive content and vocabulary. | Local | Finland | FI1B | Helsinki University Hospital | Local Government | Health | Public health services. | Implemented | 2.019 | Public services and engagement | Service personalisation (various) | No | No | Artificial Intelligence | G2C | x | x | x | x | x | x | https://www.unicef.org/globalinsight/media/2081/file | Communication | Natural language processing | AI Services | chatbot | 06/07/2023 | |||||||||||||||
| PSTW-105 | Bucharest airport Face recognition - Detection of wanted persons and unsafe situations | https://www.bucharestairports.ro/cnab/en/around-the-world/tomorrow-s-best-airport-security-is-already-in-your-face | A facial recognition system will be implemented in Bucarest-Henri Coandă Airport. The AI will be capable of both identifying wanted persons, terrorism subjects or others on the list of intelligence services as well as a solution which detects suspicious behaviour. | Local | Romania | RO | Bucarest-Henri Coandă Airport | Local Government | Public order and safety | Public order and safety n.e.c. | Implemented | 2.014 | Enforcement | Smart Recognition processes | No | No | Artificial Intelligence | G2G | x | x | x | https://www.bucharestairports.ro/cnab/en/around-the-world/tomorrow-s-best-airport-security-is-already-in-your-face | Perception | Computer vision | Machine learning | facial recognition | 02/11/2023 | ||||||||||||||||||
| PSTW-1050 | Intelligent Wellness Platform Experiment | https://www.tietoevry.com/en/success-stories/2018/the-city-of-espoo-a-unique-experiment/ | Experiment featuring a customer-centric service that combined through AI social, healthcare and education data of all Espoo's citizens to identify their needs. The starting point was to test whether AI can help target services preventively, the answer was a strong yes. In particular, the predictions were used to plan social and healthcare services to prevent social exclusion. “The starting point for the project was to test if AI can help to target preventive services to individuals at the right time so that the city can support individual wellbeing. Tieto and the City of Espoo jointly handled a huge data mass that consisted of client relationship data of the entire population of Espoo for the years 2002–2016 and covered approximately 520,000 people and more than 37 million customer contacts. All data processing included extreme measures to ensure information security. Personal data, such as names, identity numbers and addresses were concealed already during data collection. Encryption was used for all data transmission. Our experiment demonstrated that artificial intelligence and the utilisation of data could have a significant role in health care. With support from AI and data analytics, new service paths can be developed. Social and healthcare service professionals can also utilise AI in their daily work to support decision making. | Local | Finland | FI1B | Espoo Municipality | Local Government | Social protection | Social protection n.e.c. | Pilot | 2.018 | Public services and engagement | Service personalisation (various) | No | No | Artificial Intelligence | G2C | x | x | x | https://www.tietoevry.com/en/success-stories/2018/the-city-of-espoo-a-unique-experiment/ | Learning | Machine learning | data analytics | 06/07/2023 | |||||||||||||||||||
| PSTW-1051 | Gallery Visitor's AI Analysis | https://smartdublin.ie/dublins-hugh-lane-gallery-understanding-visitor-patterns-and-flows-using-a-unique-privacy-by-design-approach/ | The Hugh Lane Gallery, working with Dublin City Council’s Smart City team, set out to identify technological solutions that would provide accurate, non-intrusive analytics, measuring how many visitors attend the Gallery and how they move throughout the Gallery. This vital information can assist in exhibition curation; optimising and enhancing the experience of visitors, improving and understanding space utilisation, as well as providing important health and safety information. Working with technology provider Arm, an innovative, privacy-enhanced technology was identified, that gathers and analyses anonymised data from a system of connected cameras within the Gallery. The use of ‘Heat Mapping’ which is a data visualisation technique will assist greater e-scooter safety, by flagging footpath riding incidents indicating problematic junctions or inadequate cycling infrastructure. | Local | Ireland | IE06 | Dublin City Council | Local Government | Recreation, culture and religion | Cultural services. | In development | 2.020 | Analysis, monitoring and regulatory research | Information analysis processes | No | No | Artificial Intelligence | G2G | x | x | https://smartdublin.ie/dublins-hugh-lane-gallery-understanding-visitor-patterns-and-flows-using-a-unique-privacy-by-design-approach/ | Perception | Computer vision | 06/07/2023 | |||||||||||||||||||||
| PSTW-1052 | AI-controlled Smart Traffic Junctions | https://www.smarttransport.org.uk/news/latest-news/greater-manchester-to-roll-out-smart-ai-traffic-junctions | Transport for Greater Manchester (TfGM) rolls out of Vivacity's AI-controlled ‘smart’ traffic junctions to accommodate the increase of active travel modes, such as cycling and walking. Using sensors with inbuilt artificial intelligence, Vivacity enables TfGM to anonymously identify different types of road users at selected junctions and control traffic signals to allow different modes of transportation to be prioritised as and when required. With more cyclists on the road as people avoided public transport, these ‘smart junctions’ were able to give priority to people on foot or bike where and when appropriate. This comes as part of a three-year Innovate UK co-funded programme (alongside Immense Simulations) to use AI to optimise traffic networks. The project scaled up to an area of 20 junctions by the end of 2021. | Local | United Kingdom | UKD3 | Greater Manchester | Local Government | Economic Affairs | R&D economic affairs | Implemented | 2.020 | Analysis, monitoring and regulatory research | Innovating Public Policy | No | No | Artificial Intelligence | G2G | x | x | https://vivacitylabs.com/tfgm-active-travel-scheme/ | Perception | Computer vision | sensor network | 06/07/2023 | ||||||||||||||||||||
| PSTW-1054 | Gavius Virtual Assistant | https://gavius.eu/?lang=en | The Gavà City Council is the leader of the project, but has the help of other 7 partners. A public-private partnership that has been essential for Gavius to get ahead. Gavius is an innovative virtual assistant which uses AI technology to communicate to the citizens the social aids that they have at their disposal, process them, grant them and perceive them in a comfortable, fast and simple way, via a mobile device. The new virtual assistant will be applied in the field of social services, but has the possibility of being implemented in other uses that improve the relationship of the administration with the citizens. Two more virtual assistants are also being developed: one for staff and the other for managers. The service is part of a project financed by ERDF funds through the Urban Innovative Actions initiative. The project ended on February 28, 2023. | Local | Spain | ES51 | Gava Municipality | Local Government | Social protection | Social protection n.e.c. | In development | 2.021 | 2023 | Adjudication | Taking decisions on benefits | No | No | Artificial Intelligence | G2C | x | x | x | x | https://www.usercentricities.eu/services/gavius-virtual-assistant | Learning | Machine learning | 06/07/2023 | ||||||||||||||||||
| PSTW-1055 | Rimini Chatbot | https://www.usercentricities.eu/services/rimini-chatbot | The Digital Assistant (Chatbot) is an innovative tool available 7/24, that supports citizens looking for information related to all the administrative services offered on the institutional portal of the city of Rimini. Using a chat window it is possible to talk with the digital assistant, asking it questions and requests, obtaining information, assistance and support. The digital assistant was designed following the principles of conversational design in order to ensure an interaction experience that is as natural and intuitive as possible. Thanks to the use of artificial intelligence (AI) technology and deep learning algorithms, the Digital Assistant is able to understand user requests more and more precisely by answering an increasing number of questions. In this way, citizens who need to use the Municipality services, is supported and made autonomous in the search for information and in accessing the services themselves. The continuous availability and speed of response of the Digital Assistant allow to take advantage of a complementary channel than traditional ones (e-mail, telephone, physical counter ...) thus also lightening the workload of the operators. | Local | Italy | ITH5 | Rimini Municipality | Local Government | General public services | General public services n.e.c. | Implemented | 2.021 | Public services and engagement | Service personalisation (various) | No | No | Artificial Intelligence | G2C | x | x | x | x | x | x | https://www.usercentricities.eu/services/rimini-chatbot | Communication | Natural language processing | AI Services | Deep learning | Machine learning | chatbot | 06/07/2023 | |||||||||||||
| PSTW-1057 | Hello Charly - AI chatbot assisting students making decisions | https://www.cnews.fr/vie-numerique/2021-01-12/parcoursup-une-ia-veut-vous-aider-choisir-votre-orientation-1035198 | Called Hello Charly, this chatbot is following the trend for mobile messaging, inviting secondary school students to chat with it from a dedicated site, but also via the chatbots available on TikTok, Snapchat and Instagram. The idea here is to have access to a contact available 24 hours a day, since it is an artificial intelligence that aims to offer a personalised dialogue. For Hello Charly, the idea is to chat completely anonymously, and there's no need to register to start the conversation. The robot will then invite you to choose different answers to its questions or to write down or explain your plans, and it always starts by getting to know you better in order to understand your personality. In all, more than 850 professions are listed and 110,000 different training courses are offered, to cover all the needs of 14-24 year-olds. High-school students will be able to draw up a scorecard to help them see their plans more clearly, while the chatbot will also answer various questions. The Hello Charly start-up, which specialises in Edtech (education-related technologies), was a winner of the government's Programme d'investissement d'avenir project. It points out that its chatbot has been used by more than 220,000 people in France since it was created in 2016. | National | France | FR | France's Ministry of Istruction | Central-Government | Education | Education not definable by level. | Implemented | 2.016 | Public services and engagement | Service personalisation (various) | No | No | Artificial Intelligence | G2C | x | x | x | x | x | x | https://www.cnews.fr/vie-numerique/2021-01-12/parcoursup-une-ia-veut-vous-aider-choisir-votre-orientation-1035198 | Communication | Natural language processing | AI Services | chatbot | 06/07/2023 | |||||||||||||||
| PSTW-1059 | DELIA | Algorithm to predict location and perpetrator of crime | https://keycrime.com/predictive-crime-analysis/ | KeyCrime’s field trials have been executed over a lengthy time period and on a large scale in order to ensure long–term sustainability and repeatability of outcomes in different seasons and environments. The City of Milan started testing the software in 2008 and a third field trial commenced in 2019. After working in field trial with the KeyCrime solution, Milan’s Questura (main police station) migrated to a field trial of delia® which includes advances in software architecture, user interface and, most importantly, improvements in the crime linking engine. Initial results have been promising, with positive feedback received from the Questura after the initial months of use.The results of the testing were recorded and, during the field trials, all the documentation was evaluated by the Italian Ministry of Justice and also by the University of Essex to ensure that the evaluation would be fully objective. The test results (confirmed by the evaluators) have proven the effectiveness of the solution in fighting crime. The deployment of KeyCrime’s prototype software has led to a reduction of crime, by ca. 58% in the city of Milan in the period 2008-2019 for commercial robberies and by ca. 89% in the province of Milan for bank robberies in the period 2009-2019. | Local | Italy | ITC4 | City of Milan | Local Government | Public order and safety | Police Services | Pilot | 2.019 | Enforcement | Predictive enforcement processes | No | No | Artificial Intelligence | G2G | x | x | https://keycrime.com/results/ | Learning | Machine learning | 06/07/2023 | |||||||||||||||||||||
| PSTW-1061 | Resource Allocation System | https://www.devon.gov.uk/accesstoinformation/information_request/adult-residential-care-homes-and-resource-allocation/ | The Resource Allocation System (RAS) is just a tool used to generate an estimated budget for community care. Staff will use their judgement as to the amount of money estimated and the suitability of this budget to meet care and support needs. The Social Care professional, the person assessed and their nominated representatives will determine a support plan to meet the outcomes relevant to the identified needs. Support planning is the process which determines how the needs recorded in the assessment will be met for the individual in question. As part of this process, the estimated budget acts as guidance with regard to the likely order of budget that the local authority would expect to spend. The Council take into consideration the application of a strengths based approach and meet needs from the person’s own network and community. All records can be challenged reviewed. | Local | United Kingdom | UKK4 | Devon County Council | Local Government | General public services | General public services n.e.c. | Implemented | 2.021 | Adjudication | Taking decisions on benefits | No | No | Artificial Intelligence | G2G | x | x | x | https://www.devon.gov.uk/accesstoinformation/information_request/algorithms-or-machine-learning-systems/ | Learning | Machine learning | 06/07/2023 | ||||||||||||||||||||
| PSTW-1062 | 80 councils in the UK use AI to identify possible frauds in welfare claims | https://www.theguardian.com/society/2021/jul/18/calls-for-legal-review-of-uk-welfare-screening-system-that-factors-in-age | 80 councils in the UK have implemented an automated system designed to assess welfare claimants for potential fraud or errors with the help of a UK-based technology firm specializing in "risk-based verifications". This solution has come under scrutiny after revelations that its decisions have been influenced, in part, by the applicants' age, creating potential biases in the system's decision-making process. | Local | United Kingdom | UK | UK Municipalities | Local Government | Social protection | Social protection n.e.c. | Implemented | 2.021 | Enforcement | Supporting inspection processes | No | No | Artificial Intelligence | G2G | x | x | x | x | https://www.theguardian.com/society/2021/jul/18/calls-for-legal-review-of-uk-welfare-screening-system-that-factors-in-age | Learning | Machine learning | anomaly detection | 07/09/2023 | ||||||||||||||||||
| PSTW-1069 | Enhancing road safety through automatic identification of traffic violations | https://dt4regions.eu/dt-book/dt-stories/enhancing-road-safety-through-automatic-identification-traffic-violations | Road safety is a paramount concern due to the prevalence of traffic violations such as the absence of seat belts and distracted driving caused by mobile phone usage. These violations not only pose a risk to drivers and passengers but also contribute significantly to road accidents and human error-related sanctions. This presents an opportunity to develop a solution that can effectively identify and discourage these violations, thereby enhancing road safety and reducing the associated risks.. The goal is to improve road safety by identifying and deterring two common violations: the absence of seat belts and the use of mobile phones while driving. The story highlights the potential benefits of implementing a solution that utilizes Artificial Intelligence (AI) for automated violation detection and the optimization of the sanctioning process. | Regional | Spain | ES51 | Generalitat de Catalunya | Regional Government | Public order and safety | Public order and safety n.e.c. | In development | 2.021 | Enforcement | Supporting inspection processes | No | No | Artificial Intelligence | G2G | x | x | https://dt4regions.eu/dt-book/dt-stories/enhancing-road-safety-through-automatic-identification-traffic-violations | Perception | Computer vision | Image processing | 06/07/2023 | ||||||||||||||||||||
| PSTW-107 | Antonia - Automatic processing of requests of public services | https://primariaclujnapoca.ro/ | The City Hall of Cluj has an AI system called Antonia, which handles the automatic processing of 64 types of forms for requesting public services. The also has a chatbot component so she can answer questions about how to fill the forms. In the second development stage of the AI-based technology, Antonia will become a hologram, this being the surprise-element for the next stage. This depends on how fast we will work out the technical aspects, so there is "no time estimation for the complete implementation" according o the local officials in Cluj-Napoca. The project is estimated to be completed within 30 months' period. Antonia has been launched in April 2018 and functions around the clock. | Local | Romania | RO11 | Municipality of Cluj-Napoca | Local Government | General public services | Executive and legislative organs, financial and fiscal affairs, external affairs. | Implemented | 2.018 | Public services and engagement | Engagement management | No | No | Artificial Intelligence | G2C | x | x | x | https://www.romaniajournal.ro/society-people/antonia-the-first-virtual-public-servant-in-romania/ | Communication | Natural language processing | Machine learning | chatbot | 02/11/2023 | ||||||||||||||||||
| PSTW-1071 | Proactive administrative procedures | https://dt4regions.eu/dt-book/dt-stories/proactive-administrative-procedures | Proactive services will reduce administrative burdens. Citizens won’t have to care about not missing the application periods, neither they should fill the same forms again and again. Proactive services should make it sure that the public resources go to those who most need them, rather than to the citizens that have a bureaucratic expertise. The solution is designed to reduce administrative burdens. Citizens shouldn’t care anymore about application periods, neither they should type data that they already gave within previous forms. The Spanish law doesn’t allow for full proactive administrative procedures: citizens must state every time that they want the procedure and that data is right. So, the solution approach tries to minimize the citizen effort, provided that it is not possible to provide 100% proactive services. Just one pilot has been implemented: the proactive service for University scholarships. Few subscriptions have been reached so far, by lack of diffusion, that will be reviewed. | Regional | Spain | ES51 | Generalitat de Catalunya | Regional Government | General public services | General public services n.e.c. | Pilot | 2.022 | Public services and engagement | Service personalisation (various) | No | No | Artificial Intelligence | G2C | x | x | x | x | https://dt4regions.eu/dt-book/dt-stories/proactive-administrative-procedures | Learning | Machine learning | recommender system | 06/07/2023 | ||||||||||||||||||
| PSTW-108 | Taxana - Chatbot for financial administration | https://dataconcept.digital/case-study/taxana/ | The Slovakian Financial Administration is the first state institution to launch an automated Chatbot to communicate with its clients, available 24/7. This Chatbot was named Taxana, chosen by the employees of the financial administration combining the English word tax and the Slovak word toy. The system has been put in place as it is argued that the state financial management must continue to digitize and electronic processes to make the processes easier for taxpayers. The introduction of automated chat in communication with their clients will also assist the call center staff, who save time and can thus deal with more complex issues of taxpayers. | National | Slovakia | SK | Financial Administration | Central-Government | General public services | Executive and legislative organs, financial and fiscal affairs, external affairs. | Implemented | 2.018 | 2019 | Public services and engagement | Engagement management | No | No | Artificial Intelligence | G2C | x | x | x | x | https://www.youtube.com/watch?v=UQ_XRlIFtrQ & https://www.podnikajte.sk/dane/taxana-chatbot | Communication | Natural language processing | Machine learning | chatbot | 08/11/2023 | ||||||||||||||||
| PSTW-1082 | Trombia Free experiment in Helsinki | https://trombia.com/2021/11/29/case-study-helsinki-airport-trombia-free/ | The results of the Trombia Free autonomous street sweeper pilots showed that autonomous technology operates efficiently in semi-closed areas such as parking lots where both narrow indoor spaces and busy outdoor areas need continuous maintenance. Trombia Free handled all the cleaning tasks much more efficiently than standard suction sweeping technology. Our patented air knife technology made it possible to clean even the dustiest corners without throwing water on the surface. That is a key to continuous year-round maintenance when temperatures go below zero celsius. The cleaning vehicle is able at this stage to cover between 5000 and 15 000 m² of roads per hour. | Local | Finland | FI1B | City of Helsinki | Local Government | Environmental Protection | Waste management. | Pilot | 2.021 | Internal management | Internal primary processes | No | No | Artificial Intelligence | G2G | x | x | x | https://trombia.com/2021/11/29/case-study-helsinki-airport-trombia-free/ | Integration and Interaction | Robotics and Automation | 06/07/2023 | ||||||||||||||||||||
| PSTW-1083 | Swedish police used face recognition until 2019 at the Skavsta airport | https://automatingsociety.algorithmwatch.org/wp-content/uploads/2020/12/Automating-Society-Report-2020.pdf | As part of a broadly discussed special operation to fight organized crime (operation Rime Ice), the Swedish police implemented several face recognition pilot projects including searching through visual material such as pictures from crime scenes and CCTV footage to identify reoccurring people. The Swedish Police used the face recognition App “Clearview AI". However, in 2021, the Swedish Authority for Privacy Protection found that the Swedish Police Authority has processed personal data in breach of the Swedish Criminal Data Act when using Clearview AI to identify individuals, forcing the Police to make sure every personal information got erased from the AI system. | National | Sweden | SE | Swedish Police Authority | Central-Government | Public order and safety | Police Services | Pilot | 2.019 | Enforcement | Smart Recognition processes | No | No | Artificial Intelligence | G2G | x | x | x | https://automatingsociety.algorithmwatch.org/wp-content/uploads/2020/12/Automating-Society-Report-2020.pdf | Perception | Computer vision | face recognition | 06/07/2023 | |||||||||||||||||||
| PSTW-1088 | Use of smart video surveillance by the local police | https://automatingsociety.algorithmwatch.org/wp-content/uploads/2020/12/Automating-Society-Report-2020.pdf | Since 2019, the local police in the cities of Kortrijk, Kuurne, and Lendelde (VLAS) have been using a ‘smart’ video surveillance system developed by an American company called Briefcam. According to the police, the first objective is to aid investigations. For instance, if a person with a backpack and wearing a blue coat has fled in a certain direction, this person can be found easily by the algorithm. The person is then traced on other cameras to get a more complete picture of the route he or she took and to detect crimes that might have been committed. The system can also help search for lost children and solve bicycle theft more easily. Another goal functionality is the generation of live alerts. For instance, at the beginning and end of the school day, trucks are not permitted to drive near schools. If a truck is spotted driving through an area it is not allowed to, the system sends an alert to the police. Lastly, the system collects statistical information to support policy. Use of smart video surveillance by the local police (Briefcam) since 2019, e.g. a fleeing person can be tracked. The system stores all ‘objects’ that appear in the video images. An algorithm then decides what category each object belongs to. In exceptional circumstances, when requested by an investigatory judge, it is possible to use face recognition. | Local | Belgium | BE25 | Police department | Local Government | Public order and safety | Police Services | Implemented | 2.019 | Enforcement | Smart Recognition processes | No | No | Artificial Intelligence | G2G | x | x | x | https://automatingsociety.algorithmwatch.org/wp-content/uploads/2020/12/Automating-Society-Report-2020.pdf | Perception | Computer vision | object recognition | 06/07/2023 | |||||||||||||||||||
| PSTW-109 | OverSi - Chatbot to faster burocracy | https://stopbyrokracii.sk/wp-content/themes/social-activism/overSiBot.html | The Oversi Chatbot is part of a government initiative to stop the bureaucracy in Slovakia and to apply the once only principle in a digital way. The Chatbot has been invented in order to help find the best solutions and answers to common questions for the general public. | National | Slovakia | SK | The Office of the Deputy Prime Minister of the Slovak Republic for Investments and Informatization (ODPMII) | Central-Government | General public services | General services. | Implemented | 2.018 | Public services and engagement | Service personalisation (various) | No | No | Artificial Intelligence | G2C | x | x | x | x | https://stopbyrokracii.sk/wp-content/themes/social-activism/overSiBot.html | Communication | Natural language processing | Machine learning | chatbot | 08/11/2023 | |||||||||||||||||
| PSTW-1090 | Face recognition tool for the Slovenian police | https://algorithmwatch.org/en/slovenia-police-face-recognition/ | The slovenian police have been using face recognition AI tools since 2014 but only after 5 years it was actually legalized. The police had been using a piece of face-recognition software called Face Trace to find suspects using open source investigation methods (such as searching social media and other online sources). | National | Slovenia | SI | Slovenian Police | Central-Government | Public order and safety | Police Services | Implemented | 2.014 | Enforcement | Smart Recognition processes | No | No | Artificial Intelligence | G2G | x | x | x | https://www.reframetech.de/en/2020/09/02/algorail-in-slovenia-legalization-as-an-afterthought/ | Perception | Computer vision | facial recognition | 06/07/2023 | |||||||||||||||||||
| PSTW-1094 | SPIRIT - Scalable privacy preserving intelligence analysis for resolving identities | https://automatingsociety.algorithmwatch.org/wp-content/uploads/2020/12/Automating-Society-Report-2020.pdf | SPIRIT project (“Scalable privacy preserving intelligence analysis for resolving identities”). Aims to use tools such as face extraction and matching, to correlate information from social media data, and to continuously initiate complex associative searches across all sources relevant to criminal investigation. Trial runs will be organized, including in Greece. | National | Greece | EL | Hellenic Police | Central-Government | Public order and safety | Police Services | In development | 2.018 | Enforcement | Smart Recognition processes | No | No | Artificial Intelligence | G2G | x | x | https://automatingsociety.algorithmwatch.org/wp-content/uploads/2020/12/Automating-Society-Report-2020.pdf | Perception | Computer vision | facial recognition | 06/07/2023 | ||||||||||||||||||||
| PSTW-1096 | Automated surveillance through audio processing | https://automatingsociety.algorithmwatch.org/wp-content/uploads/2020/12/Automating-Society-Report-2020.pdf | In Saint-Étienne (pop. 175,000), the city planned to deploy microphones in order to automatically detect suspicious sounds. The project was to be implemented in a poor neighborhood, in coordination with CCTV cameras and an autonomous drone equipped with a camera. The plan was to register all “suspicious” sounds, including things like gunshots but also electric drills, sprays, and whistles. It is currently on hold because the French data protection authority considered it illegal. | Local | France | FRK2 | City of Saint-Étienne | Local Government | Public order and safety | Police Services | In development | 2.019 | Enforcement | Smart Recognition processes | No | No | Artificial Intelligence | G2G | x | x | https://automatingsociety.algorithmwatch.org/wp-content/uploads/2020/12/Automating-Society-Report-2020.pdf | Perception | Audio processing | 06/07/2023 | |||||||||||||||||||||
| PSTW-1097 | ALICEM - face recognition for administrative procedures | https://automatingsociety.algorithmwatch.org/wp-content/uploads/2020/12/Automating-Society-Report-2020.pdf | Government program (“Alicem”) that allows identification via face recognition for administrative procedures. Citizens register their face’s biometric characteristics using a smartphone app. They can then use the app to go through administrative procedures that currently require them to physically visit a government agency. After Bloomberg reported about the scheme in October 2019 (Fouquet, 2019), the public outcry led to the government delaying the launch of the app. Now, it is expected to launch in 2020, but no official launch date has been made public. | National | France | FR | Government of France | Central-Government | General public services | General public services n.e.c. | In development | 2.019 | Enforcement | Smart Recognition processes | No | No | Artificial Intelligence | G2G | x | x | https://automatingsociety.algorithmwatch.org/wp-content/uploads/2020/12/Automating-Society-Report-2020.pdf | Perception | Computer vision | facial recognition | 06/07/2023 | ||||||||||||||||||||
| PSTW-1099 | BOM - Biometrics on the Move | https://automatingsociety.algorithmwatch.org/wp-content/uploads/2020/12/Automating-Society-Report-2020.pdf | Frontex project that uses face recognition and fingerprints scan for seamlessly crossing the border, In October 2019, the Humberto Delgado International Airport in Lisbon tested a voluntary trial called BOM (“Biometrics on the Move”) which is a Frontex (the European Border and Coast Guard Agency) project together with the Portuguese Immigration and Border Service and the Lisbon Airport Authority (ANA). It uses face recognition and touchless scanning of fingerprints enabling passengers to cross the border “almost seamlessly”, “without even taking out their passport or other documents”, according to Frontex. | National | Portugal | PT | Portuguese Immigration and Border Service | Central-Government | Public order and safety | Police Services | Pilot | 2.019 | Enforcement | Smart Recognition processes | No | No | Artificial Intelligence | G2G | x | x | https://automatingsociety.algorithmwatch.org/wp-content/uploads/2020/12/Automating-Society-Report-2020.pdf | Perception | Computer vision | facial recognition | 06/07/2023 | ||||||||||||||||||||
| PSTW-110 | PCA - AI algorithms in audit methodology detecting potential fraud when prescribing medicines | https://dennikn.sk/blog/1561696/big-data-ukazali-nestandardne-predpisovanie-liekov-usporime-tak-statisice-eur/ | AI algorithms in audit methodology detecting potential fraud when prescribing medicines. | National | Slovakia | SK | Institute of health policy (IZP) | Central-Government | Health | Public health services. | Pilot | 2.018 | Enforcement | Management of auditing and logging | No | No | Artificial Intelligence | G2G | x | x | x | x | https://dennikn.sk/blog/1561696/big-data-ukazali-nestandardne-predpisovanie-liekov-usporime-tak-statisice-eur/ | Learning | Machine learning | Automated reasoning | 08/11/2023 | ||||||||||||||||||
| PSTW-1102 | Machine vision AI solution for better traffic management in Tallinn | https://automatingsociety.algorithmwatch.org/wp-content/uploads/2020/12/Automating-Society-Report-2020.pdf | The machine vision Kratt, or AI solution of the Public Transport and Traffic Management Department in Tallinn, started in autumn 2018 in cooperation with Sifr OÜ (Kasutuslood | Krattide veebileht o. J.). The main purpose of this solution is to monitor the traffic load In Tallinn, specifically the cars driving in and out of the city every day. This information is used to make decisions about parking problems or road construction, among other issues. To test the solution, three cameras were selected to monitor intersections in Tallinn. This helped train the software to count vehicles passing the camera. This solution uses a machine vision algorithm, which counts buses, cars, trucks, and motorcycles. In the future, it is hoped that the same solution can be used to count pedestrians. | Local | Estonia | EE00 | Public Transport and Traffic Management Department | Local Government | Public order and safety | Police Services | Implemented | 2.018 | Enforcement | Smart Recognition processes | No | No | Artificial Intelligence | G2G | x | x | https://automatingsociety.algorithmwatch.org/wp-content/uploads/2020/12/Automating-Society-Report-2020.pdf | Perception | Computer vision | object recognition | 07/07/2023 | ||||||||||||||||||||
| PSTW-1114 | System called ARNO for submitting and processing application in Estonia | https://tartu.ee/en/general-education-schools | The city of Tartu uses the ARNO system (www.arno.ee) for managing applications and placements in nursery schools and childcare. The ADM systems determine a child's municipal school based on their registered address. School placements are generated annually using three sets of data: the automatic queue for preschool-aged children, the parent's preferred kindergarten, and the nearest kindergarten. Parents can request a school change later if necessary. For kindergartens, parents need to apply for a spot after their child's birth. The ARNO system is developed by OÜ Piksel. | Local | Estonia | EE00 | City of Tartu | Local Government | Education | Education not definable by level. | Implemented | 2.022 | Adjudication | Taking decisions on benefits | No | No | Artificial Intelligence | G2C | x | x | x | x | x | https://automatingsociety.algorithmwatch.org/wp-content/uploads/2020/12/Automating-Society-Report-2020.pdf | Learning | Machine learning | 07/07/2023 | ||||||||||||||||||
| PSTW-1118 | CENTAUR - Greek camps for asylum seekers surveillance systems | https://algorithmwatch.org/en/greek-camps-surveillance/#:~:text=The%20Greek%20Ministry%20of%20Migration,official%20strategy%20document%20AlgorithmWatch%20consulted. | The Greek Ministry of Migration and Asylum has implemented the Greece Integrated Maritime Surveillance System (GIMSS) in refugee camps to enhance security and prevent illegal activities. GIMSS utilizes drones, thermal cameras, and motion sensors for real-time monitoring and data collection. The collected data is processed using advanced algorithms to generate actionable intelligence. However, concerns have been raised about the lack of transparency and public consultation during the system's deployment. Privacy and human rights issues arise, with potential violations of refugees' rights and their freedom of movement and privacy. | National | Greece | EL | Ministry of Migration and Asylum | Central-Government | Public order and safety | Police Services | In development | 2.020 | Enforcement | Supporting inspection processes | No | No | Artificial Intelligence | G2G | x | x | x | https://algorithmwatch.org/en/greek-camps-surveillance/#:~:text=The%20Greek%20Ministry%20of%20Migration,official%20strategy%20document%20AlgorithmWatch%20consulted. | Perception | Computer vision | 07/07/2023 | ||||||||||||||||||||
| PSTW-112 | Semantic analyser - Document analyser for the public administration | https://nio.gov.si/nio/asset/semanticni+analizator+besedil | In cooperation with the Faculty of Computer Science and Informatics of the University of Ljubljana, a set of tools for comparing unstructured texts according to the meaning and content of the texts (semantic comparison) was developed. The goal and idea of the project was to enable the search for similarities between texts beyond the mere statistical analysis of texts, i.e. texts that contain words in the same context with the same or similar meaning. | National | Slovenia | SI | Ministry of Public Administration | Central-Government | General public services | Executive and legislative organs, financial and fiscal affairs, external affairs. | In development | 2.020 | 2022 | Internal management | Internal support processes | No | No | Artificial Intelligence | G2G | x | x | x | x | https://nio.gov.si/nio/asset/semanticni+analizator+besedil | Communication | Natural language processing | Machine learning | text analysis | 08/11/2023 | ||||||||||||||||
| PSTW-1122 | Project RAPID - Automatic Identification of Passengers Holding Traveling Documents | https://automatingsociety.algorithmwatch.org/wp-content/uploads/2020/12/Automating-Society-Report-2020.pdf | The Portuguese Immigration and Border Service invested 4.2M euros + VAT in 2019 to update Project RAPID, an automated system for controlling passengers crossing Schengen's external borders. RAPID combines the operations of reading and verifying electronic passports with innovative biometric assessment features. The system checks the authenticity of electronic passports and validates the data stored in the chip. It also compares the passenger's photo stored in the chip with their physical appearance on-site, automatically opening the border gate when the images match. The newly purchased devices will be installed in the airports of Lisbon, Porto, Faro, and Madeira, enhancing border control capabilities. | National | Portugal | PT | Portuguese Immigration and Border Service | Central-Government | Public order and safety | Police Services | Implemented | 2.019 | Enforcement | Supporting inspection processes | No | No | Artificial Intelligence | G2G | x | x | https://automatingsociety.algorithmwatch.org/wp-content/uploads/2020/12/Automating-Society-Report-2020.pdf | Perception | Computer vision | face recognition | 07/07/2023 | ||||||||||||||||||||
| PSTW-1128 | EU Exit: ID document check - applying for settled status in the UK after Brexit | https://automatingsociety.algorithmwatch.org/wp-content/uploads/2020/12/Automating-Society-Report-2020.pdf | The government implemented the registration system in the form of a smartphone app “EU Exit: ID document check” app. Applicants are required to complete five steps: firstly, they take an image of the personal details page of either their passport or identity card. Then, they must scan this document, via a smartphone, by using the NFC feature. The smartphone then reads the contents of the electronic chip stored inside modern identity documents. The applicant must then take a video and a photo of their face. Finally, she or he must answer an online questionnaire. If the applicant submits their National Identification number, automated processing of tax and other benefits is carried out. This algorithm-based verification process is done against records held by the tax authority (HMRC) and the Department for Work and Pensions (DWP). This is not a mandatory step, but official documentation says that applicants who submit their NI number will not have to provide further evidence. | National | United Kingdom | UK | UK Home Office | Central-Government | Public order and safety | Police Services | Implemented | 2.019 | Adjudication | Taking decisions on benefits | No | No | Artificial Intelligence | G2C | x | x | x | x | https://automatingsociety.algorithmwatch.org/wp-content/uploads/2020/12/Automating-Society-Report-2020.pdf | Perception | Computer vision | 07/07/2023 | |||||||||||||||||||
| PSTW-1130 | Pro-Kid used for risk assessment by the Dutch police | https://www.fairtrials.org/app/uploads/2021/11/Automating_Injustice.pdf | The Dutch police have used an automated risk assessment tool called ProKid since 2011 to evaluate the risk of (re)offending among children and young people. The tool is an actuarial risk assessment system that assigns weights to specific information to estimate the risk of future violent and property offenses. However, it does not actually predict the likelihood of criminality but rather the likelihood of a child being registered on the police system in relation to a crime. ProKid utilizes police data from criminal fact and criminal opinion databases to formulate its risk assessments. Being assessed as 'at risk' by ProKid can have significant consequences for children and their families, potentially leading to separation and involvement with youth care and child abuse protection services. The assessments have been found to be incorrect and erroneous in a significant number of cases. A Ministry of Security and Justice evaluation revealed that one-third of the assessed children had their risk levels mis-assigned due to errors or reports based on irrelevant incidents. ProKid profiles serve as the initial step in a series of automated risk assessments that can have serious implications in the criminal justice system. Despite its name, ProKid has raised concerns and controversy. | National | Netherlands | NL | Dutch police | Central-Government | Public order and safety | Police Services | Implemented | 2.011 | Enforcement | Predictive enforcement processes | No | No | Artificial Intelligence | G2G | x | x | https://www.fairtrials.org/app/uploads/2021/11/Automating_Injustice.pdf | Learning | Machine learning | probabilistic model | 07/07/2023 | ||||||||||||||||||||
| PSTW-1131 | “Top 600” and “Top400” used for automated risk modelling | https://www.fairtrials.org/app/uploads/2021/11/Automating_Injustice.pdf | The Amsterdam Municipality, police, and social services use the "Top 600" and "Top 400" systems for automated risk modeling and profiling. The Top 600 focuses on identifying the 600 young people most at risk of committing "High Impact Crime" based on criteria such as past arrests for serious offenses, bankruptcy proceedings, and convictions. Being on the Top 600 list leads to consequences like increased penalties, active prosecution for minor offenses, and asset confiscation. Those listed face regular police surveillance, home checks, limited participation in activities, potential residence permit revocation, and employment difficulties. The Top 400 targets children under 16 to prevent involvement in crime and uses the ProKid risk assessment model with broader criteria, including non-criminal indicators and mere suspicion of involvement. These systems have significant impacts, including ongoing surveillance, restricted activities, and potential negative consequences for employment and residence permits. | Local | Netherlands | NL32 | City of Amsterdam | Local Government | Public order and safety | Police Services | Implemented | 2.012 | Enforcement | Predictive enforcement processes | No | No | Artificial Intelligence | G2G | x | x | https://www.fairtrials.org/app/uploads/2021/11/Automating_Injustice.pdf | Learning | Machine learning | 07/07/2023 | |||||||||||||||||||||
| PSTW-1132 | The Sensing Project for risk assessment and profiling by the Roermond police | https://www.fairtrials.org/app/uploads/2021/11/Automating_Injustice.pdf | In Roermond, the Netherlands, the police use an algorithmic system called the Sensing Project for risk assessment and profiling. The project aims to identify and "predict" likely perpetrators of pickpocketing and shoplifting in a local shopping center. The Roermond police developed the algorithm based on their own criteria, focusing on a concept they call "mobile banditry," committed by foreign groups from Eastern European countries. Dutch nationals are excluded from this definition. The Sensing Project algorithm evaluates individuals traveling in Roermond against specific criteria. These criteria include traveling by car with passengers, following certain routes, having specific license plates, or using rental cars associated with previous criminality. The algorithm calculates an overall risk score, and if it's high, the car, driver, and passengers are labeled as "suspicious," generating a "hit" in the system. Police officers have discretion in responding to these notifications. Even if individuals in the car are not considered suspected criminals, their car's details are recorded in the police system. Subsequently, when the car is driven in Roermond again, it receives a higher risk score due to its previous registration in the system, regardless of any evidence or police suspicion of criminality beyond the Sensing Project's risk assessment. | Local | Netherlands | NL42 | Roermond police | Local Government | Public order and safety | Police Services | Implemented | 2.018 | Enforcement | Predictive enforcement processes | No | No | Artificial Intelligence | G2G | x | x | x | https://www.fairtrials.org/app/uploads/2021/11/Automating_Injustice.pdf | Perception | Computer vision | 07/07/2023 | ||||||||||||||||||||
| PSTW-1133 | Cassandra – Automated risk assessment system used by the Ukraine Ministry of Justice | https://www.fairtrials.org/app/uploads/2021/11/Automating_Injustice.pdf | Cassandra is an automated system used for providing pre-trial and pre-sentence reports. It analyzes individual offenders to assess the risk of re-offending, influencing judges' decisions on custodial sentences. Probation officers input information into the system based on specific questions, and the system assigns a score to each piece of information. It then summarizes the scores to estimate the probability of the individual committing a new crime, ranging from 0 to 97. Limited information is available publicly about the software, the specifics of the AI system, or the data used in Cassandra. | National | Ukraine | UA | Ministry of Justice | Central-Government | General public services | Executive and legislative organs, financial and fiscal affairs, external affairs. | Pilot | 2.020 | Enforcement | Supporting inspection processes | No | No | Artificial Intelligence | G2G | x | x | x | https://www.fairtrials.org/app/uploads/2021/11/Automating_Injustice.pdf | Learning | Machine learning | 07/07/2023 | ||||||||||||||||||||
| PSTW-1137 | AI tool to predict recidivism in prisoners in Switzerland | https://automatingsociety.algorithmwatch.org/wp-content/uploads/2020/12/Automating-Society-Report-2020.pdf | The Swiss Execution of Penal Sentences and Justice follows a system of levels where inmates are granted increasing freedom based on their imprisonment duration. To prevent recidivism, the Risk-Oriented Sanctioning (ROS) system was introduced, dividing offender work into triage, assessment, planning, and progress stages. The triage stage uses an automated tool called the Fall-Screening-Tool (FaST) to classify cases into classes A, B, and C based on risk factors. Class C indicates a risk of violent or sexual delinquency, while class B signifies a general risk of further delinquency. Class A has no assessment needs. The FaST tool uses criminal records and statistical risk factors to determine classifications. However, it is not a risk analysis but a way to identify cases requiring further assessment. The triage classification guides decision-making and determines the offender's problem profile for sentence execution planning. ADM applications are not used in other stages of ROS, and FaST is only utilized during the triage stage. | National | Switzerland | CH | Swiss Execution of Penal Sentences and Justice | Central-Government | Public order and safety | Police Services | Implemented | 2.018 | Enforcement | Supporting inspection processes | No | No | Artificial Intelligence | G2G | x | x | https://automatingsociety.algorithmwatch.org/wp-content/uploads/2020/12/Automating-Society-Report-2020.pdf | Learning | Machine learning | 07/07/2023 | |||||||||||||||||||||
| PSTW-1140 | Gangs Violence Matrix (GVM) to predict crime in London | https://www.europarl.europa.eu/RegData/etudes/STUD/2020/656295/IPOL_STU(2020)656295_EN.pdf | This predictive policing tool is used since 2012 by the Metropolitan Police in order to identify and risk-assess gang members across London involved in gang violence, and to identify those at risk of victimisation. The GVM measures the harm that individuals pose by scoring them based on evidence of them committing violence and weapons offences, as well as police intelligence relating to them having access to weapons, or them being involved in, or at risk from, gang violence: individuals are thus graded as red, amber or green, denoting the level of risk (for victims) or harm (for offenders) they present. The database encompasses both adults and minors. Amnesty International criticised the Metropolitan Police for refusing to divulge information about the precise criteria used to assign automated 'harm scores' to individual on the matrix. | Regional | United Kingdom | UKI | Metropolitcan Police Service | Regional Government | Public order and safety | Police Services | Implemented | 2.012 | Enforcement | Predictive enforcement processes | No | No | Artificial Intelligence | G2G | x | x | https://www.europarl.europa.eu/RegData/etudes/STUD/2020/656295/IPOL_STU(2020)656295_EN.pdf | Learning | Machine learning | 07/07/2023 | |||||||||||||||||||||
| PSTW-1142 | STIR - an algorithm to fight VAT fraud in Poland | https://automatingsociety.algorithmwatch.org/wp-content/uploads/2020/12/Automating-Society-Report-2020.pdf | The STIR system in Poland aims to automatically identify and label suspicious transactions and fraudulent entrepreneurs to predict VAT fraud. It gathers financial information from banks and operates under the State Clearance Chamber. The system uses automated decision-making tools to provide risk indicators to tax authorities, allowing them to block suspicious accounts without informing the bank or account owner. The freezing of an account can last up to 72 hours initially, with the possibility of extension up to three months. The algorithm used by STIR remains undisclosed, but criteria such as unusual bank account activity and transfers to high-risk fraud countries are considered. The law prohibits the disclosure or unauthorized use of algorithms or risk indicators, with potential imprisonment of up to five years for those who violate this provision. | National | Poland | PL | National Revenue Administration | Central-Government | General public services | Executive and legislative organs, financial and fiscal affairs, external affairs. | Implemented | 2.017 | Enforcement | Supporting inspection processes | No | No | Artificial Intelligence | G2G | x | x | x | x | https://automatingsociety.algorithmwatch.org/wp-content/uploads/2020/12/Automating-Society-Report-2020.pdf | Learning | Machine learning | 07/07/2023 | |||||||||||||||||||
| PSTW-1143 | Gladsaxe Model - profiling families for early detection of vulnerable children | https://automatingsociety.algorithmwatch.org/wp-content/uploads/2020/12/Automating-Society-Report-2020.pdf | The Gladsaxe-model was a points-based profiling system designed to detect children in vulnerable families. It utilized risk indicators such as parental mental health, unemployment, missed medical and dental appointments, and divorce. Initially a pilot project, it faced heavy criticism and was put on hold. However, the municipality of Gladsaxe continued working on the algorithm by incorporating additional data. Permission to proceed was denied by data protection authorities, leading to the project's termination without explanation. In 2020, a new research project at the University of Århus aimed to develop an algorithmic tool for identifying vulnerable children, but faced criticism for following a similar approach as the Gladsaxe Model. | Local | Denmark | DK01 | Municipality of Gladsaxe | Local Government | Social protection | Social protection n.e.c. | In development | 2.020 | Enforcement | Supporting inspection processes | No | No | Artificial Intelligence | G2G | x | x | https://automatingsociety.algorithmwatch.org/wp-content/uploads/2020/12/Automating-Society-Report-2020.pdf | Learning | Machine learning | 07/07/2023 | |||||||||||||||||||||
| PSTW-1146 | Offender Assessment System (OASys) | https://www.lawsociety.org.uk/topics/research/algorithm-use-in-the-criminal-justice-system-report | The Offender Assessment System (OASys) is a national risk/need assessment tool with algorithmic components used across probation areas and prison establishments in England and Wales. Originally trialled as a paper-based system, OASys rapidly became a digital tool, and has gathered a range of digital components. OASys was designed by the Ministry of Justice, and is today managed in close connection to the Ministry of Justice Data Science Hub. Its stated aims are to assess how likely an offender is to reoffend, identify and classify offending-related needs, assess risk of serious harm, risks to the individual and other risks, assist with management of risk of serious harm, link the assessment to the sentence plan, indicate the need for further specialist assessments, and measure change during the offender’s sentence. OASys assessments are carried out at several points in the justice system: for a pre-sentence report; at the start of a sentence in prison or in the community; at regular review periods; at key decision points, such as when an offender is up for parole; and on termination of the sentence. | National | United Kingdom | UK | Ministry of Justice | Central-Government | Public order and safety | Police Services | Implemented | 2.013 | Enforcement | Supporting inspection processes | No | No | Artificial Intelligence | G2G | x | x | https://www.lawsociety.org.uk/topics/research/algorithm-use-in-the-criminal-justice-system-report | Learning | Machine learning | 07/07/2023 | |||||||||||||||||||||
| PSTW-1148 | National Data Analytics Solution (NDAS) | https://www.fairtrials.org/app/uploads/2021/11/Automating_Injustice.pdf | National Data Analytics Solution (NDAS) is used for risk assessment and profiling by West Midlands Police, UK Home Office & other police forces. NDAS uses machine-learning and predictive analytics to conduct “behavioural analysis” and “predictive modelling” in order to create and provide individual predictions and profiles about people and their likely future actions. These are intended to inform and influence pre-emptive policing interventions, using data from police intelligence reports on individuals and ‘events’, stop and search data, drug use data and custody information. Stop and search data use was criticised because of its discriminatory nature: for instance, in 2019/20, Black people were four and a half times more likely than white people to be stopped and searched in the West Midlands Police area of England. | National | United Kingdom | UK | UK Home Office & others | Central-Government | Public order and safety | Police Services | Implemented | 2.016 | Enforcement | Predictive enforcement processes | No | No | Artificial Intelligence | G2G | x | x | https://www.fairtrials.org/app/uploads/2021/11/Automating_Injustice.pdf | Learning | Machine learning | probabilistic model | 07/07/2023 | ||||||||||||||||||||
| PSTW-1154 | Profiling system for the unemployed | https://automatingsociety.algorithmwatch.org/wp-content/uploads/2020/12/Automating-Society-Report-2020.pdf | To claim unemployment benefits, a profile is created for newly unemployed individuals using a nationwide tool. This profile is automatically generated and includes data such as age, origin, unemployment history, previous jobs, education, and the cause of unemployment, including health indications. The purpose of this profile is to estimate the likelihood of long-term unemployment and provide decision support to officials handling the case. It is important to note that this profile is not used as an automated decision-making tool but rather as a tool to support decision-making processes. | Local | Denmark | DK01 | City of Copenhagen | Local Government | Social protection | Unemployment. | Implemented | 2.019 | Adjudication | Taking decisions on benefits | No | No | Artificial Intelligence | G2G | x | x | https://automatingsociety.algorithmwatch.org/wp-content/uploads/2020/12/Automating-Society-Report-2020.pdf | Learning | Machine learning | decision support | 07/07/2023 | ||||||||||||||||||||
| PSTW-1156 | AuroraAI for life-event management | https://automatingsociety.algorithmwatch.org/wp-content/uploads/2020/12/Automating-Society-Report-2020.pdf | AuroraAI is an initiative that aims to automatically identify and predict "life events" in people's lives, which are specific circumstances that require certain services. It is often described as a "nanny" or a "good guardian" that assists citizens in accessing public and private services by suggesting and offering the appropriate ones for their particular situation. The system brings together data from different sectors of the public sector to proactively develop services for citizens. Some use case examples include a student relocating to a new city, retirement, job loss, or changes in family relationships. The goal is to provide personalized support and guidance based on individuals' unique circumstances. | National | Finland | FI | Ministry of Finance | Central-Government | Recreation, culture and religion | Recreational and sporting services. | Implemented | 2.019 | Analysis, monitoring and regulatory research | Information analysis processes | No | No | Artificial Intelligence | G2C | x | x | x | x | https://automatingsociety.algorithmwatch.org/wp-content/uploads/2020/12/Automating-Society-Report-2020.pdf | Learning | Machine learning | 07/07/2023 | |||||||||||||||||||
| PSTW-1160 | Automated benefit processes at the Social Insurance Institution of Finland | https://www.kela.fi/automated-decisions | Kela utilizes automation for routine tasks that don't require individual consideration. Automated decisions are made without human involvement but only in cases where the issues are indisputable and can be resolved by applying relevant legislation and known facts. Machine learning or statistical modeling is not used for automated decision-making. Automation improves customer service delivery by speeding up processes, allowing Kela to allocate freed-up resources for customer advice and support. Automated decisions clearly indicate their automatic nature, provide information sources, and include instructions for appeals. Kela makes automated decisions in various contexts, such as benefit rate adjustments, student financial aid awards, cancellations, and reviews based on updated information. They also automate decisions related to government guarantees for student loans and certain benefit cancellations for non-compliance or lack of response. Proposed decisions on student financial aid benefits may also be automated, becoming final if not reviewed by the recipient. | National | Finland | FI | Social Insurance Institution | Central-Government | Social protection | Social protection n.e.c. | Implemented | 2.018 | Adjudication | Taking decisions on benefits | No | No | Artificial Intelligence | G2G | x | x | x | https://automatingsociety.algorithmwatch.org/wp-content/uploads/2020/12/Automating-Society-Report-2020.pdf | Learning | Machine learning | 07/07/2023 | ||||||||||||||||||||
| PSTW-1163 | Performance and health monitoring for hydropower plants (PHM Hydro) | https://aidirectory.no/view-project.php?id=1402 | Continuous monitoring of the condition of critical equipment such as turbines and generators, as well as the efficiency of the equipment, ensures that hydropower plants operate profitably and without unwanted downtime. PHMHydro aims to build the foundation for such a performance and condition monitoring architecture for hydropower plants that is scalable to multiple technical components and to multiple power plants. This includes evaluation of new methodology, development of new algorithms using physics and artificial intelligence (AI), and an architecture to handle the algorithms in cloud/fog deployment. | National | Norway | NO | Royal Norwegian Ministry of Trade, Industry and Fisheries | Central-Government | Economic Affairs | Fuel and energy | Pilot | 2.022 | 2025 | Internal management | Internal primary processes | No | No | Artificial Intelligence | G2G | x | x | https://data.norge.no/kunstig-intelligens | Integration and Interaction | 07/07/2023 | |||||||||||||||||||||
| PSTW-1166 | Robotized baggage handling (Roba) in airports project | https://avinor.no/en/corporate/airport/oslo/development/abh/related-projects/robotized-baggage-handling/ | In the RoBa project, research will be done on new and robust methods for robotic packing of luggage in trolleys and adjacent automated transport systems and intermediate storage of trolleys. The results are to be implemented in a pilot facility at Gardermoen and become an important basis for further development both here and at other airports. | National | Norway | NO | Ministry of Transport | Central-Government | Economic Affairs | Transport | Pilot | 2.020 | Internal management | Internal primary processes | No | No | Artificial Intelligence | G2G | x | x | https://data.norge.no/kunstig-intelligens | Integration and Interaction | Robotics and Automation | 30/08/2023 | |||||||||||||||||||||
| PSTW-1169 | IARI - AI-based image recognition for railway infrastructure inspection | https://nr.no/prosjekter/kunstig-intelligens-skal-inspisere-jernbanen/ | Inspection is essential to ensure a safe and efficient railway. However, manual inspection is time- and cost-consuming, and will often result in the closure of railway routes to ensure the safety of the personnel carrying out the inspection. Expanding or replacing certain tasks with automated methods has great potential for savings and improving knowledge of the condition of the railway. NR develops algorithms that recognize faults in the infrastructure by using images from cameras on, among other things, trains and drones. We also use data from IR and depth cameras, which can provide more information than is found in normal images. The algorithms, deep learning in combination with classical static methods, are trained to recognize typical defects in images using a dataset of images of known defects. In collaboration with Bane NOR, we work to identify critical inspection tasks that are suitable for image recognition and establish data sets to train the algorithms with. | National | Norway | NO | Ministry of Transport and Communication | Central-Government | Economic Affairs | Transport | Pilot | 2.020 | 2021 | Enforcement | Supporting inspection processes | No | No | Artificial Intelligence | G2G | x | x | https://data.norge.no/kunstig-intelligens | Perception | Computer vision | Machine learning | Deep learning | 11/07/2023 | ||||||||||||||||||
| PSTW-117 | Chatbot - Boost relations with citizens | https://www.aoc.cat/es/blog/2018/la-finestreta-mes-rapida-de-sant-just-desvern-es-un-xatbot/ | The City Council of Sant Just Desvern, a Catalan municipality in the Baix Llobregat region with 17,200 inhabitants, has presented a chatbot with which this administration aims to streamline its processes and boost relations with its citizens. The first two available chatbots take care of the previous appointments of the City Council, so that waits will be reduced and the management of the registration flyers. | Local | Spain | ES | Municipality of Sant Just Desvern | Local Government | General public services | Executive and legislative organs, financial and fiscal affairs, external affairs. | Implemented | 2.018 | Public services and engagement | Engagement management | No | No | Artificial Intelligence | G2C | x | x | x | x | https://www.observatorio-empresas.vodafone.es/articulos/administraciones-publicas/chatbot-atencion-ciudadano-sant-just-desvern-perpinya/ | Communication | Natural language processing | Machine learning | chatbot | 08/11/2023 | |||||||||||||||||
| PSTW-1174 | AI decision support in medical emergency calls | https://prosjektbanken-forskningsradet-no.translate.goog/project/FORISS/331965?_x_tr_sl=auto&_x_tr_tl=en&_x_tr_hl=it&_x_tr_pto=wapp&_x_tr_hist=true | The project has three parts: First, a detailed mapping of what contact stroke patients in Helse Bergen was made with the healthcare system before they reach the hospital and end up in the Stroke Register. Then they use these patients' 113 calls and structured hospital data (Norwegian Patient Register) to develop and test (on historical data) an AI model. Finally, the model will be put into use live in AMK Bergen to investigate whether the accuracy for stroke is better with the use of AI, compared to the current system. | Regional | Norway | NO05 | Haukeland University Hospital (Helse Bergen) | Regional Government | Health | R&D health. | Pilot | 2.022 | 2025 | Internal management | Internal primary processes | No | No | Artificial Intelligence | G2G | x | x | https://data.norge.no/kunstig-intelligens | Learning | Machine learning | 30/08/2023 | ||||||||||||||||||||
| PSTW-1175 | AI for improved diagnostics in endometrial cancer | https://ehealthresearch.no/kin/prosjekter/kunstig-intelligens-for-forbedret-diagnostikk-i-endometriekreft | Gynecologic cancers have characteristic structural and functional imaging features reflected in clinical phenotypes, and these imaging biomarkers highlight pathogenic mechanisms potentially targetable by novel treatments. The challenge is now to integrate these imaging biomarkers into clinically relevant treatment algorithms by identifying molecular targets for treatment based on imaging biomarker profiles. | Regional | Norway | NO05 | Haukeland University Hospital (Helse Bergen) | Regional Government | Health | R&D health. | Pilot | 2.008 | 2028 | Public services and engagement | Service personalisation (various) | No | No | Artificial Intelligence | G2C | x | x | x | x | x | https://data.norge.no/kunstig-intelligens | Perception | Natural language processing | Automated reasoning | 30/08/2023 | ||||||||||||||||
| PSTW-1178 | CoSeM - Computational sepsis mining and modelling | https://www.ntnu.edu/cosem#/view/publications | The objective of this research project is to capture and preserve individual case histories using novel technology for integrating temporal interpretation of clinical text with structured data; to establish knowledge and decision support for individualized, real-time, infection and sepsis monitoring and to demonstrate a clinical dashboard extending the computerized chart for process monitoring and patient risk mitigation. Indirectly, it also improves interventions and reduce drug resistance. | Regional | Norway | NO | Central Norway Regional Health Authority | Regional Government | Health | R&D health. | Pilot | 2.020 | 2025 | Public services and engagement | Service personalisation (various) | No | No | Artificial Intelligence | G2C | x | x | x | x | x | https://ehealthresearch-no.translate.goog/kin/prosjekter/cosem?_x_tr_sl=auto&_x_tr_tl=en&_x_tr_hl=it&_x_tr_pto=wapp | Perception | Computer vision | sensor system | 11/07/2023 | ||||||||||||||||
| PSTW-1179 | Fraxinus - An open source, software only, navigation system for bronchoscopy | https://ehealthresearch.no/kin/prosjekter/fraxinus-an-open-source-software-only-navigation-system-for-bronchoscopy | Bronchoscopy is the endobronchial procedure for inspection and diagnostic sampling in the airways, e.g. to diagnose lung cancer. Navigating the flexible bronchoscope through the airways to the target for the diagnostic sampling, like biopsy or fine needle aspiration, is challenging due to the numerous divisions of the airways tree structure and the lack of direct visibility of smaller peripheral lesions. Even with fluoroscopy guidance, the diagnostic success rate for bronchoscopically non-visible tumors is as low as 15% compared to 80% for visible tumors, dependent on tumor size, the doctors experience and the method used for sampling. Using navigated bronchoscopy is a possibility to reduce these challenges and thus increase the biopsy success rate. | Regional | Norway | NO | Central Norway Regional Health Authority | Regional Government | Health | R&D health. | Pilot | 2.021 | 2025 | Public services and engagement | Service personalisation (various) | No | No | Artificial Intelligence | G2C | x | x | x | x | x | https://www.custusx.org/index.php/applications/fraxinus | Perception | Computer vision | 11/07/2023 | |||||||||||||||||
| PSTW-118 | VioGen - Forecast gender violence | https://algorithmwatch.org/en/viogen-algorithm-gender-violence/ | The Spanish polices uses VioGen, an algorithm that assesses the risk faced by victims of gender violence. Based on two tests to assess the risk of complainants or victims already sentenced, VioGén determines a level of risk of aggression that entails a specific degree of police protection , both before and after the trial or even when it does not occur. The figures support its success: since the implementation of this tool a decade ago, the recurrence of attacks has decreased by 25% according to the latest data. And if, in a generic way, recidivism in other neighboring countries reaches 35%, in Spain it is already at 15%. | National | Spain | ES | Spanish Police | Central-Government | Public order and safety | Police Services | Pilot | 2.021 | Enforcement | Predictive enforcement processes | No | No | Artificial Intelligence | G2G | x | x | x | https://algorithmwatch.org/en/viogen-algorithm-gender-violence/ | Learning | Machine learning | Planning and Scheduling | 08/11/2023 | |||||||||||||||||||
| PSTW-1180 | IDDEAS - Individual Digital Decision Assist System for Child and Adolescent Mental Health | https://www.ntnu.edu/rkbu/iddeas#/view/about | IDDEAS stands for "Individualized Digital Decision Assist System", which can be translated into individualized digital decision support system in Norwegian. IDDEAS is a KBSS under development, which initially targets children and young people with attention deficit hyperactivity disorder (ADHD). ADHD accounts for 29% of mental disorders among young people in Norway, and the disorder can persist into adulthood. Without the right treatment, ADHD can cause dramatic social and medical challenges that affect both the individual, the family and society. The IDDEAS project will provide evidence-based support to Norwegian healthcare personnel. The purpose is to improve the available specialist health services for children and young people. IDDEAS focuses on prevention, early diagnosis and early intervention, as well as treatment and follow-up of patients with ADHD. The system will adapt available data to the patient's needs and provide the patient with an optimized and evidence-based survey and follow-up. IDDEAS is therefore designed to improve clinical outcomes. | Regional | Norway | NO | Central Norway Regional Health Authority | Regional Government | Health | R&D health. | Pilot | 2.018 | 2023 | Public services and engagement | Service personalisation (various) | No | No | Artificial Intelligence | G2C | x | x | x | x | x | https://data.norge.no/kunstig-intelligens | Learning | Machine learning | Natural language processing | decision support | 11/07/2023 | |||||||||||||||
| PSTW-1181 | Segmenting and characterizing lymph nodes from thoracic CT scans using machine learning | https://ehealthresearch-no.translate.goog/kin/prosjekter/segementing-lymph-nodes-from-thorax-ct?_x_tr_sl=auto&_x_tr_tl=en&_x_tr_hl=it&_x_tr_pto=wapp | Accurate lung cancer diagnosis is crucial to select the best course of action for treating the patient. From a thorax CT volume, it is necessary to identify whether the cancer has spread to nearby lymph nodes or not. It is equally important to know precisely where each malignant lymph node is with respect to the surrounding anatomical structures and the airways. In this project, we introduce a new data-set containing annotations of fifteen different anatomical structures in the mediastinal area, including lymph nodes of varying sizes. We have developed a 2D pipeline for semantic segmentation and instance detection of anatomical structures and potentially malignant lymph nodes in the mediastinal area. | Regional | Norway | NO | Central Norway Regional Health Authority | Regional Government | Health | R&D health. | Pilot | 2.018 | 2028 | Public services and engagement | Service personalisation (various) | No | No | Artificial Intelligence | G2C | x | x | x | x | x | https://data.norge.no/kunstig-intelligens | Learning | Machine learning | 11/07/2023 | |||||||||||||||||
| PSTW-1182 | AI for cancer treatment | https://www-nrk-no.translate.goog/mr/alesund-sjukehus-og-st.-olavs-hospital-bruker-kunstig-intelligens-i-stralebehandling-mot-brystkreft-1.15882436?_x_tr_sl=auto&_x_tr_tl=en&_x_tr_hl=it&_x_tr_pto=wapp | Oncologists can sit in front of the PC for hours and draw hearts, lungs and other organs on a CT image, manually. In the program on the PC, one can scroll through hundreds of CT images, all mapped carefully and by hand. The time that is saved means that the oncologists can spend more time getting to know each patient's case even better, treating more people, and developing new treatment. | Regional | Norway | NO | Central Norway Regional Health Authority | Regional Government | Health | R&D health. | Pilot | 2.021 | 2030 | Public services and engagement | Service personalisation (various) | No | No | Artificial Intelligence | G2C | x | x | x | x | x | https://data.norge.no/kunstig-intelligens | Perception | Computer vision | 11/07/2023 | |||||||||||||||||
| PSTW-1183 | AI in image-guided neurosurgery | https://ehealthresearch.no/kin/prosjekter/ki-i-bildeveiledet-nevrokirurgi | The main goal is to gain new knowledge about the relationship between clinical and radiological findings, disease progression and treatment response in brain tumour patients. This can lead to more personalised treatment. We use machine learning to train models for automatic image analysis and prediction of survival and treatment response based on data from the individual patient in combination with data from hundreds of previous patients. The project is mainly based on data from the Central Norwegian Brain Tumour Registry and Biobank, which was established in 2015 by clinicians and researchers at St. Olavs Hospital and NTNU. Based on data from this registry, together with data from national and international partners, researchers at SINTEF are developing models for automatic image analysis and prediction of prognostic factors and disease progression based on artificial intelligence and machine learning. | Regional | Norway | NO | Central Norway Regional Health Authority | Regional Government | Health | R&D health. | Pilot | 2.011 | 2025 | Public services and engagement | Service personalisation (various) | No | No | Artificial Intelligence | G2C | x | x | x | x | x | https://data.norge.no/kunstig-intelligens | Learning | Machine learning | 11/07/2023 | |||||||||||||||||
| PSTW-1184 | Personalized decision support for patients with chronic pain | https://ehealthresearch.no/prosjekter/persontilpasset-beslutningsstotte-for-pasienter-med-kroniske-smerter | Patients with chronic pain constitute a large and heterogeneous patient group. There is currently no clear best alternative for the treatment of chronic pain, and it is therefore important that new tools and methods are developed that can more easily identify effective treatment alternatives for the individual patient. Existing tools for decision support are currently generic and without options for personal customization. Through this project, the objective is to provide doctors and patients with relevant, valid and personalized decision options with evidence-based probabilities for outcomes and side effects. The project has two main goals: (1) Process data from the health service and the patient (pain intensity, etc.), while respecting privacy and (2) Develop a solution that gives doctor and patient relevant, valid and personalized decision alternatives with evidence-based probabilities for outcomes and side effects. To achieve the first objective, we will use a mobile application to collect patient-reported data. In order to safeguard patients' privacy, this data is stored in accordance with the principle of "secret sharing". To achieve the second goal, personalized medical decision trees are constructed in real time. These are based on electronic patient record data from several health institutions. When processing patient data, secure privacy-preserving distributed computing techniques are used. Journal data from each health institution contributes to the final result without individual data being shared outside the health institutions. | Regional | Norway | NO07 | Northern Norway Regional Health Authority | Regional Government | Health | R&D health. | Pilot | 2.019 | 2022 | Public services and engagement | Service personalisation (various) | No | No | Artificial Intelligence | G2C | x | x | x | https://data.norge.no/kunstig-intelligens | Learning | Machine learning | Automated reasoning | decision support | 30/08/2023 | |||||||||||||||||
| PSTW-1185 | ClinCode: Computerised clinical ICD-10 coding | https://ehealthresearch.no/kin/prosjekter/clincode | ICD-10 diagnosis codes are crucial in Norwegian, Swedish, and global hospitals. They describe the examinations and treatments patients receive, recorded after each contact with a healthcare professional. However, the coding system, with its 30,000 codes, can be challenging and time-consuming to use. Consequently, incorrect or incomplete codes are often recorded by clinicians, leading to difficulties in billing accurately and planning resource utilization efficiently. The ClinCode project aims to explore how computer-assisted coding support (CAC) can improve the quality of ICD-10 coding without burdening clinicians further. The project leverages the extensive manually coded patient histories already present in electronic patient records to achieve this goal. The computer program will analyze both free text notes and structured data that has already been coded manually using natural language processing (NLP) and deep learning (Deep Learning) or what is also called artificial intelligence methods (AI) and learn from this data. | Regional | Norway | NO | Northern Norway Regional Health Authority | Regional Government | Health | R&D health. | Pilot | 2.021 | 2023 | Internal management | Internal primary processes | No | No | Artificial Intelligence | G2G | x | x | https://ehealthresearch-no.translate.goog/kin/prosjekter/chronic-pain?_x_tr_sl=auto&_x_tr_tl=en&_x_tr_hl=it&_x_tr_pto=wapp | Learning | Machine learning | Natural language processing | Deep learning | 11/07/2023 | ||||||||||||||||||
| PSTW-1186 | IM-PACT - Identification of multimorbid patients with modifiable risk profiles using artificial intelligence | https://ehealthresearch.no/kin/prosjekter/im-pact | This project is based on large data sets from hospitals and municipal care in Northern Norway. The care model, PAtient Centered-Team (PACT), combines elements of person-centred care, integrated care and proactive care. The PACT team incorporates insights and feedback from both patients and carers in the care process, and emphasises the patients' role in the decision-making process. The project was designed to provide appropriate, patient-centred, integrated and timely healthcare services to patients with multiple illnesses. The project is funded by NSE. | Regional | Norway | NO | Northern Norway Regional Health Authority | Regional Government | Health | R&D health. | Pilot | 2.021 | 2023 | Public services and engagement | Service personalisation (various) | No | No | Artificial Intelligence | G2C | x | x | x | x | x | https://ehealthresearch.no/kin/prosjekter/im-pact | Learning | Machine learning | 11/07/2023 | |||||||||||||||||
| PSTW-1188 | Predicting the risk of postoperative wound infections using artificial intelligence | https://data.norge.no/kunstig-intelligens | In the project, we will evaluate the validity of four non-AI-based risk tools to see which best predict the risk of postoperative wound infection. The variables, such as previous illnesses and age, in the risk tool with the best predictive power, will be used to develop algorithms for an AI-based risk tool, which we assume will predict the risk of postoperative wound infection better than the non-AI-based risk tools. The main goal is to develop an AI-based tool that can indicate the probability of a postoperative wound infection occurring in the individual patient, so that risk-reducing measures can be taken and the burden of disease for the patient is reduced. | Regional | Norway | NO | Northern Norway Regional Health Authority | Regional Government | Health | R&D health. | Pilot | 2.022 | 2027 | Public services and engagement | Service personalisation (various) | No | No | Artificial Intelligence | G2C | x | x | x | x | x | https://data.norge.no/kunstig-intelligens | Learning | 11/07/2023 | ||||||||||||||||||
| PSTW-1189 | Predicting the risk of postoperative wound infections with AI | https://ehealthresearch.no/kin/prosjekter/predikering-av-risiko-for-postoperative-sarinfeksjoner-med-bruk-av-kunstig-intelligens | The main goal is to develop an AI-based tool that can indicate the probability of a postoperative wound infection occurring in the individual patient, so that risk-reducing measures can be taken and the burden of disease for the patient is reduced. The project's team will evaluate the validity of four non-AI-based risk tools to see which best predict the risk of postoperative wound infection. The variables, such as previous illnesses and age, will be used to develop algorithms for an AI-based risk tool, which we assume will predict the risk of postoperative wound infection better than the non-AI-based risk tools. | Regional | Norway | NO07 | Northern Norway Regional Health Authority | Regional Government | Health | R&D health. | Pilot | 2.022 | 2027 | Public services and engagement | Service personalisation (various) | No | No | Artificial Intelligence | G2C | x | x | x | https://data.norge.no/kunstig-intelligens | Learning | Machine learning | probabilistic model | 30/08/2023 | ||||||||||||||||||
| PSTW-1190 | Prediction of relapse in glioblastoma | https://data.norge.no/kunstig-intelligens | Glioblastoma is the most common type of brain tumor. Survival in patients with this disease is approximately 15 months. Surgery is the most common form of treatment for glioblastoma. After surgery, it is very common for new tumor formation to occur in areas close to the original tumor that is not removed by surgery. The purpose of this project is to analyze these peripheral areas in post-operative magnetic resonance (MR) and positron emission tomography (PET) images using artificial intelligence and try to predict which areas are most likely to develop new tumor tissue formation. In the future, this will be able to provide the surgeon with useful information about which areas should be removed during surgery and when choosing further treatment for the patient. | Regional | Norway | NO | Northern Norway Regional Health Authority | Regional Government | Health | R&D health. | Pilot | 2.021 | 2023 | Public services and engagement | Service personalisation (various) | No | No | Artificial Intelligence | G2C | x | x | x | x | x | https://data.norge.no/kunstig-intelligens | Learning | 11/07/2023 | ||||||||||||||||||
| PSTW-1193 | Phenotyping for requisitioning genetic analyzes for hereditary conditions - structuring of phenotype data from text | https://ehealthresearch.no/kin/prosjekter/strukturering-av-fenotypedata | AMG is developing a solution to simplify and improve the requisition process for genetic analyses. The project is built around a solution with artificial intelligence to interpret text and turn it into Human Phenotype Ontology (structured phenotype data) which enables faster and more precise requisitioning of genetic analyses. Support for filling in HPO terms will increase the probability of filling in the form, thus facilitating diagnostics by saving time and increasing the probability of the right test and thus the right diagnosis. The project develops a proposal for a national cloud-based solution. | Regional | Norway | NO08 | South-Eastern Norway Regional Health Authority | Regional Government | Health | R&D health. | Pilot | 2.021 | 2025 | Public services and engagement | Service personalisation (various) | No | No | Artificial Intelligence | G2C | x | x | x | https://data.norge.no/kunstig-intelligens | Learning | Machine learning | 30/08/2023 | |||||||||||||||||||
| PSTW-1195 | Pathology services in the Western Norway Health Region – a center for applied digitization: Automatic classification of skin lesions | https://data.norge.no/kunstig-intelligens | Melanoma of the skin is the cancer type with the largest increase in incidence during the last decade. Currently, after excision of a suspicious skin lesion, the tissue is fixed in buffered formalin and a histological section is examined under a microscope by a trained expert pathologist. The pathologists use their deep domain knowledge to identify several possible complex morphological and cytological features. Unfortunately, this manual diagnosis of skin cancer is a time- and labour intensive task and not always that easy and reproducible. In addition, the sheer amount of skin biopsies causes logistic and personnel issues. The main challenge is to find the few malignant melanomas among all the other benign or less malign skin cancers. This project aims to develop a Computer-aided Diagnostic (CAD) system for whole slide images that will help pathology departments to diagnose malignant melanoma more efficiently, by (1) reducing examination time, (2) reducing diagnostic variations and (3) increase diagnostic accuracy. | Regional | Norway | NO | Western Norway Regional Health Authority | Regional Government | Health | R&D health. | Pilot | 2.021 | 2024 | Public services and engagement | Service personalisation (various) | No | No | Artificial Intelligence | G2C | x | x | x | x | x | https://ehealthresearch.no/kin/prosjekter/automatic-classification-of-skin-lesions | Perception | Computer vision | 11/07/2023 | |||||||||||||||||
| PSTW-1197 | Pathology services in the Western Norway Health Region – a center for applied digitization: Measuring proliferation in breast cancer | https://data.norge.no/kunstig-intelligens | Breast cancer is the most frequent female malignancy in the western world. To improve therapeutic decision-making, guidelines often combine conventional predictors to estimate relapse ⁄ mortality risk, but inaccuracy will cause over- and undertreatment. Proliferation factors are stronger prognostic indicators than Adjuvant! or NBCG Guidelines. Ki67 is also prognostic, and has been included in the Norwegian and Sankt Gallen therapy guidelines, but lacks independent laboratory test validation. As there is no formal standard operating procedure for Ki67 assessment based on scientific observations existent so far, the Norwegian guidelines nowadays also includes the classical mitosis counting, a time-consuming manual method. Both Ki67/PHH3 and mitosis counting can be automated and improved by means of digital image analysis. This project aims to train, test, validate and implement a machine learning system for calculating the Mitotic Activity Index (MAI), Ki-67 and PHH3 index in breast cancer | Regional | Norway | NO | Western Norway Regional Health Authority | Regional Government | Health | R&D health. | Pilot | 2.020 | 2024 | Public services and engagement | Service personalisation (various) | No | No | Artificial Intelligence | G2C | x | x | x | x | x | https://data.norge.no/kunstig-intelligens | Learning | Machine learning | 11/07/2023 | |||||||||||||||||
| PSTW-1198 | kvalitativ analyse av EIN | https://ehealthresearch.no/en/kin/prosjekter/quantitative-analysis-of-ein | Endometrioid intraepithelial neoplasia (EIN) is a pre-malignant lesion of the uterine lining that predisposes to endometrioid endometrial adenocarcinoma (EEC). Correct diagnosis and management of EIN is becoming increasingly relevant with the rise in obesity, a well-established risk factor of EEC, in the population. Morphometric analysis called D-score, aims to provide a quantitative assessment of progression risk of premalignant endometrial lesions. Although it has been shown to be a reproducible measurement, adaption of the D-score is slow in laboratories, because it’s costly and timely. Despite the inclusion of EIN in WHO14 many pathologists still hold on to the original WHO94 definition both in diagnostics and research. This project aims to train, test, validate and implement an application for automated, fast and reproducible method for EIN-scoring. | Regional | Norway | NO | Western Norway Regional Health Authority | Regional Government | Health | R&D health. | Pilot | 2.020 | 2024 | Public services and engagement | Service personalisation (various) | No | No | Artificial Intelligence | G2C | x | x | x | x | x | https://data.norge.no/kunstig-intelligens | Learning | Machine learning | 11/07/2023 | |||||||||||||||||
| PSTW-12 | Jobnet - Reskilling, upskilling and retraining of people | https://www.agoria.be/nl/diensten/expertise/digitalisering/digitalisering-van-bedrijven/vdab-gebruikt-ai-om-jobmatching-te-verrijken | The Flemish Employment and Vocational Training Service (VDAB) is using AI since 2018 which assists in the reskilling, upskilling and retraining of people. The software is called Jobnet and is the combination of a variety of different AI-models into one big AI-model. With the AI, citizens can see which jobs are fitting to their skills, which relevant skills they still lack, starting from their own experience combined with job market data. | Regional | Belgium | BE | Vlaamse Dienst voor Arbeidsbemiddeling en Beroepsopleiding | Local Government | Social protection | Unemployment. | Implemented | 2.018 | Public services and engagement | Service personalisation (various) | No | No | Artificial Intelligence | G2C | x | x | x | https://www.agoria.be/nl/VDAB-gebruikt-AI-om-jobmatching-te-verrijken | Learning | Machine learning | Searching | 06/10/2023 | |||||||||||||||||||
| PSTW-1200 | Pathology services in the Western Norway Health Region – a center for applied digitization: Optimization of the pathology workflow | https://ehealthresearch.no/kin/prosjekter/optimization-of-the-pathology-workflow | Pathology departments face a situation with constantly increasing number of samples and complexity of analyses while personal resources are not increasing in line with the escalating workload. We need to optimize our work processes in order to handle this situation. Unilab-700 provides atomic data describing the workflow. There are currently no systems available which are able to use these data in order to optimize the pathology workflow. The objective of the project is to develop and implement an optimisation model for pathology workflow, namely a system which delivers both long-term and ad hoc plans for optimised workflows in all pathology departments of the Western Norwegian Health Region. | Regional | Norway | NO0A | Western Norway Regional Health Authority | Regional Government | Health | R&D health. | Pilot | 2.021 | 2024 | Internal management | Internal primary processes | No | No | Artificial Intelligence | G2G | x | x | https://data.norge.no/kunstig-intelligens | Planning | Optimisation | 30/08/2023 | ||||||||||||||||||||
| PSTW-1201 | Ki-67 in neuroendocrine tumours of the gastrointestinal tract | https://ehealthresearch.no/en/kin/prosjekter/ki-67-in-gi-net | Ki-67 is both a prognostic and predictive biomarker in various tumours. To assess the Ki-67 index in neuroendocrine tumours (NET) of the gastrointestinal tract, it is recommended to count 2000 cells. For practical reasons, it is common to count fewer cells or make visual estimates without counting at all, resulting in less accurate and less precise Ki-67 indices. This project aims to train, test, validate and implement a machine learning system for calculating the Ki-67 index in neuroendocrine tumors of the gastrointestinal tract. | Regional | Norway | NO | Western Norway Regional Health Authority | Regional Government | Health | R&D health. | Pilot | 2.019 | 2022 | Public services and engagement | Service personalisation (various) | No | No | Artificial Intelligence | G2C | x | x | x | x | x | https://data.norge.no/kunstig-intelligens | Perception | Computer vision | 11/07/2023 | |||||||||||||||||
| PSTW-1205 | MIM - Machine learning in the Mammography programme | https://ehealthresearch.no/kin/prosjekter/mim | The idea behind the MIM project is to develop an algorithm that uses artificial intelligence (deep learning) to learn to recognize complex patterns and make independent decisions. By combining mammograms, associated screening information and any breast cancer diagnoses, the algorithm will learn to recognize patterns in the mammograms that may indicate breast cancer or breast disease, and mammograms without signs of disease. In this way, the method can be used to develop automatic systems that can pick out screening mammograms that are highly likely to show no signs of breast cancer. | National | Norway | NO | Cancer Registry Norway | Regional Government | Health | R&D health. | Pilot | 2.018 | 2022 | Public services and engagement | Service personalisation (various) | No | No | Artificial Intelligence | G2C | x | x | x | https://data.norge.no/kunstig-intelligens | Learning | Machine learning | Deep learning | 13/07/2023 | ||||||||||||||||||
| PSTW-1208 | Naturinngrep i inngrepsfri natur | https://nr.no/fagfelt/bildeanalyse-og-jordobservasjon/jordobservasjon/klima-og-miljo/ | The Norwegian Environment Agency (MDIR) is responsible for maintaining a map of intervention-free nature in Norway, which is defined as areas where there is at least 1 km to the nearest nature intervention. NR developed methods for the detection of construction roads and forest roads from Sentinel-2 satellite images with 10 m spatial resolution. The method is based on the deep neural network U-Net. By training U-Net on wind power development areas, the method found all the wind power development areas in Åfjord municipality, Trøndelag. Several of these development areas resulted in a reduction of intervention-free nature. By training U-Net on known roads, the method found an illegally built road in Melhus municipality, Trøndelag. | National | Norway | NO | Norwegian Environmental Agency | Central-Government | Environmental Protection | Environmental protection n.e.c. | Implemented | 2.020 | Enforcement | Supporting inspection processes | No | No | Artificial Intelligence | G2G | x | x | https://data.norge.no/kunstig-intelligens | Perception | Computer vision | 13/07/2023 | |||||||||||||||||||||
| PSTW-1213 | Chatbot Frida | https://memu.no/artikler/frida-jobber-dognet-rundt/ | Chatbot that uses AI technology to answer questions from citizens. The technology is not developed by NAV, it is delivered by boost.ai | National | Norway | NO | NAV IT | Central-Government | Social protection | Social protection n.e.c. | Implemented | 2.018 | Public services and engagement | Service personalisation (various) | No | No | Artificial Intelligence | G2C | x | x | x | x | x | x | https://data.norge.no/kunstig-intelligens | Communication | Natural language processing | AI Services | chatbot | 13/07/2023 | |||||||||||||||
| PSTW-1219 | AdaptAl - Adaptive control of aluminium production | https://prosjektbanken.forskningsradet.no/en/project/FORISS/314054?Kilde=FORISS&distribution=Ar&chart=bar&calcType=funding&Sprak=no&sortBy=date&sortOrder=desc&resultCount=30&offset=0&Geografi.2=L%C3%B8renskog | The project aims to create a product-service system that integrates various models, sensors, and virtual data using optimizing software. This system is based on a digital twin called PRO3, developed by Hydro - aluminium production company in Norway 34% owned by the Ministry fo Trade, Industry and Fisheries - over the past decade. PRO3 simulates and optimizes process parameters in the aluminium industry. The project extends the software's capabilities to include adaptive control, addressing process and chemical variations in the aluminium value chain. Without an adaptive control system, these variations can exceed tolerance limits, resulting in increased production costs. The project will demonstrate the adaptive control system through extrusion and forming processes in automotive, furniture, and sports markets. | National | Norway | NO | Norsk Hydro ASA | Central-Government | Economic Affairs | Mining, manufacturing and construction. | Pilot | 2.020 | 2023 | Internal management | Internal primary processes | No | No | Artificial Intelligence | G2G | x | x | https://data.norge.no/kunstig-intelligens | Learning | Optimisation | 13/07/2023 | ||||||||||||||||||||
| PSTW-122 | ARSI – Aerial Robot for Sewer Inspection | https://eurecat.org/en/portfolio-items/aerial-robot-for-sewer-inspection/ | The aspired robotics solution will be able to determine the state of the sewer in order to identify segments where the sewer’s functionality has been compromised, either by sediments or by structural defects. Other required functionalities of the technology include sewer monitoring and collecting samples of water, air and sediments. | Local | Spain | ES51 | Barcelona | Local Government | Housing and community amenities | Housing development. | Pilot | 2.017 | Enforcement | Supporting inspection processes | No | No | Artificial Intelligence | G2B | x | x | x | http://echord.eu/public/wp-content/uploads/2015/11/20141218_Challenge-Brief_Urban_Robotics.pdf | Integration and Interaction | Robotics and Automation | Machine learning | 08/11/2023 | |||||||||||||||||||
| PSTW-1220 | Norsk Hydro's AI tool to detect hackers | https://www.wsj.com/articles/norsk-hydro-tests-ai-in-cyber-defenses-after-attack-11566207000 | The AI tool is designed to plug security gaps by identifying areas where industrial equipment could be exposed to hackers and monitoring small changes over time. This solution is used by Norsk Hydro ASA, an aluminum production company that is 34% owned by the Ministry of Trade, Industry and Fisheries. | National | Norway | NO | Norsk Hydro ASA | Central-Government | Economic Affairs | Mining, manufacturing and construction. | Pilot | 2.019 | Enforcement | Improving Cybersecurity | No | No | Artificial Intelligence | G2G | x | x | https://data.norge.no/kunstig-intelligens | Services | Searching | 13/07/2023 | |||||||||||||||||||||
| PSTW-1221 | Unsupervised learning to detect customs declarations | https://www.digdir.no/kunstig-intelligens/fagforum-kunstig-intelligens-i-offentlig-sektor/2569 | Foreign operators are reported in the customs declaration as a free text field. This creates challenges for further analysis by both customs officers and data analysts. The data analytics department has developed an unsupervised algorithm to group a list of names. It is based on cluster analysis in a network and splitting cluster. | National | Norway | NO | Norwegian Customs (Tolletaten) | Central-Government | General public services | Executive and legislative organs, financial and fiscal affairs, external affairs. | Implemented | 2.021 | Enforcement | Predictive enforcement processes | No | No | Artificial Intelligence | G2G | x | x | https://data.norge.no/kunstig-intelligens | Learning | Machine learning | data analytics | 13/07/2023 | ||||||||||||||||||||
| PSTW-1222 | Automatisert saksbehandling med arkivmessige hensyn for kunstig intelligens | https://www.arkivverket.no/nyheter/automatisert-saksbehandling-og-innsyn-i-regulatorisk-sandkasse | The Norwegian Maritime Authority has initiated a major reorganisation of how the organisation will conduct case processing and associated information management in the future. When the Norwegian Maritime Directorate issues certificates in the future, it will be in an automated solution. Together with the National Archives and the Directorate of Digitisation, they will now look at how they can ensure that the documentation is taken care of and can be accessed. The new solutions will also be responsible for data collection. It is important that correct documentation, both incoming and outgoing, process and rules are ensured in an appropriate manner. | National | Norway | NO | Norwegian Maritime Authority | Central-Government | Economic Affairs | General economic, commercial and labour affair | In development | 2.022 | Internal management | Internal primary processes | No | No | Artificial Intelligence | G2G | x | x | https://data.norge.no/kunstig-intelligens | Learning | 13/07/2023 | ||||||||||||||||||||||
| PSTW-1223 | NVE Copernicus 2 | https://publikasjoner.nve.no/rapport/2021/rapport2021_03.pdf | Norsk Regnesentral develops algorithms that retrieve information about water and snow for emergency warnings related to avalanches and floods. | National | Norway | NO | Norwegian Water Resources and Energy Directorate | Central-Government | Economic Affairs | Fuel and energy | In development | 2.022 | Analysis, monitoring and regulatory research | Information analysis processes | No | No | Artificial Intelligence | G2G | x | x | x | https://data.norge.no/kunstig-intelligens | Perception | Computer vision | image processing | 13/07/2023 | |||||||||||||||||||
| PSTW-126 | Corpus Viewer: NLP and ML-based Platform for Public Policy Making and Implementation | http://journal.sepln.org/sepln/ojs/ojs/index.php/pln/article/view/6117, https://rua.ua.es/dspace/bitstream/10045/96627/1/PLN_63_28.pdf | The Corpus Viewer platform is based on natural language processing (PLN), machine learning (ML) and machine translation (MT) techniques to analyze structured metadata and unstructured textual data in large corpus of textual documents. The platform allows decision-makers and policy implementers the possibility to analyze the R&D information space (mainly patents, scientific publications and public aid) for the implementation of policies based on evidence and knowledge. It is based,modeling topics and graph analysis. Corpus Viewer development began in 2016 and continues to advance thanks to the collaboration of various university research groups and companies and it is currently used by 3 public administrations: SEAD (Ministry of Economy), the Spanish Foundation for Science and Technology (FECYT) and the Secretary of State for Universities and Research, Development and Innovation (SEUIDI) ( Ministry of Science). | National | Spain | ES | State Secretary for Digital Advancement (SEAD) | Central-Government | Health | Public health services. | Pilot | 2.019 | Enforcement | Predictive enforcement processes | No | No | Artificial Intelligence | G2C | x | x | x | https://www.plantl.gob.es/tecnologias-lenguaje/actividades/plataformas/Documents/corpus-viewer/manual-corpus-viewer-en.pdf | Learning | Machine learning | Natural language processing | Knowledge representation | 08/11/2023 | ||||||||||||||||||
| PSTW-1265 | AI to detect incorrect health reimbursement payments | https://www.helfo.no/nyheter/innovasjon-skal-bidra-til-riktig-bruk-av-offentlige-helsekroner | In a new innovation project, Helfo, in collaboration with Skatteforsk at the Norwegian University of Life Sciences, the Norwegian Institute of Public Health and the Centre for eHealth at the University of Agder (UiA), will develop new digital tools with the aim of creating systems that ensure responsible use of public health funds by preventing incorrect payment of health reimbursements. The innovation project involves developing new data-driven control systems. Data can be used in new models to improve controls and stop erroneous claims before payments are made. New tools will also be able to help uncover existing blind spots, free up resources and make reporting easier for the vast majority of health actors who try to follow the rules. | National | Norway | NO | The Norwegian Health Economics Administration | Central-Government | Health | Public health services. | In development | 2.021 | 2021 | Internal management | Internal support processes | No | No | Artificial Intelligence | G2G | x | x | https://data.norge.no/kunstig-intelligens | Learning | Machine learning | 14/07/2023 | ||||||||||||||||||||
| PSTW-1275 | SSmart On-Line health assessment of cable terminations | https://prosjektbanken.forskningsradet.no/project/FORISS/318007 | In the SmartACT project, an innovative and non-intrusive long-life sensor system for online condition assessment and monitoring will be developed and tested for installation inside 420 kV oil-filled cable terminations, which are the components most prone to failure. This new sensor system will provide continuous feedback regarding the condition of the cable terminals, thus allowing mitigation procedures when needed to avoid supply interruptions. The sensor system is expected to increase the security of energy supply by assessing temperature, humidity, pressure and partial discharges (PD) combined with a new digitalised machine learning assisted assessment methodology. SmartACT therefore addresses thematic priority area 3 in the ENERGIX work programme. Collaboration between the Norwegian TSO Statnett, Nexans Norway, SINTEF and NTNU is essential to achieve the project goals. | National | Norway | NO | Statnett | Central-Government | Economic Affairs | Fuel and energy | In development | 2.021 | 2024 | Internal management | Internal primary processes | No | No | Artificial Intelligence | G2G | x | x | https://data.norge.no/kunstig-intelligens | Perception | sensor system | 17/07/2023 | ||||||||||||||||||||
| PSTW-128 | Tengai - Robot in recruitment processes | https://www.mynewsdesk.com/tengai-interview-robot/pressreleases/swedish-muncipality-first-in-the-world-to-use-social-interview-robot-tengai-in-recruitment-2878357 | Municipality of Upplands-Bro experimented the robot Tengai in their recruitment processes since June 2019. Tengai is one of the first interviewer robots developed with the aim to make the recruitment process less biased than traditional interview practices would do. The robot is adopted by the recruitment and staffing agency of the municipality, which has already made their recruitment processes less biased. The Tengai robot is the result of a collaboration between the municipality staff and the AI consultancy Furhat Robotics. After the Tengai robot was released, within a week, it was decided to adopt its services permanently. Tengai firstly identify candidates with the highest general performance score, in order to make a shortlist for future selections. The robot then conducts the interviews to assess the candidates by analysing their behaviours, problem-solving capacities and other skills. If needed, the robot is able to ask follow-up questions. The interviews are then analysed, combined with the competency scores. The recruiters of the municipality will conduct the final interview with candidates to assess their motivation. The first results following the adoption of the Tengai robot have been regarded as successful and brought significant media attention to the municipality due to the innovative approach to recruitment. | Local | Sweden | SE | Municipality of Upplands-Bro | Local Government | General public services | General public services n.e.c. | Implemented | 2.019 | Internal management | Internal primary processes | No | No | Artificial Intelligence | G2G | x | x | x | https://www.mynewsdesk.com/tengai-interview-robot/pressreleases/swedish-muncipality-first-in-the-world-to-use-social-interview-robot-tengai-in-recruitment-2878357 | Communication | Natural language processing | Machine learning | Audio processing | Robotics and Automation | speech recognition | 08/11/2023 | ||||||||||||||||
| PSTW-1285 | Automated case management of family immigration with a professional background | https://www.ledernytt.no/et-lite-innblikk-i-moderne-teknologi-for-udi.6390894.html | Until 2020, all citizenship applications at the Directorate of Immigration were processed manually. They came in one by one, and were assessed individually by a case officer. Because the volume of applications is so large, such manual processes take a long time. Normally, the processing time for citizenship applications has been over a year. To meet the enormous pressure and optimise case management processes, case management is now being automated. | National | Norway | NO | Directorate of Immigration | Central-Government | Public order and safety | Police Services | Pilot | 2.021 | Internal management | Internal primary processes | No | No | Artificial Intelligence | G2G | x | x | x | x | https://data.norge.no/kunstig-intelligens | Integration and Interaction | Robotics and Automation | 17/07/2023 | |||||||||||||||||||
| PSTW-1286 | Ada-bot helps process applications for family reunification | https://forskning.no/juridiske-fag-roboter/roboter-er-pa-full-fart-inn-i-jussen/1588380 | The robot "Ada" at the Directorate of Immigration is programmed to make individual decisions based on laws and other legal sources. Ada collects documents for family reunification cases. This can make the whole process up to five times faster. | National | Norway | NO | Directorate of Immigration | Central-Government | Public order and safety | Police Services | Implemented | 2.019 | Internal management | Internal primary processes | No | No | Artificial Intelligence | G2G | x | x | https://data.norge.no/kunstig-intelligens | Integration and Interaction | Robotics and Automation | 17/07/2023 | |||||||||||||||||||||
| PSTW-1288 | KartAi: automate and streamline case management in construction cases | https://kartai.no/ | A research project to improve the quality of the property register (cadastre) and the Central Common Map Database (SFKB) using artificial intelligence (AI). | Local | Norway | NO09 | Kristiansand Municipality | Local Government | Housing and community amenities | Housing development. | Pilot | 2.021 | 2023 | Analysis, monitoring and regulatory research | Information analysis processes | No | No | Artificial Intelligence | G2G | x | x | https://data.norge.no/kunstig-intelligens | Learning | Machine learning | Computer vision | 17/07/2023 | |||||||||||||||||||
| PSTW-129 | AIDA - Interpreting detailed plan provisions | https://www.smartbuilt.se/projekt/innovationer-och-nya-tillaempningar/aida/ | In order to more quickly digitize Sweden's existing detail plans and get closer to a national plan database, the project developed and implemented an Artificial Intelligence system to work on interpreting detail plan regulations according to the National Board of Housing, Building and Planning's standard. The goal was to reduce the digitization process by 20%, which would, taking into account all the detailed plans to be digitized, would save years of working time. In addition, both direct and indirect effects would have contributed to Smart Built Environment's goals. | National | Sweden | SE | Örebro Municipality | Local Government | General public services | Executive and legislative organs, financial and fiscal affairs, external affairs. | Pilot | 2.018 | Analysis, monitoring and regulatory research | Information analysis processes | No | No | Artificial Intelligence | G2B | x | x | x | https://www.smartbuilt.se/projekt/innovationer-och-nya-tillaempningar/aida/ | Communication | Natural language processing | Machine learning | text analysis | 08/11/2023 | ||||||||||||||||||
| PSTW-1291 | Helsinki chatbot | https://ai.hel.fi/en/helsinki-chatbot/ | Helsinki chatbot is a 24-hour customer service channel of the City of Helsinki information website, aimed at improving the accessibility of customer service and the customer experience. The service provides relevant information to each customer’s specific questions faster than by searching for the information on the website. In the initial phase, the chatbot will implemented within the Sports and Recreation related pages. For instance, the chatbot will answer questions related to sports facilities and services. The service will work based on the trained rule-based discussion paths and the question-answer pairs determined by specialists from Helsinki City Information and thematic experts. | Local | Finland | FI1B | City of Helsinki | Local Government | General public services | General services. | Implemented | 2.023 | Public services and engagement | Service personalisation (various) | No | No | Artificial Intelligence | G2C | x | x | x | x | x | x | https://gouai.cidob.org/atlas/ | Communication | Natural language processing | AI Services | chatbot | 07/08/2023 | |||||||||||||||
| PSTW-1292 | E-vignette: toll road payment controlled by AI | https://evinjeta.dars.si/en/toll-control | The e-vignette is the new online way of paying the motorway toll for travelling through slovenian highways, using just the personal e-mail and the registration number of the vehicle. The correct use of the e-vignette is controlled by the Motorway Company in the Republic of Slovenia (DARS), the Financial Administration of the Republic of Slovenia and the Police. The toll road operator controls whether travellers have bought the e-vignette via cameras on the motorway network, at control points, and by using toll control vehicles. After the system has checked the vehicle for which the e-vignette is purchased, this information is erased from the system immediately upon establishing tolling compliance, and no traces are left in the system regarding the use of the toll road. If non-compliance is detected, the system stores the information until the completion of the minor offence proceedings. | National | Slovenia | SI | Financial Administration of the Republic of Slovenia | Central-Government | Public order and safety | Police Services | Implemented | 2.022 | Enforcement | Smart Recognition processes | No | No | Artificial Intelligence | G2G | x | x | x | https://evinjeta.dars.si/en/toll-control | Perception | Computer vision | 21/08/2023 | ||||||||||||||||||||
| PSTW-1294 | Algorithmic Transparency Standard | https://www.algorithmregister.org/standard | The Algorithmic Transparency Standard is a set of shared categories of information that cities can use to help people understand how the algorithms used in local administrations work, and what their purpose is. It is publicly available for administration to use and download in the .cvs and Excel format. This will allow people to compare different algorithms within and across cities. This standard was created to support documenting decisions and assumptions for both management of artificial intelligence (AI) governance and provide meaningful transparency in a standardized way. | Across Countries | European Union | EU | City of Amsterdam, Barcelona, Brussels, Eindhoven, Mannheim, Rotterdam and Sofia | Local Government | General public services | Executive and legislative organs, financial and fiscal affairs, external affairs. | Pilot | 2.022 | Public services and engagement | Engagement management | No | No | Artificial Intelligence | G2C | x | x | x | x | x | https://gouai.cidob.org/atlas/ | Ethics and Philosophy | AI Services | 21/08/2023 | ||||||||||||||||||
| PSTW-1298 | Public Eye: AI crowd monitoring system in Amsterdam | https://druktebeeld.amsterdam.nl/ | Public Eye maps the crowds in a few places in Amsterdam (e.g., Arena Boulevard, Marineterrein and Dam Square). There are cameras that are linked to a server of the municipality. An algorithm on the server analyses through the images how many people are present in the location or how many biking parks are filled. Then the information, but not the images, are shown on the publicly available platform for citizens' access. The information about the number of people is also forwarded to municipal employees, who can use the count to better regulate traffic. The ambition is to realize this for all locations. | Local | Netherlands | NL32 | City of Amsterdam | Local Government | General public services | General services. | Implemented | 2.022 | Enforcement | Smart Recognition processes | No | No | Artificial Intelligence | G2C | x | x | x | https://algoritmeregister.amsterdam.nl/public-eye/ | Perception | Computer vision | 21/08/2023 | ||||||||||||||||||||
| PSTW-1299 | AI for poverty detection | https://algoritmeregister.amsterdam.nl/vroeg-eropaf/ | The City of Amsterdam receives a report from health insurers, housing associations, energy suppliers and Waternet, amongst others, if they have a customer who has payment arrears with them. The system forwards the report to a social worker from the municipality, who then contacts the citizen within 14 days and makes an initial analysis within 28 days to offer information and make detailed agreements. The social worker reports to the central reporting point which agreements have been made, so that a creditor knows what the next steps are for the payment arrears. The linking of the creditors' report with the data of the Poverty Reduction Department is automated, but a human action is required to start the link. From the moment the report has been forwarded to the emergency services in the correct district, the process is no longer automated. The social service provider visits the reported citizen if the citizen does not make contact himself. | Local | Netherlands | NL32 | City of Amsterdam | Local Government | Social protection | Social exclusion n.e.c. | Implemented | 2.022 | Enforcement | Supporting inspection processes | No | No | Artificial Intelligence | G2G | x | x | https://gouai.cidob.org/atlas/ | Learning | Machine learning | 21/08/2023 | |||||||||||||||||||||
| PSTW-13 | VDAB Chatbot for job seekers - Chatbots to better match jobseekers with the right vacancies | https://www.vdab.be/ | VDAB experiments with chatbots to better match jobseekers with the right vacancies. A chatbot is an automated conversation partner that participates in typed conversations. VDAB is also investigating how chatbots can guide job seekers in their search by automatically answering questions and addressing job seekers. http://chatbotvanvdab.be/ | Local | Belgium | BE | Vlaamse Dienst voor Arbeidsbemiddeling en Beroepsopleiding | Local Government | General public services | Executive and legislative organs, financial and fiscal affairs, external affairs. | Implemented | 2.020 | Public services and engagement | Service personalisation (various) | No | No | Artificial Intelligence | G2C | x | x | x | x | https://github.com/vercruyssetim/chatbot-vdab https://www.philippemuyters.be/nieuws/chatbots-en-artificiele-intelligentie-bij-de-vdab | Communication | Natural language processing | Searching | Optimisation | chatbot | 06/10/2023 | ||||||||||||||||
| PSTW-1300 | Autonomous Boats Deployment | https://www.ams-institute.org/news/roboat-ready-self-driving-pilots-amsterdam-canals/ | The project, named Roboat, is a joint research program of Massachusetts Institute of Technology (MIT) and Amsterdam Institute for Advanced Metropolitan Solutions (AMS Institute), supported by the City of Amsterdam, Amsterdam’s water company Waternet and the City of Boston. Through this project, Amsterdam will deploy self-driving boat pilots equipped with sensors to perceive their surroundings. It is envisioned to fulfil multiple functions: from passenger transport, waste collection to the monitoring of the water quality. | Local | Netherlands | NL32 | City of Amsterdam | Local Government | General public services | General services. | Pilot | 2.021 | Public services and engagement | Service integration (various) | No | No | Artificial Intelligence | G2C | x | x | https://gouai.cidob.org/atlas/ | Perception | Computer vision | Robotics and Automation | 21/08/2023 | ||||||||||||||||||||
| PSTW-1301 | Using AI to measure accessibility | https://amsterdamintelligence.com/posts/using-artificial-intelligence-to-measure-accessibility | The City of Amsterdam launched the “Amsterdam for All” project with the goal of making the city accessible for all. To do so, the project uses AI to measure the accessibility of the city in a series of experiments. On one hand, AI is being used to improve pedestrian mobility, for example by predicting which sidewalks have obstacles or where pathways, curb ramps or crosswalks are located. The aim is to offer the appropriate data and analytics to city officials so they can base their decisions on tangible evidence and find out which problems need to be tackled. | Local | Netherlands | NL32 | City of Amsterdam | Local Government | Social protection | Sickness and disability. | Pilot | 2.022 | Analysis, monitoring and regulatory research | Innovating Public Policy | No | No | Artificial Intelligence | G2G | x | x | x | x | x | https://gouai.cidob.org/atlas/ | Perception | Computer vision | 21/08/2023 | ||||||||||||||||||
| PSTW-1302 | Automatically Assessing and Improving the Readability of Municipal Communication | https://www.amsterdamintelligence.com/posts/automatically-assessing-and-improving-the-readability-of-municipal-communication | According to recent research, 16% of the people between 16 and 65 in Amsterdam have low literacy skills. This hinders societal participation in tasks such as voting, paying taxes, reissuing documents, or applying for social benefits. Thus, as part of "Amsterdam for All" project, the City of Amsterdam set on a mission to research the use of AI for measuring and improving the readability of municipal communication, using an innovative methodology for contextualized lexical simplification, which means substituting complex words within the context of a sentence with more accessible ones. | Local | Netherlands | NL32 | City of Amsterdam | Local Government | Social protection | Sickness and disability. | In development | 2.023 | Public services and engagement | Service personalisation (various) | No | No | Artificial Intelligence | G2C | x | x | x | x | x | x | https://gouai.cidob.org/atlas/ | Communication | Natural language processing | 21/08/2023 | |||||||||||||||||
| PSTW-1303 | AI for green roof management | https://greencitywatch.com/accurate-green-roof-area-quantification | Although the City of Amsterdam has mapped green roof coverage across the city before, there is lack of comprehensive data. For example, in the previous study, if less than 30% of a building roof was covered in green, the entire roof area would be categorised as a green roof. This meant that up to two-thirds of the data collected was unreliable and, likely, inaccurate. To resolve this, and to achieve an accurate estimation of green roof area coverage across the City of Amsterdam, Green City Watch built a proof-of-concept using Very High Resolution (VHR) satellite imagery. VHR imagery enables a pixel resolution of ±30 cm, so we can quantify the exact roof composition, pixel by pixel. | Local | Netherlands | NL32 | City of Amsterdam | Local Government | Environmental Protection | R&D environmental protection. | Pilot | 2.023 | Enforcement | Smart Recognition processes | No | No | Artificial Intelligence | G2G | x | x | https://gouai.cidob.org/atlas/ | Perception | Computer vision | Machine learning | 21/08/2023 | ||||||||||||||||||||
| PSTW-1304 | 3D Point Cloud | https://amsterdamintelligence.com/projects/3d-point-cloud | The City of Amsterdam uses mobile LiDAR-scanners - a type of technology that allows to gather a 3D representation of the environment through the visual representation of "point clouds". This technology allows to detect the exact location of objects and to capture geometric properties such as their width and height. The goal of this project is to automatically locate and classify various assets such as trees, street lights, traffic signs, and other street furniture in street level point clouds; this offers valuable information about the streets of Amsterdam. | Local | Netherlands | NL32 | City of Amsterdam | Local Government | General public services | Basic research. | Pilot | 2.023 | Analysis, monitoring and regulatory research | Information analysis processes | No | No | Artificial Intelligence | G2G | x | x | https://gouai.cidob.org/atlas/ | Perception | Computer vision | Machine learning | 21/08/2023 | ||||||||||||||||||||
| PSTW-1305 | The Hague Digital Twin | https://www.argaleo.com/en/pf/living-lab-scheveningen/ | The Municipality of The Hague is developing a Living Lab on the coast of Scheveningen to learn how digitisation and technological solutions can contribute to solutions for social, economic and societal challenges facing the city. One of these technological solutions is the online Digital Twin dashboard where (live) data is visualised and can be analysed. As a first step, pedestrian and bicycle data is examined to, among other things, support the management of peak traffic volumes. The solution includes real-time location of buses, trams and trains, information about the cycle network, cycle paths and bicycle parking facilities and accessibility analyses of hotspots. | Local | Netherlands | NL33 | Municipality of The Hague | Local Government | General public services | R&D general public services. | Pilot | 2.021 | Analysis, monitoring and regulatory research | Innovating Public Policy | No | No | Artificial Intelligence | G2G | x | x | x | https://gouai.cidob.org/atlas/ | Perception | Machine learning | Computer vision | 21/08/2023 | |||||||||||||||||||
| PSTW-1306 | Digital Twin Technology to Improve Operations | https://www.portofrotterdam.com/en/to-do-port/futureland/smart-shipping-process | The Port of Rotterdam piloted the development of an Internet of Things cloud-based platform in partnership with IBM, Esri Cisco and Axians to create the port's digital twin. This platform would allow users to access a variety of hydrological and metereological data - for examples, water levels, salinity, wind speeds, visibility and currents - that has been collected with the aid of sensors. The platform is intended to help the port reduce waiting times and optimise mooring, loading and departure windows. or example, the platform could be used to predict the best time for mooring and departure, with the guarantee of maximum capacity utilisation, based on the recorded water level, currents and wind conditions. | Local | Netherlands | NL33 | Port of Rotterdam | Local Government | Economic Affairs | Transport | Pilot | 2.018 | Internal management | Internal primary processes | No | No | Artificial Intelligence | G2G | x | x | x | https://gouai.cidob.org/atlas/ | Learning | Machine learning | internet of things | 21/08/2023 | |||||||||||||||||||
| PSTW-1307 | Chatbot for rental apartment search | https://ai.hel.fi/en/the-rental-apartment-search-chatbot/ | The rental apartment search chatbot is a 24-hour customer service channel of the City of Helsinki housing services aimed at improving the accessibility of customer service. The service provides relevant information to each customer’s specific questions realted to finding housing in the city, faster than by searching for the information on the website. The chatbot responds based on the trained rule-based discussion paths and the question-answer pairs determined by rental apartment search experts. The service also increases efficiency by enabling the automation of frequently asked questions. | Local | Finland | FI1B | City of Helsinki | Local Government | Housing and community amenities | Housing and community amenities n.e.c. | Implemented | 2.022 | Public services and engagement | Service personalisation (various) | No | No | Artificial Intelligence | G2C | x | x | x | x | x | x | https://gouai.cidob.org/atlas/ | Communication | Natural language processing | AI Services | chatbot | 21/08/2023 | |||||||||||||||
| PSTW-131 | SKOSA - Interpreting medical information | https://computersweden.idg.se/2.2683/1.720144/forsakringskassan-ai-stod | The project, called Skosa, builds a general platform with a digital knowledge base with the help of various business experts such as doctors and other experts. It can then help administrators to analyze, structure and interpret medical information and use it in needs assessments. | National | Sweden | SE | Swedish Social Insurance Agency | Central-Government | Health | Hospital services. | Implemented | 2.020 | Analysis, monitoring and regulatory research | Information analysis processes | No | No | Artificial Intelligence | G2G | x | x | x | x | https://computersweden.idg.se/2.2683/1.720144/forsakringskassan-ai-stod | Reasoning | Knowledge representation | Machine learning | 08/11/2023 | ||||||||||||||||||
| PSTW-132 | Scapis - Prevention of heart- and lung-diseases | https://www.scapis.org/about/ | Prevention of heart- and lung-diseases. SCAPIS is the largest population study in Sweden within the cardiovascular and pulmonary system area. It is a world unique project that includes 30,000 patients and involves all six healthcare regions, university hospitals and a number of scientific players. The vision is to be able to individualize risk assessments as well as to prevent and postpone cardiovascular and pulmonary diseases in patients. SCAPIS, Swedish CardioPulmonary bioImage Study, is a population study around cardiovascular, epidemic and genetic research, initiated by Swedish researchers in 2007. A pilot study was conducted in 2012 to ensure that the population study was possible to implement, and in 2014, the major SCAPIS study was initiated. | National | Sweden | SE | Uppsala, Umeå, Linköping, Malmö/Lund, Gothenburg and Stockholm Hospitals | Central-Government | Health | Hospital services. | Pilot | 2.014 | Public services and engagement | Service personalisation (various) | No | No | Artificial Intelligence | G2G | x | x | x | https://www.scapis.org/about/ | Learning | Machine learning | Automated reasoning | 08/11/2023 | |||||||||||||||||||
| PSTW-1321 | Intelligent management of aid to citizens and companies | https://oecd-opsi.org/wp-content/uploads/2022/10/UAI_Intelligent-Management-Aid_EN_def.pdf | The European Union, committed to economic recovery and the protection of citizens' rights during the covid-19 pandemic, made it possible to provide the Andalusian region with funding for the implementation of a large number of aids that would help preserve employment and ensure financial stability. The aid management process was however one of the most complex processes that the Andalusian administration has been carrying out manually. The Digital Agency of Andalusia implemented the aid automation process, based on innovative process automation technology (Robotic Process Automation - RPA). Since then, the intelligent aid management system has processed more than 300 000 aid applications. | Regional | Spain | ES61 | Digital Agency of Andalusia | Regional Government | Social protection | Social protection n.e.c. | Implemented | 2.020 | Adjudication | Taking decisions on benefits | No | No | Artificial Intelligence | G2G | x | x | x | x | https://oecd-opsi.org/innovations/intelligent-management-of-aid-to-citizens-and-companies/ | Learning | Machine learning | 23/08/2023 | |||||||||||||||||||
| PSTW-1322 | Monitoring structure health of bridges with InSAR | https://www.innovatieveoverheidsopdrachten.be/en/projects/monitoring-structure-health-bridges-insar | Using radar satellite images, theoretical displacements down to the millimeter level can be determined by measuring phase differences between successive images. This is done based on an INSAR (Interferometric Synthetic Aperture Radar) analysis.The project aims at monitoring bridge deformations based on this technique. The main goal of the project is to investigate whether INSAR can be deployed in the daily management of bridges and to investigate which types of satellite images and analysis are best suited for this purpose. The second objective of this innovation is to detect problems faster based on the analysis carried out and to use topographic measurements more efficiently on bridges that may pose a risk. Ideally, anomalies in the deformations can be automatically detected for this. | Regional | Belgium | BE2 | Flemish Ministry of Mobility and Public Works (MOW) | Regional Government | Economic Affairs | Transport | Pilot | 2.022 | Analysis, monitoring and regulatory research | Information analysis processes | No | No | Artificial Intelligence | G2G | x | x | https://oecd-opsi.org/innovations/monitoring-structure-health-of-bridges-with-insar/ | Perception | Computer vision | 23/08/2023 | |||||||||||||||||||||
| PSTW-1324 | Hello Lamp Post | https://www.gov.uk/government/news/environment-agency-flood-defences-now-talk-back | The Environment Agency has a responsibility to protect communities from flood and coastal risks. In the past, the agency has struggled to scale their public engagement and reach their diverse audiences, while also retaining a local relevance. Hello Lamp Post was brought on to provide an interactive, live 24/7 conversational channel to educate and inform the public on flood safety, in high-risk locations around the South West of England and Newcastle. | National | United Kingdom | UK | Environment Agency | Central-Government | Public order and safety | Public order and safety n.e.c. | Pilot | 2.021 | Public services and engagement | Service personalisation (various) | No | No | Artificial Intelligence | G2C | x | x | x | x | x | https://oecd-opsi.org/innovations/hello-lamp-post/ | Communication | Natural language processing | 23/08/2023 | ||||||||||||||||||
| PSTW-1326 | Citibeats – Ethical AI for Social Understanding | https://www.citibeats.com/ | Citibeats is a AI platform that searches and analyzes large amounts of text provided by citizens - the application structures this data using natural language processing (NPL) and machine learning (ML) techniques. The solution identifies social trends, leading indicators, and insights for governments, and organizations thanks to the analysis of open data. | Local | Spain | ES51 | City of Barcelona | Local Government | General public services | General services. | Pilot | 2.018 | Analysis, monitoring and regulatory research | Information analysis processes | No | No | Artificial Intelligence | G2G | x | x | x | https://oecd-opsi.org/innovations/citibeats/ | Learning | Machine learning | Natural language processing | sentiment analysis | 23/08/2023 | ||||||||||||||||||
| PSTW-1327 | Madrid Mobility 360 (multimodal planner for urban commuting) | https://www.mobility360.app/ | Madrid Mobility 360 is a mobile application that allows citizens to move around the city and calculate the most efficient route between all modes of transport in the capital (public transportation, carsharing and bicycles). It includes a powerful route planner, which estimates current and future journey times, and provides the real-time capacity on specific buses. The app allows payment for various methods of transport and reports the CO2 emissions generated. | Local | Spain | ES30 | Empresa Municipal de Transported del Ayuntamiento de Madrid | Local Government | Economic Affairs | Transport | Implemented | 2.020 | Public services and engagement | Service personalisation (various) | No | No | Artificial Intelligence | G2C | x | x | x | x | x | https://oecd-opsi.org/innovations/madrid-mobility-360/ | Planning | Planning and Scheduling | Machine learning | recommender system | 23/08/2023 | ||||||||||||||||
| PSTW-133 | Norwegian Tax Administration chat service | https://www.skatteetaten.no/en/person/taxes/tax-return/find-item/ | Norwegian Tax Administration chat service answering to general enquiries. | National | Norway | NO | Norwegian Tax Administration | Central-Government | General public services | Executive and legislative organs, financial and fiscal affairs, external affairs. | Implemented | 2.017 | Public services and engagement | Engagement management | No | No | Artificial Intelligence | G2C | x | x | x | https://www.skatteetaten.no/en/person/taxes/tax-return/find-item/ | Communication | Natural language processing | Searching | chatbot | 08/11/2023 | ||||||||||||||||||
| PSTW-1330 | HOPE - Healthy Outdoor Premises for Everyone | https://kartta.hsy.fi/ | This air quality monitoring network in Helsinki region provides information from fixed monitoring stations but the network consists currently of only few locations. The project aims to produce comprehensive hyper-local air quality monitoring network, including crowdsourcing portable monitors that gives citizens air quality information of the exposure to air pollution in places where they live and they travel in the city. | Local | Finland | FI1B | City of Helsinki | Local Government | Environmental Protection | Environmental protection n.e.c. | Pilot | 2.018 | 2022 | Analysis, monitoring and regulatory research | Information analysis processes | No | No | Artificial Intelligence | G2G | x | x | x | x | x | x | https://oecd-opsi.org/innovations/hope-project/ | Perception | sensors system | 23/08/2023 | ||||||||||||||||
| PSTW-1331 | Aeolus – Mid-altitude maritime monitoring platform for security, search & rescue and environmental monitoring | http://aeolus.ie/ | AELOUS is a mid-altitude airborne maritime sensor platform which significantly increases the operating surveillance range by increasing the elevation of the monitoring systems. The Aeolus platform can effectively operate at 450m above the ship – increasing the surveillance area in excess of 11 times of what can be monitored with existing solutions. The platform can be used with multiple lifting systems and can be deployed for many hours. | National | Ireland | IE | Irish Naval Service | Central-Government | Defence | Military defence. | Pilot | 2.018 | Enforcement | Smart Recognition processes | No | No | Artificial Intelligence | G2G | x | x | x | https://oecd-opsi.org/innovations/aeolus-mid-altitude-maritime-monitoring-platform-for-security-search-rescue-and-environmental-monitoring/ | Perception | Computer vision | 24/08/2023 | ||||||||||||||||||||
| PSTW-1333 | R2D3: Active-waiting robot for the disabled people’s waiting room | https://www.youtube.com/watch?v=xinXJGvtNX8&t=83s | The active-waiting robot was developed by the French local-level Seine Saint Denis Innovation Lab. They created the robot R2-D3 to help reduce the digital gap with Departmental Home for Disabled Persons users. It informs users on various topics in a playful and simplified way. It can speak and understand many languages. It is user-oriented and it's built upon new robotic and open-source technology. | Local | France | FR10 | Saint Denis Innovation Lab | Local Government | Social protection | Sickness and disability. | Pilot | 2.017 | Public services and engagement | Service personalisation (various) | No | No | Artificial Intelligence | G2C | x | x | x | x | x | https://oecd-opsi.org/innovations/r2d3-active-waiting-robot-for-the-disabled-peoples-waiting-room-at-bobigny-france/ | Integration and Interaction | Robotics and Automation | 24/08/2023 | ||||||||||||||||||
| PSTW-1334 | Voice assistant services | https://aws.amazon.com/it/solutions/case-studies/aylesbury-vale-district-council/#:~:text=About%20Aylesbury%20Vale%20District%20Council&text=Using%20artificial%20intelligence%2C%20the%20Council,can%20go%20in%20recycling%20bins. | Aylesbury Vale District Council (AVDC) is the first local authority in the UK to launch a skill for Amazon’s voice-controlled Alexa. Residents can ask for various information, including: who are the political leaders of the council, council tax payment options, and what items can go in recycling bins. There is also an option to book assisted waste collections. | Local | United Kingdom | UKJ1 | Aylesbury Vale District Council | Local Government | General public services | General public services n.e.c. | Implemented | 2.017 | Public services and engagement | Service personalisation (various) | No | No | Artificial Intelligence | G2C | x | x | x | x | x | x | https://oecd-opsi.org/innovations/voice-assistant-services-aylesbury-vale-district-council-others/ | Communication | Natural language processing | Robotics and Automation | chatbot | 24/08/2023 | |||||||||||||||
| PSTW-1335 | Alexa skill - vehicle tax and MOT | https://www.amazon.co.uk/DVLA-Vehicle-Enquiry/dp/B07414QQ18/ref=sr_1_1?s=digitalskills&%20ie=UTF8&qid=1501145333&sr=1-1&keywords=DVLA | The UK Government’s Driving License and Vehicle Authority (DVLA) has deployed a voice-based service (Alexa skill) for stating when a citizen’s vehicle tax and MOT (motor technical test) is due. | National | United Kingdom | UK | Driver and Vehicle Licensing Agency (DVLA) | Central-Government | General public services | General public services n.e.c. | Implemented | 2.017 | Public services and engagement | Service personalisation (various) | No | No | Artificial Intelligence | G2C | x | x | x | x | x | x | https://oecd-opsi.org/innovations/voice-assistant-services-aylesbury-vale-district-council-others/ | Communication | Natural language processing | Robotics and Automation | chatbot | 24/08/2023 | |||||||||||||||
| PSTW-1336 | Alexa skill and Google home app - checking state pension age | https://www.gov.uk/government/news/government-uses-alexa-and-google-home-to-make-services-easier-to-access | The UK Government’s Department for Work and Pensions have also developed a prototype voice service (Alexa skill) for checking state pension age. | National | United Kingdom | UK | Department for Work and Pensions | Central-Government | Social protection | Old age. | Implemented | 2.019 | Public services and engagement | Service personalisation (various) | No | No | Artificial Intelligence | G2C | x | x | x | x | x | x | https://oecd-opsi.org/innovations/voice-assistant-services-aylesbury-vale-district-council-others/ | Communication | Natural language processing | Robotics and Automation | chatbot | 24/08/2023 | |||||||||||||||
| PSTW-1337 | Alexa skill - enquiring about tax credits | https://www.gov.uk/government/news/open-hmrc-alexa-helps-tax-credits-customer | HM Revenue and Customs (HMRC) launched new and innovative technology to help more than 3 million customers renew their tax credits. HMRC has developed a customer-focused service through Amazon Alexa specifically for those seeking help with their tax credits renewals. | National | United Kingdom | UK | Her Majesty’s Revenue & Customers | Central-Government | General public services | Executive and legislative organs, financial and fiscal affairs, external affairs. | Implemented | 2.018 | Public services and engagement | Service personalisation (various) | No | No | Artificial Intelligence | G2C | x | x | x | x | x | x | https://oecd-opsi.org/innovations/voice-assistant-services-aylesbury-vale-district-council-others/ | Communication | Natural language processing | Robotics and Automation | chatbot | 24/08/2023 | |||||||||||||||
| PSTW-1339 | Big Data Analysis for HR efficiency improvement | https://www.oecd-ilibrary.org/docserver/932780bc-en.pdf?expires=1692870748&id=id&accname=guest&checksum=A86B6C131EBB7C712599C331A1D4E692 | The Big Data pilot project launched in April 2016, with the objective to learn what a big data tool installed on the Governmental State Cloud Infrastructure could enable in terms of the research of HR data in the Ministry of Public Administration to improve our efficiency, develop organisational capacity, improve effectiveness and efficiency and staff satisfaction. | National | Slovenia | SI | Ministry of Public Administration | Central-Government | General public services | General services. | Pilot | 2.016 | Internal management | Internal management processes | No | No | Artificial Intelligence | G2G | x | x | https://oecd-opsi.org/innovations/partnering-with-emc-dell-to-infuse-big-data-analysis-into-the-ministry-of-public-administration-of-republic-of-slovenia/ | Learning | Machine learning | data analytics | 24/08/2023 | ||||||||||||||||||||
| PSTW-1341 | Chatbot Munich | https://muenchen.digital/blog/chatbot-technologie-kommunikationskanaele-im-kvr-bekommen-zuwachs/ | The IT-Department of the municipality of Munich is developing a chatbot for Munich which is supposed to complete the current services like the common emergency number 115, the service portal and mobile apps. | Local | Germany | DE21 | Municipality of Munich | Local Government | General public services | General public services n.e.c. | In development | 2.023 | Public services and engagement | Service personalisation (various) | No | No | Artificial Intelligence | G2C | x | x | x | x | x | x | https://www.koinno-bmwk.de/fileadmin/user_upload/publikationen/Mapping_AI_in_Public_Sector_new.pdf | Communication | Natural language processing | AI Services | chatbot | 24/08/2023 | |||||||||||||||
| PSTW-1342 | Steuerchatbot | https://steuerchatbot.digital-bw.de/steuerbw.html | The Department of Finances in Karlsruhe has established a chatbot to answer simple questions related to tax declarations. | Local | Germany | DE12 | Municipality of Karlsruhe | Local Government | General public services | Executive and legislative organs, financial and fiscal affairs, external affairs. | In development | 2.020 | Public services and engagement | Service personalisation (various) | No | No | Artificial Intelligence | G2C | x | x | x | x | x | x | https://www.koinno-bmwk.de/fileadmin/user_upload/publikationen/Mapping_AI_in_Public_Sector_new.pdf | Communication | Natural language processing | AI Services | chatbot | 24/08/2023 | |||||||||||||||
| PSTW-1343 | DB Smile - the national railway service chatbot for job seekers | https://chatbot-bahn.de/ | Thanks to artificial intelligence (AI), the DB Smile chatbot can find suitable jobs, provide answers to almost all questions relating to a job application, and now even accept job applications via chat, making the entire process easier and quicker. | National | Germany | DE | Deutsche Bahn | Central-Government | Economic Affairs | Transport | Implemented | 2.023 | Public services and engagement | Service personalisation (various) | No | No | Artificial Intelligence | G2C | x | x | x | x | x | x | https://www.dbsystel.de/dbsystel-en/about-us/Digital-Stories-en/The-DB-Smile-chatbot-a-personal-assistant-for-job-applications-10565436 | Communication | Natural language processing | AI Services | chatbot | 24/08/2023 | |||||||||||||||
| PSTW-1344 | SEMMI - Avatar | https://semmi.deutschebahn.com/semmi-en/SEMMI-as-a-Service/SEMMI-Avatar | SEMMI Avatar is an advanced, lively and user-friendly human-machine interface which complements customer service. Operating on the SEMMI Conversational AI, SEMMI Avatar leverages display hardware to deliver a novel, multimodal experience for users. With only a minimum of requirements, SEMMI Avatar can be used on existing or new hardware, outdoor or indoor, with or without touchscreen and completely responsive on any screen size and format. | National | Germany | DE | Deutsche Bahn | Central-Government | Economic Affairs | Transport | Implemented | 2.023 | Public services and engagement | Service personalisation (various) | No | No | Artificial Intelligence | G2C | x | x | x | x | x | x | https://www.koinno-bmwk.de/fileadmin/user_upload/publikationen/Mapping_AI_in_Public_Sector_new.pdf | Communication | Natural language processing | virtual assistant | 24/08/2023 | ||||||||||||||||
| PSTW-1347 | Urban Cockpit - a digital twin of Bad Hersfeld | https://badhersfeld.urbanpulse.de/#!/tiles/ | The municipality Bad Hersfeld built a digital twin using a multiple variety of open sourced data and is publicly showing them in the so called Urban Cockpit. Citizens can gather information about parking, the current status of waste bins and where to find a station for e-cars. | Local | Germany | DE73 | Municipality of Bad Hersfeld | Local Government | General public services | General public services n.e.c. | Implemented | 2.020 | Public services and engagement | Service integration (various) | No | No | Artificial Intelligence | G2C | x | x | x | x | x | https://www.koinno-bmwk.de/fileadmin/user_upload/publikationen/Mapping_AI_in_Public_Sector_new.pdf | Learning | Knowledge representation | 25/08/2023 | ||||||||||||||||||
| PSTW-1348 | Traffic flux representation with AI in Lisbon | https://www.koinno-bmwk.de/fileadmin/user_upload/publikationen/Mapping_AI_in_Public_Sector_new.pdf | The City Hall of Lisbon has partnered with the National Civil Engineering Laboratory (LNEC) and an academic partner, Instituto Superior Técnico, to put in place AI systems to gather, treat, classify and use urban mobility and situational context data, in order to map out and manage traffic flux can in an integrated way. | National | Portugal | PT17 | City Hall of Lisbon | Local Government | Public order and safety | Police Services | Implemented | 2.019 | Analysis, monitoring and regulatory research | Information analysis processes | No | No | Artificial Intelligence | G2G | x | x | https://www.koinno-bmwk.de/fileadmin/user_upload/publikationen/Mapping_AI_in_Public_Sector_new.pdf | Learning | Machine learning | data analytics | 25/08/2023 | ||||||||||||||||||||
| PSTW-1349 | Baggage handling at the Copenhagen Airport | https://www.netcompany.com/pl/Case-studies/CPH-Airports | Since 2016, Copenhagen Airport has been using artificial intelligence to optimise baggage handling. Artificial Intelligence is used to predict where staff can probably best empty aircraft and put cases on conveyor belts, focusing on time optimisation to improve passenger experience and shorten queues. | National | Denmark | DK | Copenhagen Airport | Central-Government | Economic Affairs | Transport | Implemented | 2.019 | Internal management | Internal primary processes | No | No | Artificial Intelligence | G2G | x | x | x | x | https://www.koinno-bmwk.de/fileadmin/user_upload/publikationen/Mapping_AI_in_Public_Sector_new.pdf | Learning | Optimisation | Machine learning | bayesian optimisation | 25/08/2023 | |||||||||||||||||
| PSTW-135 | Plausibility check on quality and reliability of administrative data | https://www.experimental.bfs.admin.ch/expstat/en/home/projects/plausi.html | Statistical offices carry out data validation to check the quality and reliability of administrative data and survey data. Data that are either clearly incorrect or seem at least questionable are sent back to data suppliers with a correction request or comment. Until now, such data validation have mainly been carried out at two different levels: either through manual checks or automated processes using threshold values and logical tests. This process of two-way plausibility checks involves a great deal of work. In some cases, staff are required to manually check the data again, in other cases rules are applied that often require additional checks. This rule-based approach has developed from previous experience but is not necessarily exhaustive and always precise. Machine learning could help to ensure faster and more accurate checks. This approach would rely on an algorithm using historical data at first. Based on a previous data analysis, a target variable can be defined that should be able to be predicted by the algorithm. Only then can the algorithm be used for the prediction. As the final stage, the predicted and actual values of the target variables are compared and the predictive accuracy can be evaluated. Finally, a feedback mechanism is also used to send an automatic explanation to data suppliers. | National | Switzerland | CH | Federal Office for Statistics | Central-Government | General public services | Executive and legislative organs, financial and fiscal affairs, external affairs. | Pilot | 2.019 | Internal management | Internal primary processes | No | No | Artificial Intelligence | G2G | x | x | x | x | https://www.experimental.bfs.admin.ch/expstat/en/home/projects/plausi.html | Learning | Machine learning | 09/11/2023 | |||||||||||||||||||
| PSTW-1351 | Fietsbarometer - barometer for cycleways safety | https://fietsbarometer.provincieantwerpen.be/geoloketten/?viewer=fietsbarometer | This is a project that involves adolescents who digitize and assess their daily home-to-school routes in different school neighborhoods in Flanders (Belgium). Through a web-based platform, called the “Bike Barometer” (“Fietsbarometer” in Dutch) the participants have the potential to offer detailed spatial insights about the local safety conditions in Flanders and in specific school neighborhoods. The example reported here is the Barometer of the Province of Antwerp. | Regional | Belgium | BE2 | Government of Flanders - Ghent University | Regional Government | Public order and safety | Police Services | Implemented | 2.022 | Public services and engagement | Service integration (various) | No | No | Artificial Intelligence | G2C | x | x | x | x | x | x | https://mbrcgi.gov.ae/programs/mbrcgi-and-oecd-partnership/ | Learning | Machine learning | data analytics | 25/08/2023 | ||||||||||||||||
| PSTW-1352 | Jelbi - the mobility app for Berlin's public and sharing services | https://www.jelbi.de/en/home/ | The Jelbi project links BVG (Berlin Transport Authority) services in Berlin with other mobility providers. At various points in Berlin, vehicles based on the sharing principle, such as scooters, bicycles, cars or scooters, are available to customers. These offers can be seen, rented and paid for via the free Jelbi app. In this way, an individually suitable combination of means of transport can be found for every route through the city - whether by train, bus, e-scooter, rental bike or car. | Local | Germany | DE30 | Berlin Public Transport Authority | Local Government | Economic Affairs | Transport | Implemented | 2.021 | Public services and engagement | Service integration (various) | No | No | Artificial Intelligence | G2C | x | x | x | x | x | https://mbrcgi.gov.ae/programs/mbrcgi-and-oecd-partnership/ | Planning | Planning and Scheduling | Optimisation | platform as a service | 25/08/2023 | ||||||||||||||||
| PSTW-1357 | Chatbot - German Federal Employment Agency | https://www.arbeitsagentur.de/ | The chatbot of the Federal Employment Agency answers general questions on many topics, including unemployment benefits, short-time allowance, child supplement, child support and training & studies. | National | Germany | DE | Federal Employment Agency | Central-Government | Social protection | Unemployment. | Implemented | 2.023 | Public services and engagement | Service personalisation (various) | No | No | Artificial Intelligence | G2C | x | x | x | x | x | x | https://www.arbeitsagentur.de/ | Communication | Natural language processing | AI Services | chatbot | 28/08/2023 | |||||||||||||||
| PSTW-1358 | Chatbot Guido | https://service.wirtschaft.nrw/ | Chatbot Guido answers questions related to online business registration procedures. | Regional | Germany | DEA | State Government of North Rhine-Westphalia | Regional Government | Economic Affairs | General economic, commercial and labour affair | Implemented | 2.023 | Public services and engagement | Service personalisation (various) | No | No | Artificial Intelligence | G2B | x | x | x | x | x | x | https://service.wirtschaft.nrw/top-10/gewerbe-anmelden | Communication | Natural language processing | AI Services | chatbot | 28/08/2023 | |||||||||||||||
| PSTW-1359 | Digitale Assistenz Ina | https://www.schleswig-holstein.de/DE/landesregierung/ministerien-behoerden/IAMT/Projekte/teilhabe_Chatbot_Fachinhalt.html | Chatbot Ina answers to general enquiries related to the Integration Office (e.g., disability). | Regional | Germany | DEF0 | Integration Office of the State Government of Schleswig-Holstein | Regional Government | General public services | General public services n.e.c. | Implemented | 2.023 | Public services and engagement | Service personalisation (various) | No | No | Artificial Intelligence | G2C | x | x | x | x | x | x | https://www.schleswig-holstein.de/DE/landesregierung/ministerien-behoerden/IAMT/Projekte/teilhabe_Chatbot_Fachinhalt.html | Communication | Natural language processing | AI Services | chatbot | 28/08/2023 | |||||||||||||||
| PSTW-136 | NOGAuto - Assign or control codes to companies for economic activities | https://www.experimental.bfs.admin.ch/expstat/en/home/projects/nogauto.html | The General Classification of Economic Activities (NOGA) is an essential element for the FSO’s statistical production. The quality of the NOGA coding of the enterprises registered in the Business and Enterprise Register (BER) has a direct impact on the results of the structural, economic and synthetic statistics that concern enterprises. These depend on stable, monitored and quality NOGA coding of the BER units. With a view to reducing the burden on enterprises and continuously improving the coding of enterprises, the project aims to automate the allocation of economic activity codes to enterprises. In an initial phase, this will be based on information that is already available within the FSO. Staff who are responsible for NOGA coding allocate or controll an enterprise’s economic activity code using the information that is available (survey input, economic activity description from the commercial register, etc.). This is inevitably associated with a human and subjective interpretation of information available which makes standardised coding difficult. | National | Switzerland | CH | Federal Office for Statistics | Central-Government | Economic Affairs | R&D economic affairs | Pilot | 2.021 | Internal management | Internal primary processes | No | No | Artificial Intelligence | G2B | x | x | x | https://www.experimental.bfs.admin.ch/expstat/en/home/projects/nogauto.html | Learning | Machine learning | Automated reasoning | 09/11/2023 | |||||||||||||||||||
| PSTW-1360 | TWIN4ROAD@Essen: AI-based analysis and forecast | https://www.bable-smartcities.eu/explore/use-cases/use-case/predicting-potholes-with-the-project-twin4road-in-essen.html | The German road network has a length of over 830,000 kilometres. The management and maintenance of the road network pose fundamental challenges to the economy, the state and society. The collection of area-wide and constantly updated data on road condition and road space inventory as well as their evaluations and change analyses is the central problem of road authorities due to the enormous amount of data and the lack of procedures for automated evaluation. These data enable the creation of digital twins for reliable and data-oriented decision-making as basis for road maintenance and investment planning as well as infrastructure monitoring. With the help of ground penetrating radar (GPR) technology, 3D data and image recordings, an extensive database on road infrastructure and the assessment of the road condition will be set up in the City of Essen. This includes mobile laserscanning measurements, extensive acquisition of road space imagery and continuous GPR-measurements. With the aid of AI, the data will be able to present robust and stable assessments on road damages, needs for renovation and potential future potholes solely by measurements and data analysis. Furthermore, this "digital twin" provides an inventory which can be accessed in context of most other sorts of municipal tasks in the public road space. | Local | Germany | DEA1 | City of Essen | Local Government | Economic Affairs | Transport | Pilot | 2.022 | Analysis, monitoring and regulatory research | Information analysis processes | No | No | Artificial Intelligence | G2G | x | x | https://www.bable-smartcities.eu/explore/use-cases/use-case/predicting-potholes-with-the-project-twin4road-in-essen.html | Perception | Computer vision | 28/08/2023 | |||||||||||||||||||||
| PSTW-1361 | KI4Forst - Monitoring the Forest with Satellite Data and AI | https://www.schleswig-holstein.de/DE/landesregierung/themen/digitalisierung/kuenstliche-intelligenz/KI_Strategie/_documents/ki__ai_strategy_download.pdf?__blob=publicationFile&v=1 | Through the development of an automated process chain, the project KI4Forst of the Schleswig-Holstein State Office for Surveying and Geoinformation (LVermGeo SH) is supposed to be able to detect forest areas and changes to them using deep learning techniques and present them on maps. Using the evaluations of the satellite data, it should then be possible to localize and assess the vegetation state and any damage (for example, as a result of drought or bark beetle infestations), as well as take targeted measures. An image classification algorithm will be developed and implemented in an automatic process chain for processing satellite data. The trained artificial neural network (ANN) will be able to automatically recognize forest in new data and differentiate between deciduous and conifer forests. | Regional | Germany | DEF0 | State Government of Schleswig-Holstein | Regional Government | Environmental Protection | R&D environmental protection. | Pilot | 2.022 | Analysis, monitoring and regulatory research | Information analysis processes | No | No | Artificial Intelligence | G2G | x | x | https://www.schleswig-holstein.de/DE/landesregierung/themen/digitalisierung/kuenstliche-intelligenz/KI_Strategie/_documents/ki__ai_strategy_download.pdf?__blob=publicationFile&v=1 | Perception | Computer vision | Machine learning | Deep learning | satellite images | 29/08/2023 | ||||||||||||||||||
| PSTW-1367 | Starting up smoothly: chatbot service (Virtual Agent Network) for foreign entrepreneurs in Finland | http://startingupsmoothly.fi/ | Three key agencies within the Finnish government - the Immigration Service, the Patent and Registration Office and the Tax Administration - partnered with Accenture Finland and boost.ai to develop a unique implementation of conversational AI that can easily facilitate inter-agency seamless collaboration. This innovation, called a Virtual Agent Network, helps to break down departmental silos by connecting three independent conversational AI-powered virtual agents (Kamu, PatRek, VeroBot) together via one single network. Visitors to any of the agencies’ websites can interact with their respective virtual agents individually to find answers to their questions related to immigration, business registration and patents, and taxation. When a user asks one virtual agent about a topic that is best answered by either of its digital colleagues, the virtual agent identifies that the topic is outside of its scope using Natural Language Understanding (NLU), and offers to transfer the user to the correct department. If accepted, the new virtual agent takes over within the same chat window for a seamless interaction. | National | Finland | FI | Immigration Service, Patent and Registration Office and the Tax Administration | Central-Government | General public services | General public services n.e.c. | In development | 2.018 | 2020 | Public services and engagement | Service integration (various) | No | No | Artificial Intelligence | G2B | x | x | x | https://www.accenture.com/bg-en/case-studies/public-service/ai-powered-virtual-agent-network | Communication | Natural language processing | AI Services | chatbot | 30/08/2023 | |||||||||||||||||
| PSTW-1368 | 120 Words per Minute - a Training App for Basal Automated Reading | https://www.schleswig-holstein.de/DE/landesregierung/themen/digitalisierung/kuenstliche-intelligenz/KI_Strategie/_documents/ki__ai_strategy_download.pdf?__blob=publicationFile&v=1 | Studies for recording pupils’ basic skills demonstrate that their reading skills are continually deteriorating. The purpose of the project “120 Words per Minute” is to address this societal problem. 120 words per minute is the target speed children should have reached by the end of the fourth grade. However, around 20 – 30 percent of pupils remain considerably below 100 words per minute and often do not improve this rate later on during school. An app is going to be developed that maps all phases of the program “Lesen macht stark” (“Reading makes you strong”) – training for the 1st and 2nd grades that is used in printed form in over 100 schools in Schleswig-Holstein. In particular, it will make the level check the children use to verify their reading skills superfluous using an AI algorithm– speech to text. The children will be able to practice in tandem or alone. Teachers can use the app continuously during education starting with the first training sequence. It is expected that using the app will promote both reading fluency and the implementation of a material-supported diagnostic and support program at school when children learn to read. | Regional | Germany | DEF0 | State Government of Schleswig-Holstein | Regional Government | Education | Pre-primary and primary education. | In development | 2.021 | Public services and engagement | Service integration (various) | No | No | Artificial Intelligence | G2C | x | x | x | x | x | https://www.schleswig-holstein.de/DE/landesregierung/themen/digitalisierung/kuenstliche-intelligenz/KI_Strategie/_documents/ki__ai_strategy_download.pdf?__blob=publicationFile&v=1 | Communication | Natural language processing | 30/08/2023 | ||||||||||||||||||
| PSTW-1369 | KI4GeoSeDa – AI-Based Georeferencing of Specialist Data Pools for Semantic Data Integration | https://www.schleswig-holstein.de/DE/landesregierung/themen/digitalisierung/kuenstliche-intelligenz/KI_Strategie/_documents/ki__ai_strategy_download.pdf?__blob=publicationFile&v=1 | In the scope of the project KI4GeoSeDa, together with Karslruhe Institute of Technology (KIT) as the project partner, algorithms are being developed that operationally evaluate address data and other natural linguistic spatial references using AI methods. The goal of this process is to enable georeferencing of specialist databases and then semantically integrate them into the spatial base data pool of the State Office for Surveying and Geo-Information. | Regional | Germany | DEF0 | Schleswig-Holstein State Office for Surveying and Geo-Information | Regional Government | General public services | General services. | Pilot | 2.021 | Analysis, monitoring and regulatory research | Information analysis processes | No | No | Artificial Intelligence | G2G | x | x | https://www.schleswig-holstein.de/DE/landesregierung/themen/digitalisierung/kuenstliche-intelligenz/KI_Strategie/_documents/ki__ai_strategy_download.pdf?__blob=publicationFile&v=1 | Learning | Machine learning | Natural language processing | Deep learning | 30/08/2023 | |||||||||||||||||||
| PSTW-137 | Chatbot - Offer residents and tourism information and services from the administration | https://www.stadt.sg.ch/home/verwaltung-politik/verwaltung-dienste/chatbot.html | Using a prototype, the city of St.Gallen tested the potential and acceptance of a chatbot in order to offer residents and tourism better access to information and services from the administration. By the end of 2018, various topics had been mapped in the chatbot. This includes the event calendar, information on parking spaces, the query of mobility information, the use of eUmzugCH, the query of information on disposal and the input of feedback to the programmers. The implementation in its own software environment, more extensive dialog options, the connection to the residence confirmation, the debt enforcement register extract and the extension of the deadline in the area of taxes will take place in 2019. Linked to this is the public test of the chatbot and subsequently a revision based on the knowledge gained from the public test. The bot is integrated in the urban app (mobileSG) and on the city's website. | Local | Switzerland | CH | Municipality of St.Gallen | Local Government | General public services | Executive and legislative organs, financial and fiscal affairs, external affairs. | Implemented | 2.021 | Public services and engagement | Engagement management | No | No | Artificial Intelligence | G2C | x | x | x | x | https://www.egovernment.ch/de/dokumentation/webpublikation/projekte/leistungen-fur-die-bevolkerung/chatbot-fur-die-offentliche-verwaltung/ | Communication | Natural language processing | Searching | chatbot | 09/11/2023 | |||||||||||||||||
| PSTW-1370 | AI-Supported unmanned aeriasl vehicles (UAVs) for Ecological Agriculture and Forestry | https://www.schleswig-holstein.de/DE/landesregierung/themen/digitalisierung/kuenstliche-intelligenz/KI_Strategie/_documents/ki__ai_strategy_download.pdf?__blob=publicationFile&v=1 | The goal of this project is to examine the transferability of the PC-based AI weed regulation system developed at the Westküste University of Applied Sciences to a “light” low-power embedded AI system and mount it on a drone. The project will also investigate whether it is possible to use the AI algorithms developed for forestry as well. | National | Germany | DEF0 | Westküste University of Applied Sciences | Central-Government | Environmental Protection | Environmental protection n.e.c. | Pilot | 2.021 | Internal management | Internal primary processes | No | No | Artificial Intelligence | G2G | x | x | https://www.schleswig-holstein.de/DE/landesregierung/themen/digitalisierung/kuenstliche-intelligenz/KI_Strategie/_documents/ki__ai_strategy_download.pdf?__blob=publicationFile&v=2 | Integration and Interaction | Robotics and Automation | unmanned vehicle | 30/08/2023 | ||||||||||||||||||||
| PSTW-1372 | Autonomous Fawn Tracking System - AROS | https://enterprise-insights.dji.com/user-stories/wildlife-protection-drones-save-baby-deer | Efforts to protect fawns from machines involve challenges like limited time and resources. nAIture GmbH & Co. KG, funded by the State Government of Scleswig-Holstein, aims to develop an AI-powered drone solution for detecting fawns hiding in agricultural fields. The drone autonomously scans fields using various sensors for hidden deer at any time of day or weather. When a fawn is detected, it sends GPS coordinates and an aerial view to a hunter and farmer for timely rescue. This innovation ultimately aims to efficiently address the issue of fawn protection. | Regional | Germany | DEF0 | State Government of Schleswig-Holstein | Central-Government | Environmental Protection | Environmental protection n.e.c. | In development | 2.021 | Enforcement | Smart Recognition processes | No | No | Artificial Intelligence | G2B | x | x | https://www.schleswig-holstein.de/DE/landesregierung/themen/digitalisierung/kuenstliche-intelligenz/KI_Strategie/_documents/ki__ai_strategy_download.pdf?__blob=publicationFile&v=1 | Perception | Computer vision | unmanned vehicle | 01/09/2023 | ||||||||||||||||||||
| PSTW-1373 | “Demenzwegweiser-SH” (Schleswig-Holstein Guide to Dementia) | https://demenzwegweiser-sh.de/ | “Demenzwegweiser-SH” (Schleswig-Holstein Guide to Dementia) is a database that is updated using only artificial intelligence. The guide to dementia provides information about the disease and regional counseling centers, specialist doctors, forms of living and care, and all further offerings. Additionally, it provides concise information on nursing care insurance, legal support, selected therapies without the use of medication, and general information on the topic of dementia. | Regional | Germany | DEF0 | Ministry of Social Affairs, Youth, Family, Senior Citizens, Integration and Equality of Schleswig-Holstein | Regional Government | Health | Public health services. | Implemented | 2.021 | Public services and engagement | Service personalisation (various) | No | No | Artificial Intelligence | G2C | x | x | x | x | x | https://www.schleswig-holstein.de/DE/landesregierung/themen/digitalisierung/kuenstliche-intelligenz/KI_Strategie/_documents/ki__ai_strategy_download.pdf?__blob=publicationFile&v=1 | Learning | Machine learning | recommender system | 01/09/2023 | |||||||||||||||||
| PSTW-1377 | Talbotti - Helsinki's financial management service chatbot | https://ai.hel.fi/en/talbotti-en/ | Talbotti is an electronic contact channel introduced by the City of Helsinki’s financial management service. The purpose of Talbot is to improve and increase customer contact opportunities, also outside customer service hours. Chatbot answers questions around the clock and offers, within the opening hours, the possibility to transfer to live chat to continue the conversation with a customer advisor. The new contact channel enables self service for customers and also advises, provides up to date information, links to websites and speeds up the search for information for residents and city employees. The chatbot learns from the data collected in customer service and it can answer most common questions related to invoicing and financial management services. | Local | Finland | FI | City of Helsinki | Local Government | General public services | General public services n.e.c. | Implemented | 2.023 | Public services and engagement | Service personalisation (various) | No | No | Artificial Intelligence | G2C | x | x | x | x | x | x | https://ai.hel.fi/en/talbotti-en/ | Communication | Natural language processing | AI Services | chatbot | 10/04/2024 | |||||||||||||||
| PSTW-1378 | Sotebotti hester | https://www.hel.fi/fi/sosiaali-ja-terveyspalvelut/lasten-ja-perheiden-palvelut/aitiys-ja-lastenneuvolat | Sotebot Hester is a chatbot for social services, health care and rescue services division. | Local | Finland | FI1B | City of Helsinki | Local Government | General public services | General public services n.e.c. | Implemented | 2.023 | Public services and engagement | Service personalisation (various) | No | No | Artificial Intelligence | G2C | x | x | x | x | x | x | https://ai.hel.fi/en/sotebotti-hester-en/ | Communication | Natural language processing | AI Services | chatbot | 05/09/2023 | |||||||||||||||
| PSTW-138 | Maxi - Chatbot answering questions on insurance | https://www.sva-ag.ch/pv | The Social Insurance Aargau SVA has introduced the Maxi Chatbot in order to reduce the number of questions received daily. The chatbot can answer general questions without sensitive data content. In the future, all further emails should run through automated and intelligent (learning) triage and further processing. To do this, requests with personal data must be correctly triaged by the chatbot and, depending on the type of request, directly trigger a process on the specialist application. With the introduction of the "Maxi" chatbot, remedial measures were taken and mail inquiries reduced by around 30%. | Regional | Switzerland | CH | Social Insurance Institute of Canton of Aargau | Local Government | Social protection | Social protection n.e.c. | Implemented | 2.021 | Public services and engagement | Engagement management | No | No | Artificial Intelligence | G2C | x | x | x | x | https://www.srf.ch/news/kuenstliche-intelligenz-maxi-beantwortet-fragen-zur-praemienverbilligung-im-aargau | Communication | Natural language processing | Searching | chatbot | 09/11/2023 | |||||||||||||||||
| PSTW-1385 | Chatbot - Municipality of Senigallia | https://www.comune.senigallia.an.it/lintelligenza-artificiale-al-servizio-del-cittadino-di-senigallia/ | This chatbot was introduced on the official website of the Municipality of Senigallia to answer general enquiries from citizens. | Local | Italy | ITI3 | Municipality of Senigallia | Local Government | General public services | General public services n.e.c. | Implemented | 2.022 | Public services and engagement | Service personalisation (various) | No | No | Artificial Intelligence | G2C | x | x | x | x | x | x | https://www.alghoncloud.com/soluzioni/public-administration/ | Communication | Natural language processing | AI Services | chatbot | 02/10/2023 | |||||||||||||||
| PSTW-1386 | Chatbot - Municipality of Treviso | https://www.comune.treviso.it/myportal/C_L407/home | This chatbot was introduced on the official website of the Municipality of Treviso to answer general enquiries from citizens. | Local | Italy | ITH3 | Municipality of Treviso | Local Government | General public services | General public services n.e.c. | Implemented | 2.021 | Public services and engagement | Service personalisation (various) | No | No | Artificial Intelligence | G2C | x | x | x | x | x | x | https://www.alghoncloud.com/soluzioni/public-administration/ | Communication | Natural language processing | AI Services | chatbot | 02/10/2023 | |||||||||||||||
| PSTW-1389 | Chatbot - Training, Guidance and Employment Agency Monza and Brianza | https://afolmonzabrianza.it/ | This chatbot was introduced on the official website of the Training, Guidance and Employment Agency of Monza and Brianza to answer general enquiries from citizens. | Local | Italy | ITC4 | Training, Guidance and Employment Agency Monza and Brianza | Local Government | Social protection | Unemployment. | Implemented | 2.023 | Public services and engagement | Service personalisation (various) | No | No | Artificial Intelligence | G2C | x | x | x | x | x | x | https://www.alghoncloud.com/soluzioni/public-administration/ | Communication | Natural language processing | AI Services | chatbot | 02/10/2023 | |||||||||||||||
| PSTW-139 | Chatbot - Security institution information, find the ones entitled to premium reductions | https://www.svasg.ch/news/meldungen/20190329_leader-award.php | In the Canton of St. Gallen, a Chatbot has been developed in the social security institution (SVA) organization to provide information for citizens about their services . | Regional | Switzerland | CH | Social Insurance Institute of St.Gallen | Local Government | Social protection | Social protection n.e.c. | Implemented | 2.019 | Public services and engagement | Engagement management | No | No | Artificial Intelligence | G2C | x | x | x | x | https://www.leaderdigital.ch/news/sva-will-chatbot-angebot-ausbauen-2718.html | Communication | Natural language processing | Searching | chatbot | 09/11/2023 | |||||||||||||||||
| PSTW-1390 | Chatbot - Chamber of Commerce of Reggio Emilia | https://www.re.camcom.gov.it/ | This chatbot was introduced on the official website of the Chamber of Commerce of Reggio Emilia to answer general enquiries from citizens and businesses. | Local | Italy | ITH5 | Chamber of Commerce of Reggio Emilia | Local Government | Economic Affairs | General economic, commercial and labour affair | Implemented | 2.023 | Public services and engagement | Service personalisation (various) | No | No | Artificial Intelligence | G2C | x | x | x | x | x | x | https://www.alghoncloud.com/soluzioni/public-administration/ | Communication | Natural language processing | AI Services | chatbot | 02/10/2023 | |||||||||||||||
| PSTW-1394 | AI for analysing investigative data in Austria | https://op.europa.eu/en/publication-detail/-/publication/4fb8e194-f634-11ea-991b-01aa75ed71a1/language-en | AI is used to conduct analysis, classification and extraction of metadata from any form of "data" as well as recognition of relationships and communication flows. This solution can detect semantic correlations among large amounts of data, extract automatically information from documents, trace information origins, visualise fraud patterns, without the need for custom coding. | National | Austria | AT | Federal Ministry of Justice | Central-Government | General public services | Executive and legislative organs, financial and fiscal affairs, external affairs. | Implemented | 2.018 | Enforcement | Supporting inspection processes | No | No | Artificial Intelligence | G2G | x | x | x | x | https://rm.coe.int/how-is-austria-approaching-ai-integration-into-judicial-policies-/16808e4d81 | Reasoning | Knowledge representation | Machine Learning | semantic web | 02/10/2023 | |||||||||||||||||
| PSTW-14 | Quickscan Organisaties | https://www.quickscanintegriteit.be/ | The Department of Culture, Youth and Media wants to use the project "innovative government procurement ", a tool" Quickscan Organizations "and associated develop underlying algorithm that makes it possible for the business automate the assessment and admissibility of grant applications, and the reduce time investment for the applicant and assessors | Regional | Belgium | BE | Departement Cultuur, Jeugd en Media (CJM) | Central-Government | General public services | Executive and legislative organs, financial and fiscal affairs, external affairs. | Pilot | 2.020 | Adjudication | Taking decisions on benefits | No | No | Artificial Intelligence | G2G | x | x | x | x | x | x | x | https://innovatieveoverheidsopdrachten.be/projecten/quickscan-organisaties | Reasoning | Automated reasoning | Searching | business assessment | 06/10/2023 | ||||||||||||||
| PSTW-1402 | Chatbot Skatti - Swedish Tax Agency | https://skatteverket.se/privat.4.76a43be412206334b89800052864.html | Chatbot answering general question on the official website of the Swedish Tax Agency. | National | Sweden | SE | Swedish Tax Agency | Central-Government | General public services | Executive and legislative organs, financial and fiscal affairs, external affairs. | Implemented | 2.023 | Public services and engagement | Service personalisation (various) | No | No | Artificial Intelligence | G2C | x | x | x | x | x | x | https://skatteverket.se/privat.4.76a43be412206334b89800052864.html | Communication | Natural language processing | AI Services | chatbot | 02/10/2023 | |||||||||||||||
| PSTW-143 | Amelia - Chatbot helping local residents find city services | https://www.intelligentcio.com/eu/2021/06/10/amelia-hired-by-centric-to-transform-citizen-services-with-conversational-ai/ | Robot Amelia uses Artificial Intelligence, machine-learning algorithms, and a natural language processor to help local residents find city services. | Local | United Kingdom | UK | London Borough of Enfield | Local Government | General public services | Executive and legislative organs, financial and fiscal affairs, external affairs. | In development | 2.021 | Public services and engagement | Engagement management | No | No | Artificial Intelligence | G2C | x | x | x | x | https://www.ukauthority.com/articles/enfield-joins-microsoft-in-citizenbot-project/ | Integration and Interaction | Robotics and Automation | Machine learning | Automated reasoning | personal assistant | 09/11/2023 | ||||||||||||||||
| PSTW-144 | Babylon - Health interactive symptom checker | https://www.babylonhealth.com/us/what-we-offer/chatbot | Babylon's interactive symptom checker asks you questions to analyse your condition. Babylon's AI system has been created by experienced doctors and scientists using the latest advances in deep-learning. Much more than a searchable database, it assesses known symptoms and risk factors to provide informed, up-to-date medical information. | National | United Kingdom | UK | National Health Service | Central-Government | Health | Medical products, appliances and equipment. | Implemented | 2.021 | Public services and engagement | Service personalisation (various) | No | No | Artificial Intelligence | G2C | x | x | x | https://www.babylonhealth.com/ | Reasoning | Automated reasoning | Knowledge representation | 09/11/2023 | |||||||||||||||||||
| PSTW-1447 | AI-based tool for monitoring cultivated land in Lithuania using Copernicus Sentinel data | https://eo4society.esa.int/2021/09/24/cultivated-sentinel-1-cap-monitoring-service-from-lithuania/ | Lithuania uses advanced technology to monitor the EU's Common Agricultural Policy (CAP) and distribute funds more efficiently. They partnered with Geomatrix UAB to develop a system (SAGRIS and CAPCON) that analyses satellite data with machine learning to assess farm activities and land use. This allows for quicker and more accurate checks on CAP subsidy claims during the farming season. After pilot testing during 2019-2020 farming seasons, the CAPCON service was successfully integrated with the information system of the National Paying Agency of Lithuania and a service contract is now in place. | National | Lithuania | LT | Lithuanian National Paying Agency (NPA) | Central-Government | General public services | Executive and legislative organs, financial and fiscal affairs, external affairs. | Implemented | 2.021 | Enforcement | Supporting inspection processes | No | No | Artificial Intelligence | G2G | x | x | x | x | x | https://eo4society.esa.int/2021/09/24/cultivated-sentinel-1-cap-monitoring-service-from-lithuania/ | Perception | Computer vision | Machine learning | image processing | 10/04/2024 | ||||||||||||||||
| PSTW-1448 | AI for analysing incoming mail | https://rm.coe.int/how-is-austria-approaching-ai-integration-into-judicial-policies-/16808e4d81 | Automated routing of all incoming documents (structured and unstructured, scanned and via ELC), without manual processing of the administration staff of the courts. Applications include: (1) Analysis of input documents and extraction of metadata (2) Identification of given identifiers (files for direct allocation) (3) Recognition of the procedure type of incoming documents without file number including intelligent allocation, creation of files and assignment (4) Categorization of scanned documents and (5 preparation of a proposal for document descriptions and names. | National | Austria | AT | Federal Ministry of Justice | Central-Government | General public services | Executive and legislative organs, financial and fiscal affairs, external affairs. | Implemented | 2.018 | Internal management | Internal support processes | No | No | Artificial Intelligence | G2G | x | x | x | https://rm.coe.int/how-is-austria-approaching-ai-integration-into-judicial-policies-/16808e4d81 | Learning | Machine learning | Optimisation | automatic classification | 02/10/2023 | ||||||||||||||||||
| PSTW-1449 | AI for digital file management | https://rm.coe.int/how-is-austria-approaching-ai-integration-into-judicial-policies-/16808e4d82 | For consistent file management, incoming unstructured documents should be processed uniformly and metadata should be adopted automatically. The intelligent digitization of existing paper files should also be supported. Areas of application include: (1) Detection of “first pages” of single documents after bulk scanning and separation of entries with supplements (2) Determination of description and classification as well as adoption and harmonization of document titles (3) Intelligent creation of the digital file structure (for scanned files) including table of contents and (4) Creation of object-orientied-views (f.e. documents of first party). | National | Austria | AT | Federal Ministry of Justice | Central-Government | General public services | Executive and legislative organs, financial and fiscal affairs, external affairs. | Implemented | 2.018 | Internal management | Internal support processes | No | No | Artificial Intelligence | G2G | x | x | x | https://rm.coe.int/how-is-austria-approaching-ai-integration-into-judicial-policies-/16808e4d81 | Learning | Machine learning | automatic classification | 02/10/2023 | |||||||||||||||||||
| PSTW-145 | TravelBot - Chatbot for travel information | https://tfl.gov.uk/info-for/media/press-releases/2017/june/tfl-launches-new-social-media-travelb | The new social media tool, which is powered by Artificial Intelligence, can "chat" with customers using Messenger and instantly tell them when their bus is due to arrive, provide service updates and Tube maps. The TravelBot can also link direct to a customer service agent, making customer service queries easier than ever. | Local | United Kingdom | UK | Transport for London | Local Government | Economic Affairs | General economic, commercial and labour affair | Implemented | 2.021 | Public services and engagement | Service personalisation (various) | No | No | Artificial Intelligence | G2C | x | x | x | x | https://tfl.gov.uk/info-for/media/press-releases/2017/june/tfl-launches-new-social-media-travelb | Communication | Natural language processing | Searching | chatbot | 09/11/2023 | |||||||||||||||||
| PSTW-1451 | Ion - the world's first government advisor | https://ion.gov.ro/ | Ion is a robot that was developed by Romanian researchers that will use artificial intelligence to "quickly and automatically capture the opinions and desires" submitted by Romanian citizens and express them to government functionaries. | National | Romania | RO | Government of Romania | Central-Government | General public services | General services. | Implemented | 2.023 | Analysis, monitoring and regulatory research | Innovating Public Policy | No | No | Artificial Intelligence | G2G | x | x | x | x | x | x | https://www.politico.eu/article/meet-the-first-ai-presidential-advisor-romanian-pm-says-nicolae-ciuca-nicu-sebe-kris-shrishak/ | Communication | Natural language processing | Multi AI techniques | sentiment analysis | 02/10/2023 | |||||||||||||||
| PSTW-1452 | Chatbot - LineaMadrid | https://www.madrid.es/portal/site/munimadrid | Chatbot on the official website of the Municipality of Madrid answering to general enquiries. | Local | Spain | ES30 | Municipality of Madrid | Local Government | General public services | General public services n.e.c. | Implemented | 2.023 | Public services and engagement | Service personalisation (various) | No | No | Artificial Intelligence | G2C | x | x | x | x | x | x | https://www.madrid.es/portal/site/munimadrid | Communication | Natural language processing | AI services | chatbot | 02/10/2023 | |||||||||||||||
| PSTW-1454 | Classification and automatic sorting of CEMs at the Italian National Institute for Social Security (INPS) | https://www.agendadigitale.eu/cittadinanza-digitale/inps-ecco-come-usiamo-lia-a-vantaggio-dei-cittadini/ | One of the most important channels by which citizens can communicate with INPS is via certified email (CE). On a practical level, when the INPS operator received the CE, he reads the text and any attachments, understands the subject matter (e.g., pensions, civil invalidity, redundancy payment), and then sorts it to the official in charge of answering the subject. At the beginning of 2021, INPS started experimenting with the Open Source version of GPT-2, and then moved on to BERT, another Machine Learning model that also leverages the Transformers architecture and was developed by Google. The entire system was developed and executed in-house in the INPS Data Centres, precisely to fully satisfy GDPR and confidentiality requirements related to the sensitivity of citizens' data. It has accelerated the process of citizen communication with the Institution, it is active in 10 Italian cities of varying size and geographic area, including Rome, Milan and Naples and it has currently processed more than 1 million CEs. When fully operational, counting all territorial offices, it is estimated that between 30,000 and 40,000 working days per year will be saved. INPS was awarded by IRCAI, UNESCO's International Research Centre for Artificial Intelligence, in the world Top 10 projects supporting the 17 UN Sustainable Development Goals (SDGs). | National | Italy | IT | National Institute for Social Security (INPS) | Central-Government | Social protection | Social protection n.e.c. | Implemented | 2.021 | Internal management | Internal primary processes | No | No | Artificial Intelligence | G2G | x | x | x | x | x | https://www.agendadigitale.eu/cittadinanza-digitale/inps-ecco-come-usiamo-lia-a-vantaggio-dei-cittadini/ | Learning | Machine learning | Generative AI | Optimisation | text classification | 02/10/2023 | |||||||||||||||
| PSTW-1455 | "INPS risponde" - Optimised management of web requests to Customer Service | https://servizi2.inps.it/servizi/AppWebCrm/ | One of the channels by which citizens can communicate with INPS is via the web with the "INPS Risponde" service, which receives more than 2.5 million communications annually. Today, on a practical level, each request is taken care of by a first level operator who in 43% of cases is able to handle and solve it autonomously, but in 57% of cases, given the complexity of the request, it requires further support from a second-level operator. These numbers show that 1.4 million requests (57% of 2.5 million) were handled twice, either by the first or second level, with an increase in response time for the citizen. INPS is currently testing an Artificial Intelligence decision engine upstream capable of assessing the complexity of citizen requests. | National | Italy | IT | National Institute for Social Security (INPS) | Central-Government | Social protection | Social protection n.e.c. | In development | 2.023 | Internal management | Internal primary processes | No | No | Artificial Intelligence | G2G | x | x | x | x | x | https://www.agendadigitale.eu/cittadinanza-digitale/inps-ecco-come-usiamo-lia-a-vantaggio-dei-cittadini/ | Learning | Machine learning | Optimisation | text classification | 02/10/2023 | ||||||||||||||||
| PSTW-1456 | Virtual Assistant based on generative AI at INPS | https://www.inps.it/it/it/inps-comunica/atti/circolari-messaggi-e-normativa/dettaglio.circolari-e-messaggi.2023.07.messaggio-numero-2659-del-14-07-2023_14221.html | INPS has recently launched an experiment with the objective to integrate within the INPS Virtual Assistant the same 'Large Language Model' (LLM) algorithm at the basis of ChatGPT, thanks to the collaboration of Microsoft Azure with OpenAI. The aim is to offer increasingly accurate answers to citizens of certain services such as the 'Opzione Donna' pension scheme and other services. | National | Italy | IT | National Institute for Social Security (INPS) | Central-Government | Social protection | Social protection n.e.c. | Implemented | 2.024 | Public services and engagement | Service personalisation (various) | No | No | Artificial Intelligence | G2C | x | x | x | x | x | x | https://www.agendadigitale.eu/cittadinanza-digitale/inps-ecco-come-usiamo-lia-a-vantaggio-dei-cittadini/ | Learning | Machine learning | Generative AI | Natural language processing | chatbot | 02/10/2023 | ||||||||||||||
| PSTW-1460 | London Electric Vehicle Charge Points Dashboard | https://loti.london/projects/ev-charge-points/ | Electric Vehicle (EV) charging infrastructure - a vital component of London’s smart and green agenda - is being delivered by a wide range of public and private bodies across London (up to 50). As a result of the project, we developed a dashboard to join up the EV Charging infrastructure in London to enable a collective understanding of what is already in place, how it is being used, and to guide future installations. | Local | United Kingdom | UKI | Greater London Authority | Local Government | General public services | General public services n.e.c. | Implemented | 2.020 | Public services and engagement | Service integration (various) | No | No | Artificial Intelligence | G2C | x | x | x | x | x | https://oecd-opsi.org/innovations/london-electric-vehicle-charge-points-dashboard/ | Services | AI Services | 02/10/2023 | ||||||||||||||||||
| PSTW-1463 | Use of Public Lighting System to Deploy a Comprehensive Smart City Platform | https://oecd-opsi.org/innovations/use-of-public-lighting-system-to-deploy-a-comprehensive-smart-city-platform/ | The City of Paris aims to reduce its public lighting energy consumption by 30% by 2020. Paris has made a smart city-ready lighting grid covering the entire city. This helps minimize its lighting system’s environmental impact and improve citizens’ public safety and user experience. It can be used to easily scale its service area to connect future smart services. | Local | France | FR10 | City of Paris | Local Government | Housing and community amenities | Street lighting. | Implemented | 2.018 | Analysis, monitoring and regulatory research | Innovating Public Policy | No | No | Artificial Intelligence | G2G | x | x | x | x | https://oecd-opsi.org/innovations/use-of-public-lighting-system-to-deploy-a-comprehensive-smart-city-platform/ | Planning | Planning and Scheduling | Optimisation | sensor network | 02/10/2023 | |||||||||||||||||
| PSTW-147 | Automatic posting of invoices - Robot to propose the correct posting | https://www.regjeringen.no/en/dokumenter/nasjonal-strategi-for-kunstig-intelligens/id2685594/?ch=6#id0043 | Customers of The Norwegian Government Agency for Financial Management (DFØ) spend considerable time and resources on posting incoming invoices due to uncertainty about the correct posting. In some cases this can lead to invoices being paid after the due date and can create extra costs for the agency in the form of interest and charges. DFØ is currently testing solutions from two companies, one of which involves an accounting robot that uses AI to propose the correct posting. The model is trained using historical data before making a prediction of the posting based on a combination of historical data and information obtained from the actual invoice. | National | Norway | NO | Norwegian Government Agency for Financial Management | Central-Government | General public services | Executive and legislative organs, financial and fiscal affairs, external affairs. | Implemented | 2.021 | Internal management | Internal support processes | No | No | Artificial Intelligence | G2C | x | x | x | https://www.regjeringen.no/en/dokumenter/nasjonal-strategi-for-kunstig-intelligens/id2685594/?ch=6#id0043 | Learning | Machine learning | Automated reasoning | 09/11/2023 | |||||||||||||||||||
| PSTW-1472 | Chatbot - Lad Va | https://www.lad.gov.lv/lv | Chatbot on the webpage of the Rural Support Service of the Republic of Latvia answering general enquiries. | National | Latvia | LV | Rural Support Service of the Republic of Latvia | Central-Government | Economic Affairs | Agriculture, forestry, fishing and hunting | Implemented | 2.023 | Public services and engagement | Service personalisation (various) | No | No | Artificial Intelligence | G2C | x | x | x | x | x | x | https://www.lad.gov.lv/en | Communication | Machine learning | AI services | chatbot | 02/10/2023 | |||||||||||||||
| PSTW-1474 | AI to increase the efficiency of fiscal audit at the Greek General Directorate of Financial Controls (GDDE) | https://innovation.gov.gr/innovationscat/financial-control-optimization-automation-system-with-data-utilization-and-risk-analysis/ | The main reasons for the creation of the innovation by the General Directorate of Financial Controls are (1) the impossibility of controlling all the General Government agencies on an annual basis, as a result of which there is no full fiscal control, (2) the need for a financial control database to automate the evaluation process, (3) the need to draw up targeted policies regarding the improvement of financial management for each institution separately, and (4) the detection of fraud and corruption phenomena, which may exist due to insufficient financial control. The innovation aims to resolve the main challenges faced by the General Directorate of Financial Controls in the exercise of its responsibilities. Specifically, the solution is expected (1) to increase the number of audits through the online application of fiscal assessment, so that they cover the greater part of the General Government bodies, within a fiscal year, (2) to automate the evaluation process thanks to the creation of the financial control database and (3) to savw at least 20% of the working time that employees currently spend on conducting checks. | National | Greece | EL | General Directorate of Financial Controls (GDDE) | Central-Government | General public services | Executive and legislative organs, financial and fiscal affairs, external affairs. | Implemented | 2.021 | Enforcement | Supporting inspection processes | No | No | Artificial Intelligence | G2G | x | x | x | x | https://innovation.gov.gr/innovationscat/financial-control-optimization-automation-system-with-data-utilization-and-risk-analysis/ | Reasoning | Automated reasoning | automatic classification | 02/10/2023 | ||||||||||||||||||
| PSTW-1476 | Municipality of Palaio Faliro: Development of IOT Platform - Energy Upgrade | https://palaiofaliro.gr/politis/exipiretisi-politi/diefthinsi-technikon-ip/katagrafi-katanalosis/ | The goal of this project is the development of a centralized IOT management platform with the ability to control, record and analyze power consumption data and other resources in buildings and other infrastructures of the Municipality of Palaio Faliro. The IoT platform (SenseOne IoT) can become a universal system, oriented towards the central monitoring and management of its energy behavior by controlling the Municipality's energy footprint in its building infrastructures (e.g. Municipal buildings, School facilities, Sports facilities, street lighting, etc.) as well as in any other infrastructure it has, from which it could collect reliable data (garbage bins, parking spaces, meters of environmental indicators, natural gas, smart meters for monitoring water consumption and tanks, smart sensors for wells and waste, electric chargers for electric cars, etc.). | Local | Greece | EL30 | Municipality of Palaio Faliro | Local Government | Economic Affairs | General economic, commercial and labour affair | Pilot | 2.021 | Analysis, monitoring and regulatory research | Prediction and planning | No | No | Artificial Intelligence | G2G | x | x | x | OPSI Database | Planning | Optimisation | internet of things | 02/10/2023 | |||||||||||||||||||
| PSTW-1477 | Chatbot Poseidon - Municipality of Palaio Faliro | https://palaiofaliro.gr/ | Chatbot on the official website of the Municipality of Palaio Faliro. | Local | Greece | EL30 | Municipality of Palaio Faliro | Local Government | General public services | General public services n.e.c. | Implemented | 2.023 | Public services and engagement | Service personalisation (various) | No | No | Artificial Intelligence | G2C | x | x | x | x | x | x | OPSI Database | Communication | Natural language processing | chatbot | 02/10/2023 | ||||||||||||||||
| PSTW-1482 | Crowdsorsa - City of Helsinki | https://crowdsorsa.com/services/ | Crowdsorsa is a mobile App that collects data on the infrastructure sector (public infrastructure, roads, energy and water infrastructure) by using gamification approaches. Through the App Inventories and condition surveys of any kind of physical assets can now be carried out in only a matter of hours. Moreover, citizens can earn money by participating in the data collection missions co-organized by Crowdsorsa and its contracting partners (i.e. the city of Helsinki). The game is played by collecting and placing virtual objects on the map while taking gps-tagged photos or videos with your smartphone. Supplied with AI and asset management analysis, it is expected that participants (i.e. citizens) go around their cities or around a specific pre-determined area, map them according to a set of rules, take pictures/photos and upload them to then be evaluated by the AI and asset management platform. | Local | Finland | FI1B | City of Helsinki | Local Government | Housing and community amenities | Community development. | Implemented | 2.023 | Public services and engagement | Service personalisation (various) | No | No | Artificial Intelligence | G2C | x | x | x | x | x | x | x | https://www.hel.fi/en/news/helsinki-surveys-cycle-path-condition-through-mobile-game | Services | AI Services | platform as a service | 02/10/2023 | |||||||||||||||
| PSTW-1485 | Chatbot - austrian Federal Ministry of Justice | https://justizonline.gv.at/jop/web/home | Chatbot on the official webpage of the austrian Federal Mnistry of Justice. | National | Austria | AT | Fedeal Ministry of Justice | Central-Government | Public order and safety | Law courts | Implemented | 2.023 | Public services and engagement | Service personalisation (various) | No | No | Artificial Intelligence | G2C | x | x | x | x | x | x | https://op.europa.eu/en/publication-detail/-/publication/4fb8e194-f634-11ea-991b-01aa75ed71a1/language-en | Communication | Natural language processing | AI services | chatbot | 02/10/2023 | |||||||||||||||
| PSTW-1488 | AI for anonymisation of court decisions in Croatia | https://www.coe.int/en/web/national-implementation/by-default-optimisation-of-efficiency-and-quality-of-judicial-services-and-transparency-of-judicial | This project for anonymisation is in the proof of concept phase, and currently negotiations are ongoing with a vendor.The tool would be used for the anonymisation of court documents before their publication. | National | Croatia | HR | Ministry of Justice | Central-Government | Public order and safety | Law courts | In development | 2.024 | Internal management | Internal support processes | No | No | Artificial Intelligence | G2G | x | x | x | https://op.europa.eu/en/publication-detail/-/publication/4fb8e194-f634-11ea-991b-01aa75ed71a1/language-en | Reasoning | Automated reasoning | Natural language processing | automatic classification | 02/10/2023 | ||||||||||||||||||
| PSTW-1489 | Judicial Anonymisation Tool | https://op.europa.eu/en/publication-detail/-/publication/4fb8e194-f634-11ea-991b-01aa75ed71a1/language-en | This project also enables the anonymisation of a large range of decisions by public courts before their publication. The aim is to automate the manual anonymisation of court decisions before publication in view of making them compliant with personal data protection laws. In terms of technology, the solution is based on Expert systems and rule-based systems and Natural Language Processing. | National | Czechia | CZ | Ministry of Justice | Central-Government | Public order and safety | Law courts | In development | 2.021 | Internal management | Internal support processes | No | No | Artificial Intelligence | G2G | x | x | x | https://op.europa.eu/en/publication-detail/-/publication/4fb8e194-f634-11ea-991b-01aa75ed71a1/language-en | Reasoning | Automated reasoning | Natural language processing | automatic classification | 02/10/2023 | ||||||||||||||||||
| PSTW-149 | ARC-D - Automatic Road Condition Detection | https://www.oeffentliche-it.de/documents/10181/14412/KI+im+Beh%C3%B6rdeneinsatz+-+Erfahrungen+und+Empfehlungen | Currently there is no automated collection of condition data for all federal motorways. An up-to-date database and an automated assessment of the quality of individual stretches of motorway would be important, e.g. in order to initiate suitable maintenance measures at an early stage and thus prevent cost-intensive long-term damage. A system is being developed, on the basis of image data previously classified by experts, that enables video data to be (partially) (partially) automated evaluation of video data in order to classify roads in terms of their condition. In the long term, other sensor data will also be incorporated. | National | Germany | DE | BMVI, Autobahn GmbH of the Federal Government | Central-Government | Economic Affairs | Transport | Pilot | 2.019 | 2020 | Enforcement | Smart Recognition processes | No | No | Artificial Intelligence | G2C | x | x | x | KI im Behördeneinsatz: Erfahrungen und Empfehlungen https://www.oeffentliche-it.de/documents/10181/14412/KI+im+Beh%C3%B6rdeneinsatz+-+Erfahrungen+und+Empfehlungen | Perception | Computer vision | Machine learning | 09/11/2023 | ||||||||||||||||||
| PSTW-1490 | AI to anonymise judicial courts in Denmark | https://op.europa.eu/en/publication-detail/-/publication/4fb8e194-f634-11ea-991b-01aa75ed71a1/language-en | This project pseudonymises Danish courts' judgments in order to be able to publish them in a move to ensure the transparency of court judgments. In terms of technology, the solution is based on machine learning. Each judgment is pseudonymised and controlled by two human participants. Beforehand, the dataset is pre-screened by the software to identify names, pronouns, phrases and connotations that are problematic in a privacy context. | National | Denmark | DK | Court administration (Domstolsstyrelsen) | Central-Government | Public order and safety | Law courts | In development | 2.020 | Internal management | Internal support processes | No | No | Artificial Intelligence | G2G | x | x | x | https://op.europa.eu/en/publication-detail/-/publication/4fb8e194-f634-11ea-991b-01aa75ed71a1/language-en | Reasoning | Automated reasoning | Natural language processing | automatic classification | 11/09/2023 | ||||||||||||||||||
| PSTW-1493 | Automatic anonymisation and content description of documents containing personal data | https://oikeusministerio.fi/en/project?tunnus=OM042:00/2018 | The Anoppi project led by the Ministry of Justice will implement two language technology-based artificial intelligence tools for automatic anonymisation and content description of court decisions and other official decisions issued by authorities. With the assistance of the new applications, the electronic availability of documents can be improved, for example for the purposes of decision-making and research. | National | Finland | FI | Ministry of Justice | Central-Government | Public order and safety | Law courts | Pilot | 2.018 | 2020 | Internal management | Internal support processes | No | No | Artificial Intelligence | G2G | x | x | x | https://op.europa.eu/en/publication-detail/-/publication/4fb8e194-f634-11ea-991b-01aa75ed71a1/language-en | Reasoning | Automated reasoning | Natural Language processing | automatic classification | 11/09/2023 | |||||||||||||||||
| PSTW-1494 | Robot process automation (RPA) in Finnish judicial system | https://op.europa.eu/en/publication-detail/-/publication/4fb8e194-f634-11ea-991b-01aa75ed71a1/language-en | The RPA project is currently used in the area of enforcement of fines with several objectives: (1) to make enquiries via email to banks and the Finnish Population Centre; (2) to go through data and spot cases of erroneous overpayment in order to facilitate the return of the payment to the citizen; and (3) to allocate overpayments (300-700 cases every year). | National | Finland | FI | Ministry of Justice | Central-Government | Public order and safety | Law courts | Implemented | 2.020 | Internal management | Internal support processes | No | No | Artificial Intelligence | G2G | x | x | x | https://op.europa.eu/en/publication-detail/-/publication/4fb8e194-f634-11ea-991b-01aa75ed71a1/language-en | Reasoning | Automated reasoning | automated machine learning | 11/09/2023 | |||||||||||||||||||
| PSTW-1495 | DataJust | https://www.justice.fr/donnees-personnelles/datajust | The Ministry of Justice processes your personal data, called “DataJust”, with the aim of developing an algorithm to be used to Carrying out retrospective and prospective evaluations of public policies in matters of civil or administrative liability; The development of an indicative framework for compensation for bodily injury; Information of the parties and assistance in evaluating the amount of compensation to which victims are entitled in order to promote an amicable settlement of disputes; Information or documentation for judges called upon to rule on claims for compensation for bodily injury. | National | France | FR | Ministry of Justice | Central-Government | Public order and safety | Law courts | Pilot | 2.019 | 2022 | Adjudication | Taking decisions on benefits | No | No | Artificial Intelligence | G2G | x | x | x | x | https://op.europa.eu/en/publication-detail/-/publication/4fb8e194-f634-11ea-991b-01aa75ed71a1/language-en | Learning | Machine learning | Optimisation | information extraction | 11/09/2023 | ||||||||||||||||
| PSTW-1496 | Land register analysis component in the project Development of a federal database land register | https://op.europa.eu/en/publication-detail/-/publication/4fb8e194-f634-11ea-991b-01aa75ed71a1/language-en | This project aims to automate the analysis of existing PDF files with land register information. Afterwards the tool will fragment the file and assign the values to a database field in order to be able to store the contents in a structured manner in a database. In terms of technology, the solution is based on Expert systems and rule-based systems. | National | Germany | DE | Commission for information technology in the judiciary | Central-Government | Public order and safety | Law courts | Pilot | 2.016 | 2020 | Internal management | Internal support processes | No | No | Artificial Intelligence | G2G | x | x | x | https://op.europa.eu/en/publication-detail/-/publication/4fb8e194-f634-11ea-991b-01aa75ed71a1/language-en | Reasoning | Automated reasoning | Optimisation | automatic classification | 11/09/2023 | |||||||||||||||||
| PSTW-1497 | Application of AI for early recognition of criminal offences that relate to hate crime | http://fra.europa.eu/en/promising-practices/application-ai-early-recognition-criminal-offences-relate-hate-crime | In this research project, the use of AI to detect, prevent and prosecute hate crime in police organisations is being investigated within a holistic framework. Analysis of the organisational, ethical and legal framework necessary for the adoption of AI by the police to effectively prevent and prosecute hate crime is being undertaken. This framework, combined with the analysis of the effects of online hate crime on society, is used to define the technical conditions that are necessary for employing AI to classify hate speech according to: the criminal code the phenomena of hate speech the topics of hate speech. The aim of the project is to produce a number of reports that outline the necessary conditions to enable the police to adopt AI to counter hate crime, and investigate the necessary technical approach and potential solutions. The technical results will be demonstrated in a prototype that the police will evaluate. Together, these analyses can be used to implement AI as a supporting tool for the police to prevent, reduce and prosecute hate crime carried out on the internet. | National | Germany | DE | Federal Criminal Police Office (BKA) | Central-Government | Public order and safety | Police Services | Pilot | 2.020 | 2023 | Enforcement | Supporting inspection processes | No | No | Artificial Intelligence | G2G | x | x | x | x | https://op.europa.eu/en/publication-detail/-/publication/4fb8e194-f634-11ea-991b-01aa75ed71a1/language-en | Reasoning | Automated reasoning | text classification | 11/09/2023 | |||||||||||||||||
| PSTW-1498 | Future criminal court rooms | https://op.europa.eu/en/publication-detail/-/publication/4fb8e194-f634-11ea-991b-01aa75ed71a1/language-en | The aim is to create modern court rooms which allow videotaping and speech-totext recognition. All participants will receive a transcription and the audio file embedded. 3D-projection of crime scenes is under consideration. The project will result in reducing time and effort and will achieve overall modernisation of court rooms. | Regional | Germany | DE | Central Cybercrime of the Department of North-Rhine-Westphalia | Regional Government | Public order and safety | Law courts | Pilot | 2.020 | Analysis, monitoring and regulatory research | Innovating Public Policy | No | No | Artificial Intelligence | G2G | x | x | x | https://op.europa.eu/en/publication-detail/-/publication/4fb8e194-f634-11ea-991b-01aa75ed71a1/language-en | Integration and Interaction | Multiple AI techniques | 11/09/2023 | ||||||||||||||||||||
| PSTW-1499 | Speech recognition and transcription | https://op.europa.eu/en/publication-detail/-/publication/4fb8e194-f634-11ea-991b-01aa75ed71a1/language-en | The project explores the use of a speech recognition and transcription software in courts in order to facilitate and expedite the drafting of court decisions and minutes. It would result in reducing manual effort. | National | Hungary | HU | National Office for the Judiciary | Central-Government | Public order and safety | Law courts | In development | 2.018 | Internal management | Internal primary processes | No | No | Artificial Intelligence | G2G | x | x | x | https://op.europa.eu/en/publication-detail/-/publication/4fb8e194-f634-11ea-991b-01aa75ed71a1/language-en | Communication | Natural language processing | speech recognition | 11/09/2023 | |||||||||||||||||||
| PSTW-15 | Plovdic - City Concierge Chatbot | https://umni.bg/en/plovdiv-city-concierge-chatbot/ | City Concierge is an AI-powered city chatbot like a virtual Tourist Office in the mobile. It is there for the visitors 24/7 in Messenger and provides information about the city Point of Interests pf the city. It is possible for tourists and visitors to search information by category and location, or by keyword, or simply ask question about restaurants, entertainment, sightseeing, shopping, transportation and other | Local | Bulgaria | BG | UMNI | Local Government | General public services | Executive and legislative organs, financial and fiscal affairs, external affairs. | Implemented | 2.020 | Public services and engagement | Engagement management | No | No | Artificial Intelligence | G2C | x | x | x | x | x | https://umni.bg/en/plovdiv-city-concierge-chatbot/ | Communication | Natural language processing | Knowledge representation | chatbot | 06/10/2023 | ||||||||||||||||
| PSTW-150 | C-19 - Interdepartmental chatbot on the topic of Corona. | https://chatbot.it.bund.de/ | Since the beginning of the pandemic, the number of enquiries in the public services has increased by up to ten times. A chatbot automatically answers questions from citizens. In the process, existing FAQs are entered as building blocks for a dialogue. In the future, chatbots will have functions for creating applications and clarifying status. The AI components will used primarily for speech recognition, but also for processing the dialogues conducted. C-19 Chatbot provides pre-formulated answers and references to further sources of information. | National | Germany | DE | ITZBund | Central-Government | General public services | General public services n.e.c. | Implemented | 2.020 | Public services and engagement | Service personalisation (various) | No | No | Artificial Intelligence | G2G | x | x | x | KI im Behördeneinsatz: Erfahrungen und Empfehlungen https://www.oeffentliche-it.de/documents/10181/14412/KI+im+Beh%C3%B6rdeneinsatz+-+Erfahrungen+und+Empfehlungen | Communication | Natural language processing | Automated reasoning | chatbot | 09/11/2023 | ||||||||||||||||||
| PSTW-1505 | Just - virtual assistant of the State Unitary Computerized Land Book | https://www.zemesgramata.lv/ | At the end of 2019, the Court Administration introduced a virtual assistant into the Land Register portal. The assistant named Justs (from the word justīcija, ‘justice’) helps people find their way around the services offered by the Land Register. | National | Latvia | LV | Ministry of Justice | Central-Government | General public services | General public services n.e.c. | Implemented | 2.019 | Public services and engagement | Service personalisation (various) | No | No | Artificial Intelligence | G2C | x | x | x | x | x | x | https://op.europa.eu/en/publication-detail/-/publication/4fb8e194-f634-11ea-991b-01aa75ed71a1/language-en | Communication | Natural language processing | AI services | chatbot | 11/09/2023 | |||||||||||||||
| PSTW-1507 | LoRaWAN - The IoT network for Zurich | https://www.ewz.ch/en/business-customers/connectivity/iot-services/lorawan.html | EWZ has built up a comprehensive Long Ranage IoT network in Zurich. It uses the freely available LoRaWAN (long-range wide-area network) industry standard, which enables incredibly simple and cost-effective data transmission. The sensors connected in the network give insight into the operating states of different facilities and locations in a simple and cost-effective way, thus laying the foundation for efficient and cost-effective work. This platform can be tested free of charge by businesses that want to use the IoT network. | Local | Switzerland | CH | EWZ - Service Division of the Department of Public Utilities and Transport of the City of Zurich | Local Government | Economic Affairs | Transport | Implemented | 2.023 | Analysis, monitoring and regulatory research | Information analysis processes | No | Yes | Artificial Intelligence | G2B | x | x | x | https://www.ewz.ch/en/business-customers/connectivity/iot-services/lorawan.html | Reasoning | Knowledge representation | Planning and Scheduling | internet of things | 20/12/2023 | ||||||||||||||||||
| PSTW-151 | Study certificates - Automatic recognition for applying for child benefit | https://www.oeffentliche-it.de/documents/10181/14412/KI+im+Beh%C3%B6rdeneinsatz+-+Erfahrungen+und+Empfehlungen | To apply for child benefit, the current certificate of study of the child in question must be submitted twice a year. This results in a high volume of documents to be checked by hand, especially since the German universities could not agree on a uniform form. The client uploads the certificate of study to an appropriate website. The text of the certificate of study is extracted with OCR (Optical Character Recognition) and transferred to the system for classification. Four issues are checked: Is it a certificate of study (yes/no) and with what probability (score)? Is it the right child? Is it the correct validity period/semester? Is it a known German university? The result of the classification is displayed to the employees in the specialist procedure of the family benefits office. At the same time, the result of the check procedure "Studienbescheinigung ja /nein" (certificate of study yes /no) is indicated. This must then be actively accepted by the employee. The training data currently consists of 60,000 study certificates that are semi-automatically annotated and then used for training. Using a specially developed algorithm, the personal data is anonymised before classification and can therefore also be used as training data. The classification of the study certificate is carried out by: Naive Base/Support Vector Machine / Logistic Regression, NLP (Natural Language Processing), and Named Entity Recognition is used for data extraction. | National | Germany | DE | Federal Employment Agency | Central-Government | Social protection | Family and children. | Implemented | 2.019 | Adjudication | Taking decisions on benefits | No | No | Artificial Intelligence | G2G | x | x | x | x | x | x | KI im Behördeneinsatz: Erfahrungen und Empfehlungen https://www.oeffentliche-it.de/documents/10181/14412/KI+im+Beh%C3%B6rdeneinsatz+-+Erfahrungen+und+Empfehlungen | Communication | Natural language processing | Knowledge representation | text analysis | 09/11/2023 | |||||||||||||||
| PSTW-154 | Child benefit - Voice assistant for parents support | https://www.oeffentliche-it.de/documents/10181/14412/KI+im+Beh%C3%B6rdeneinsatz+-+Erfahrungen+und+Empfehlungen | Parents are required by law to provide the registry office with information on the registration of their child in the first days after the birth of their child to the registrar's office, to determine the name and to create the first formal thus also create the first formal prerequisite for receiving parental and child benefits. The bureaucratic burden is increased by the fact that documents are requested at different places in a redundant manner and that there is usually (still) no electronic data exchange. Immediately after the birth, this creates additional work for many parents - in addition to the often tense domestic situation. Now, parents can submit it directly at the maternity hospital. Parents now receive their child's birth certificate, tax identification number, registration in the residents' registry, and child benefit notification much faster by mail. Child benefits are transferred directly to their account. The pilot also includes the use of a voice assistance system to make it easier and more accessible to complete the combined application. Parents are guided through the process verbally at stationary terminals in hospitals or through tablets or smartphones. | Local | Germany | DE | Hamburg Office for IT and Digitalisation | Local Government | Social protection | Family and children. | Pilot | 2.021 | Public services and engagement | Service personalisation (various) | No | No | Artificial Intelligence | G2C | x | x | KI im Behördeneinsatz: Erfahrungen und Empfehlungen https://www.oeffentliche-it.de/documents/10181/14412/KI+im+Beh%C3%B6rdeneinsatz+-+Erfahrungen+und+Empfehlungen | Communication | Natural language processing | Knowledge representation | Audio processing | Voice Assistant | 09/11/2023 | ||||||||||||||||||
| PSTW-1556 | Use of IoT technologies to gather data from the City of Ferrara | http://eventipa.formez.it/sites/default/files/allegati_eventi/Poletti_20042023.pdf | City of Ravenna started multiple projects on the use of IoT technologies to monitor and gather sensitive data from the city to monitor air quality, to analyse tourists flow, to monitor mobility sharing. | Local | Italy | IT | City of Ravenna | Local Government | General public services | General public services n.e.c. | Pilot | 2.023 | Analysis, monitoring and regulatory research | Information analysis processes | No | No | Artificial Intelligence | G2G | x | x | x | x | http://eventipa.formez.it/sites/default/files/allegati_eventi/Poletti_20042023.pdf | Planning | Planning and Scheduling | internet of things | 15/01/2024 | ||||||||||||||||||
| PSTW-1565 | Germany analyses big data with AI to manage tourist trends | https://www.segittur.es/wp-content/uploads/2021/11/Guia-50bbpp-digitalizacion-para-destinos-DTI_Segittur.pdf | This solution from the German National Tourist Board (GNTB) provides a comprehensive overview of destination visitor trends. analysed data allows for a better understanding of origin markets, tourist preferences, and the impact of certain events on tourism demand, as well as insights into how, when, and where marketing investments perform best. The project began with the design of objectives and indicators to monitor the success of GNTB marketing efforts, aiming to identify and select market information and campaign data useful for understanding their impact and designing future strategies. To maximize success, the GNTB enlisted the help of a specialised private company in Data Analytics, which fulfilled two fundamental roles. Firstly, it provided precise and almost real-time data on the impacts of different marketing campaigns on visitor origin markets. Secondly, it generated analysis reports and provided access to a Business Intelligence platform for visualizing results. Large databases from various Global Distribution Systems (GDS) and other sources on flight reservations were utilized to analyse the success of these actions by comparing variations before and after the campaigns. Notably, Machine Learning techniques were employed to create trend prediction algorithms. Insights gained included variables such as identifying nationality trends, understanding how tourists arrived at the destination, and comprehending the most popular cities among different population segments. Visitors to the destination will experience an indirect effect of this solution, as tourism offerings can be tailored to their preferences, enhancing overall trip satisfaction. | National | Germany | DE | German National Tourist Board | Central-Government | Economic Affairs | General economic, commercial and labour affair | Implemented | 2.021 | Analysis, monitoring and regulatory research | Prediction and planning | No | No | Artificial Intelligence | G2G | x | x | https://www.segittur.es/wp-content/uploads/2021/11/Guia-50bbpp-digitalizacion-para-destinos-DTI_Segittur.pdf | Planning | Planning and Scheduling | Knowledge representation | big data | 10/04/2024 | |||||||||||||||||||
| PSTW-1570 | AI application developed for Dubrovnik visitors predicting the number of visitors in the Old Town | https://dubrovnik-visitors.hr/ | The City of Dubrovnik, the DURA development agency and the Enum Software startup, within the measures projected by the ‘Respect the City’ project, have developed and launched an application which predicts the number of visitors to the Old Town of Dubrovnik, reports Dubrovački Vjesnik on October 10, 2018. Based on machine learning as a special branch of artificial intelligence, the application estimates the number of people in the historic Old Town and the contact zones of Dubrovnik on the selected day. The application is certainly most useful for visitors planning to visit the ancient city center, but no less important, it provides accurate and timely information to citizens as well as to all local businesses in planning their daily or business activities. | Local | Croatia | HR | City of Dubrovnik | Local Government | Economic Affairs | General economic, commercial and labour affair | Implemented | 2.018 | Analysis, monitoring and regulatory research | Prediction and planning | No | No | Artificial Intelligence | G2C | x | x | x | https://total-croatia-news.com/lifestyle/dubrovnik-visitors-new-application-predicting-number-of-visitors-in-old-town/ | Learning | Machine learning | Knowledge representation | 10/04/2024 | |||||||||||||||||||
| PSTW-1579 | DATAESTUR to understand tourism in Spain via big data | https://www.dataestur.es/ | SEGITTUR, a Spanish Agency under the Ministry of Industry, Trade and Tourism, has released in 2020 the DATAESTUR website. The initiative is part of the actions to create a new national observatory of tourism intelligence envisaged in the “Promotion plan of the tourism sector”, which was released in June 2020 to provide an immediate response to the impact of COVID-19.139 DATAESTUR collects the most significant Spanish national tourism data from different public and private sources, including the National Statistics Institute, the Bank of Spain, Turespaña, UNWTO, Telefónica and Mabrian Technologies SL. Data is freely available for consultation and structured into five categories: general data (e.g. international tourist arrivals and visits to museums), economic data (tourism expenditure, contribution to GDP, and employment), transport statistics, accommodation occupancy and prices, and tourism research reports and analyses. | National | Spain | ES | SEGITTUR | Central-Government | General public services | Executive and legislative organs, financial and fiscal affairs, external affairs. | Implemented | 2.020 | Public services and engagement | Service integration (various) | No | No | Artificial Intelligence | G2B | x | x | x | Smart tourism report, https://op.europa.eu/en/publication-detail/-/publication/9df86541-fba5-11ec-b94a-01aa75ed71a1/language-en | Reasoning | Knowledge representation | big data | 14/09/2023 | |||||||||||||||||||
| PSTW-1581 | Helinki Tourist info chatbot | https://www.myhelsinki.fi/en/info/tourist-information | Chatbot answering to general enquiries related to touristic information | Local | Finland | FI1B | City of Helsinki | Local Government | General public services | Executive and legislative organs, financial and fiscal affairs, external affairs. | Implemented | 2.023 | Public services and engagement | Service personalisation (various) | No | No | Artificial Intelligence | G2C | x | x | x | x | x | x | Smart tourism report, https://op.europa.eu/en/publication-detail/-/publication/9df86541-fba5-11ec-b94a-01aa75ed71a1/language-en | Communication | Natural language processing | chatbot | 14/09/2023 | ||||||||||||||||
| PSTW-1582 | Amsterdam's IBEACON LIVING LAB - First beacon-guided city walk | http://okosvaros.lechnerkozpont.hu/en/node/357 | Amsterdam's Beacon Mile is the world's first beacon-guided city walk designed to inform tourists during their exploration of the city. Designed to serve as an open and public test environment for beacons and LoRa-enabled sensor beacons, the initiative is a joint project of Glimworm and KPN, who are aiming to kick-start the capital city's Internet of Things economy. | Local | Netherlands | NL32 | City of Amsterdam | Local Government | General public services | Executive and legislative organs, financial and fiscal affairs, external affairs. | Pilot | 2.015 | Public services and engagement | Service personalisation (various) | No | No | Artificial Intelligence | G2C | x | x | x | x | x | Smart tourism report, https://op.europa.eu/en/publication-detail/-/publication/9df86541-fba5-11ec-b94a-01aa75ed71a1/language-en | Services | AI services | internet of things | 14/09/2023 | |||||||||||||||||
| PSTW-1583 | Event Impact Calculator in Gothenburg | https://www.eventimpactcalculator.com/ | Within this framework of increasing attractiveness of the city combined with growing attention towards sustainability, the Swedish Sports Confederation and Go:teborg&co – a marketing company controlled by the city – developed the Event Impact Calculator, a tool to estimate the socio-economic and environmental impact of an event. The tool is free to use for all relevant stakeholders, such as event organisers, regions, municipalities, destinations, property owners, tour operators, the hotel and restaurant industry, students, etc. The tool is characterised by its user-friendliness, as users are simply required to input a series of figures, they have knowledge of, or can make educated guesses about. These include key figures about the magnitude of the event (such as on the expected number of participants or the expected number of foreign participants), information on participants’ expected accommodation and means of transportation, costs of tickets, sponsorships, and even the residents’ attitude towards the event. After receiving the data, the tool compiles a report estimating economic, environmental and social impacts, to be potentially used by organisers to inform negotiations with destination managers, motivate grant applications, attract sponsors, or any other activity in connection with the event. Therefore, the tool allows tourism stakeholders to organise events with greater professionalism thanks to the possibility of informing discussions and decisions through data.15 | Local | Sweden | SE23 | Go:teborg&co | Local Government | Recreation, culture and religion | Recreational and sporting services. | Implemented | 2.016 | Analysis, monitoring and regulatory research | Information analysis processes | No | Yes | Artificial Intelligence | G2B | x | x | x | Smart tourism report, https://op.europa.eu/en/publication-detail/-/publication/9df86541-fba5-11ec-b94a-01aa75ed71a1/language-en | Services | AI services | data analytics | 14/09/2023 | |||||||||||||||||||
| PSTW-1588 | Webapp L15 - digital ecosystem of Lombardy Region | https://www.l15.regione.lombardia.it/#/home | This digital platform gathers single APIs provided by public or private providers. L’ambiente si basa su una personalizzazione (realizzata da Aria S.p.A) di Open 2.0, l’applicativo open source messo a disposizione da Regione Lombardia per la creazione di strumenti collaborativi. Multiple services are available, from health care unit availability in regional hopsitals to parking availability. | Regional | Italy | ITC4 | Region of Lombardy | Regional Government | General public services | General public services n.e.c. | Implemented | 2.023 | Public services and engagement | Service personalisation (various) | No | No | Artificial Intelligence | G2C | x | x | x | x | x | x | Smart tourism report, https://op.europa.eu/en/publication-detail/-/publication/9df86541-fba5-11ec-b94a-01aa75ed71a1/language-en | Services | AI Services | platform as a service | 14/09/2023 | ||||||||||||||||
| PSTW-1592 | H0DE1AN - Big data to improve the tourism management in Gipuzkoa under the Begika model | https://www.hodeian.eus/public/es/index.php | H0DE1AN wants to promote sustainable and efficient tourism. It is a tool to analyze consumption habits, origin or how visitors move through the territory of Gipuzkoa. Each indicator shown must be analyzed in the context of the information source that provides it. | Local | Spain | ES21 | City of Gipuzkoa | Local Government | General public services | Executive and legislative organs, financial and fiscal affairs, external affairs. | Implemented | 2.017 | Analysis, monitoring and regulatory research | Information analysis processes | No | No | Artificial Intelligence | G2G | x | x | x | Smart tourism report, https://op.europa.eu/en/publication-detail/-/publication/9df86541-fba5-11ec-b94a-01aa75ed71a1/language-en | Reasoning | Knowledge representation | data analytics | 14/09/2023 | |||||||||||||||||||
| PSTW-1593 | Arantxat virtual tourist guide | https://basquemagazine.com/en/plans/gipuzkoa-digitises-its-tourism/ | One of the milestones in this process of innovation and commitment to new channels is the creation of 'Arantxat', a virtual tourist guide developed under a chatbot system available for whatsapp that includes all the information flows that have been collected from the most common queries received in tourist offices. | Local | Spain | ES21 | City of Gipuzkoa | Local Government | Recreation, culture and religion | Recreation, culture and religion n.e.c. | Implemented | 2.020 | Public services and engagement | Service personalisation (various) | No | No | Artificial Intelligence | G2C | x | x | x | x | x | x | Smart tourism report, https://op.europa.eu/en/publication-detail/-/publication/9df86541-fba5-11ec-b94a-01aa75ed71a1/language-en | Communication | Natural language processing | chatbot | 14/09/2023 | ||||||||||||||||
| PSTW-1597 | e-Albania platform chatbot | https://e-albania.al/ | Chatbot for citizens enquiries available on the e-Albania platform, launched at the beginning of 2024 | National | Albania | ALB | Albanian national agency of information technology (AKSHI) | Central-Government | General public services | General public services n.e.c. | Implemented | 2.024 | Public services and engagement | Service personalisation (various) | No | No | Artificial Intelligence | G2C | x | x | x | x | x | x | https://seenews.com/news/albania-launches-virtual-assistant-for-govt-e-services-844363 | Communication | Natural language processing | AI Services | chatbot | 15/01/2024 | |||||||||||||||
| PSTW-1599 | TreC Mamma - Italian app for new mothers | https://www.apss.tn.it/Novita/Notizie/Nasce-TreC-Mamma-la-App-trentina-per-tutte-le-future-mamme | TreC Mamma is a digital appintegrated with a digital personal assistant that allows mothers to use chatbots to gather information on pregnancy and childcare. | Regional | Italy | ITH2 | Azienda Provinciale per i Servizi Sanitari Trento | Regional Government | Health | Public health services. | Implemented | 2.023 | Public services and engagement | Service personalisation (various) | No | No | Artificial Intelligence | G2C | x | x | x | x | x | x | https://magazine.fbk.eu/it/news/nasce-trec-mamma-la-app-trentina-per-tutte-le-future-mamme/ | Communication | Natural language processing | AI Services | chatbot | 15/01/2024 | |||||||||||||||
| PSTW-1600 | Hillingdon Council praised for innovative approach to safeguarding children | https://www.hillingdon.gov.uk/article/7121/Council-praised-for-innovative-approach-to-safeguarding-children, https://trentinosalutedigitale.com/blog/portfolio/trec-mamma/ | With PwC and Amazon’s support, in only a three month period, Hillingdon became the first UK local authority to have deployed an automated voice and web chat solution at scale. | Local | United Kingdom | UK | London Borough of Hillingdon | Local Government | General public services | General public services n.e.c. | Implemented | 2.023 | Public services and engagement | Service personalisation (various) | No | No | Artificial Intelligence | G2C | x | x | x | x | x | x | https://www.hillingdon.gov.uk/article/7121/Council-praised-for-innovative-approach-to-safeguarding-children | Communication | Natural language processing | AI Services | chatbot | 15/01/2024 | |||||||||||||||
| PSTW-1612 | Managing vacancies - Recommender: the amazon of the labour market | https://op.europa.eu/en/publication-detail/-/publication/807dae77-2657-11e7-ab65-01aa75ed71a1/language-en | The Innovation Lab of VDB is working to improve matching using Big Data analytics to recommend vacancies to a jobseeker when they access the VDAb's vacancy system. | Regional | Belgium | BE2 | Flemish Employment and Vocational Training Service (VDAB) | Regional Government | Social protection | Unemployment. | In development | 2.017 | Public services and engagement | Service personalisation (various) | No | No | Artificial Intelligence | G2C | x | x | x | https://op.europa.eu/en/publication-detail/-/publication/807dae77-2657-11e7-ab65-01aa75ed71a1/language-en | Reasoning | Machine learning | Optimisation | recommender system | 15/01/2024 | ||||||||||||||||||
| PSTW-1615 | Wien's digital building permit system | https://digitales.wien.gv.at/projekt/brisevienna/ | BRISE (Building Regulations Information for Submission Envolvement) generally stands for smart, efficient public administration. Based on administrative procedures in building and construction as an example for smart digital administration, the City of Vienna has taken on a pioneering role in Europe. Innovative technologies help digitise building permit applications and procedures, making the entire process faster, more efficient, more transparent and less costly. The digital processes developed for BRISE can be transferred directly to other fields of public administration. The BRISE project combines the high-tech methods of Building Information Modeling (BIM), Artificial Intelligence (AI) and Augmented Reality (AR) into a comprehensive, consistently digital and automated approval process. Instead of 2D paper plans, completely digital 3D building models are used. The BRISE solution is therefore an innovative basis for managing the entire construction project - from planning and submission to on-site construction site inspection and acceptance of the finished structure. | Local | Austria | AT | City of Wien - Municipal Directorate of Strategic ICT | Local Government | Economic Affairs | Mining, manufacturing and construction. | Pilot | 2.020 | 2023 | Analysis, monitoring and regulatory research | Innovating Public Policy | No | No | Artificial Intelligence | G2G | x | x | x | x | https://digitales.wien.gv.at/en/projekt/brise-vienna/ | Planning | Planning and Scheduling | 15/01/2024 | ||||||||||||||||||
| PSTW-1617 | Facebook chatbot connected to NoiPA services | https://www.agendadigitale.eu/cittadinanza-digitale/noipa-come-migliorare-assistenza-e-comunicazione-con-un-chatbot/ | Chatbot responding to public employees' enquiries of NoiPA services. | National | Italy | IT | Direzione dei Sistemi Informativi e dell'Innovazione of the Minitry of the Economics and Finances | Central-Government | General public services | Transfers of a general character between different levels of government. | Implemented | 2.017 | Public services and engagement | Service personalisation (various) | No | No | Artificial Intelligence | G2C | x | x | x | x | x | x | https://www.agendadigitale.eu/cittadinanza-digitale/noipa-come-migliorare-assistenza-e-comunicazione-con-un-chatbot/ | Communication | Natural language processing | AI Services | chatbot | 15/01/2024 | |||||||||||||||
| PSTW-162 | Véda-KAFIR-ROBOTZSARU (‘Robocop’) - System Operated by the Police for Traffic Safety Automated Processing | https://www.origo.hu/auto/20160415-megneztuk-a-szupertraffipaxok-vasarosnemenyi-kozpontjat.html | Véda is an intelligent road traffic camera system, which provides data to KAFIR (Közlekedésbiztonsági Automatizált Feldolgozó és Információs Rendszer - Traffic Safety Automated Processing and Information System). Together with the solutions provided by Robotzsaru (‘Robocop’), an integrated administration, case processing and electronic records management system, basically the main software of the police, fines for road traffic violations are almost automatic The cameras record the registration number, speed of the vehicle, the coordinates of the location, the date and time of the event. This data is transferred to the KAFIR, which cross-checks data with the traffic registry (e.g., if the vehicle is stolen) and uploads everything together in the Robotzsaru IT system. The generated files are then classified and transmitted to the responsible authority. Up to this point, there is no possibility for human interference. Possible infringements are punishable under no-fault liability and the data is unquestionable, even if the decision is made automatically. However, there is an ex-post check by the administrator. | National | Hungary | HU | Hungarian police | Central-Government | Public order and safety | Police Services | Implemented | 2.015 | Enforcement | Predictive enforcement processes | No | No | Artificial Intelligence | G2C | x | x | x | https://metamorphosis.org.mk/wp-content/uploads/2021/04/algovrithms_2.0_report-2021.pdf | Perception | Computer vision | Machine learning | 10/11/2023 | |||||||||||||||||||
| PSTW-1624 | Chatbot Duomo di Milano official website | https://www.duomomilano.it/it/infopage/veneranda-fabbrica-del-duomo-di-milano/23/ | Chatbot available on the official website of the Milan Duomo. | Local | Italy | IT | Duomo di Milano | Local Government | Recreation, culture and religion | Cultural services. | Implemented | 2.021 | Public services and engagement | Service personalisation (various) | No | No | Artificial Intelligence | G2C | x | x | x | x | x | x | https://www.duomomilano.it/it/infopage/informativa-servizio-chatbot/152/ | Communication | Natural language processing | AI Services | chatbot | 15/01/2024 | |||||||||||||||
| PSTW-1634 | EKOME Greece - chatbot | https://www.ekome.media/ | Chatbot on the official website of the National Centre of Audiovisual Media and Communication answering general enquiries. | National | Greece | EL | National Centre of Audiovisual Media and Communication | Central-Government | Recreation, culture and religion | Broadcasting and publishing services. | Implemented | 2.023 | Public services and engagement | Service personalisation (various) | No | No | Artificial Intelligence | G2C | x | x | x | x | x | x | https://www.ekome.media/who-we-are/ | Communication | Natural language processing | chatbot | 21/09/2023 | ||||||||||||||||
| PSTW-1644 | Aarhus Municipality creates an AI-enabled analytical tool for sustainable procurement decisions | https://www.aarhus.dk/nyt/borgmesterens-afdeling/2022/juni/kunstig-intelligens-skal-sikre-baeredygtige-indkoeb-i-aarhus-kommune/ | Aarhus Municipality has taken a significant stride in the realm of sustainable procurement, leveraging the power of artificial intelligence through a collaboration with the local company Konsido. Together, they have crafted an innovative analysis tool that guides businesses in revamping their purchasing patterns towards more eco-friendly alternatives. With public sector spending on goods and services reaching DKK 200 billion annually, this tool presents a substantial opportunity for integrating sustainability into public procurement. | Local | Denmark | DK | Aarhus Municipality | Local Government | Economic Affairs | General economic, commercial and labour affair | Pilot | 2.022 | Internal management | Procurement management | No | No | Artificial Intelligence | G2G | x | x | x | x | https://govlaunch.com/projects/aarhus-dk-and-konsido-create-ai-enabled-analytical-tool-for-sustainable-procurement-decisions | Reasoning | Automated reasoning | 10/04/2024 | |||||||||||||||||||
| PSTW-1645 | AI-enabled platform for reduced hospitalizations among senior residents | https://govlaunch.com/projects/koge-dk-develops-ai-enabled-platform-for-reduced-hospitalizations-among-senior-residents | The planned platform uses patient notes from municipal caregivers for early disease detection. Køge officials also receive recommendations for localized resource deployment. Senior care employees previously trained in early diagnosis and patient communications skills complemented by the platform. The Danish Digitisation Agency provided funding for the project and will use Køge's platform as a model for other cities. | Local | Denmark | DK | Municipality of Koge | Local Government | Health | Public health services. | Pilot | 2.021 | Analysis, monitoring and regulatory research | Prediction and planning | No | No | Artificial Intelligence | G2G | x | x | x | https://www.sn.dk/koege-kommune/kunstig-intelligens-skal-opdage-tidlige-sygdomstegn/ | Planning | Planning and Scheduling | Machine learning | probabilistic model | 10/01/2024 | ||||||||||||||||||
| PSTW-1649 | The city of Tampere, in Finland, predicts future foot traffic in the city center with its Tamperen Pulssi tool | https://govlaunch.com/projects/tampere-fi-predicts-future-foot-traffic-in-the-city-center-with-its-tamperen-pulssi-tool | Tampere and Wapice Oy used camera footage from central locations for foot traffic pattern identification. An AI-powered platform estimates future traffic within the context of weather forecasts, public holidays, and local arena events. Local businesses and agencies can see next month's estimated pedestrian traffic by opening Tamperen Pulssi in the Tampere.Finland app. This resource proves valuable in areas from staffing shops and restaurants to planning street maintenance. | Local | Finland | FI | Municipality of Tampere | Local Government | General public services | General public services n.e.c. | Pilot | 2.023 | Analysis, monitoring and regulatory research | Prediction and planning | No | No | Artificial Intelligence | G2B | x | x | x | x | https://www.tampere.fi/ajankohtaista/2023/08/15/yrittajat-mukana-alykaupunkikehittamisessa-tampereella | Planning | Planning and Scheduling | Computer vision | Knowledge representation | probabilistic model | 10/01/2024 | ||||||||||||||||
| PSTW-165 | Intelligent mechanisms for clinical evaluation - Facilitate the reconciliation of citizens | https://www.almaviva.it/it_IT/Sanita_digitale/Case_study_IA_sanita, https://www.lombardiaspeciale.regione.lombardia.it/wps/portal/LS/Home/News/Dettaglio-News/2020/10-ottobre/premio-vimercate/premio-vimercate, https://www.asst-brianza.it/web/uploads/news/newsletter/eedf8a85-a91d-43af-abff-a7655e8875fd.pdf | Vimercate Local Health Authority objective was to introduce intelligent mechanisms that would facilitate the reconciliation of the need to offer the citizen the best care and, at the same time, optimize costs, reducing the time that each doctor took away from taking care of patients for administrative duties. Machine Learning algorithm can support the doctor in the clinical evaluation and make suggestions in less time, analyzing much more information. Clinicians in the diabetic, nephrology and internal medicine departments are called upon every day to make predictions based on the conditions of the patients being treated with respect to the time of discharge, the possibility of the onset of complications and consequent need for readmission, even urgent, to the facility. They must, they needed to update the forecast every day for both patients in treatment and for those in protected discharge, to ensure that the facility was always able to provide assistance. | National | Italy | IT | Vimercate Local Health Authority | Local Government | Health | Health n.e.c. | Implemented | 2.021 | Internal management | Internal primary processes | No | No | Artificial Intelligence | G2G | x | x | x | Survey Use and impact of AI in the public sector. 2021 (https://ai-watch.ec.europa.eu/news/survey-artificial-intelligence-use-public-sector-2021-06-11_en) | Learning | Machine learning | Optimisation | 10/11/2023 | |||||||||||||||||||
| PSTW-1651 | Kuusamo Municipality experiments with Kuusamo-Kati chatbot for tourism and health questions | https://www.kuusamo.fi/tiedotteet/chatbot-taydentamaan-kaupungin-asiakaspalvelua/ | The AI-enabled bot is activated on the city's website when live support is unavailable on weeknights and weekends. The bot was initially programmed with knowledge about the website's most frequently searched topics. Residents and tourists contribute to Kuusamo-Kati's development through conversations as well as feedback forms. Municipal leaders will expand the chatbot into other topics based on lessons learned during the summer pilot. | Local | Finland | FI | Kuusamo Municipality | Local Government | General public services | General services. | Implemented | 2.021 | Public services and engagement | Service personalisation (various) | No | No | Artificial Intelligence | G2C | x | x | x | x | x | x | https://govlaunch.com/projects/kuusamo-fi-experiments-with-kuusamo-kati-chatbot-for-tourism-and-health-questions | Communication | Natural language processing | chatbot | 10/04/2024 | ||||||||||||||||
| PSTW-1652 | Järvenpää is piloting Kunta-Kati the AI chatbot as its new customer service representative | https://www.jarvenpaa.fi/a/digiassistentti-kunta-kati-vastaa-jarvenpaan-kaupungin-sivuilla | The City of Järvenpää partnered with Accenture and Boost.ai to pilot a "fixed-term employment relationship" with Kunta-Kati acting as the city's new customer service representative. Kunta-Kati uses artificial intelligence to understand urban issues and answer questions about the city. Whenever she is unable to answer a question Kunta-Kati directs the users to ask their question directly to the city's customer service staff. | Local | Finland | FI | Järvenpää Municipality | Local Government | General public services | General services. | Implemented | 2.020 | Public services and engagement | Service personalisation (various) | No | No | Artificial Intelligence | G2C | x | x | x | x | x | x | https://govlaunch.com/projects/jarvenpaa-fi-is-piloting-kunta-kati-the-ai-chatbot-as-its-new-customer-service-representative | Communication | Natural language processing | chatbot | 10/04/2024 | ||||||||||||||||
| PSTW-166 | Scout.AI - Analyse the information recorded within the SNS 24 TAE Service | https://www.spms.min-saude.pt/2019/08/spms-recebe-apoio-da-fct-para-projetos-de-ciencia-dos-dados-e-ia/ | The Triage, Counselling and Referral Service (TAE) is a telephone service provided by the Contact Centre of the National Health Service - SNS 24. In 2018, more than 1 million calls with an average duration of 7-8 minutes were answered. Being of national scope, this is a service that promotes equity in the access to health care. Telephone service is provided by nurses and follows pre-defined clinical algorithms. Triage is based on a specific clinical algorithm (out of a set of 59), and the choice of the most appropriate algorithm is extremely important and relevant. The selected clinical algorithm should ensure high safety (not failing to identify situations that require urgent medical contact) and should have high discriminatory capability. In this context, the SNS24 Scout.AI will apply Artificial Intelligence (AI) methodologies, aiming the development of decision support tools with two main objectives: (1) Support the nurse in the selection of the most appropriate clinical algorithm and (2) Provide support to Directorate-General of Health (DGS) in the optimization process of the design of clinical algorithms and their referrals. The first objective will be achieved by identifying the most appropriate algorithms for a given set of symptoms, with adjustment for age and sex. The AI methodology to be applied will be based on a classifier built on automatic learning algorithms on an anonymised data set, obtained from contacts of the SNS 24 in 2017 and 2018. This data represents accumulated experience in around 2 million cases. After the creation of the prediction model, it will be implemented in the SNS 24 TAE Service as decision support, indicating in real time which algorithms are most likely to be used. | National | Portugal | PT | SPMS - Shared Services of the Ministry of Health, EPE | Central-Government | Health | Health n.e.c. | In development | 2.021 | Enforcement | Supporting inspection processes | No | No | Artificial Intelligence | G2C | x | x | Survey Use and impact of AI in the public sector. 2021 (https://ai-watch.ec.europa.eu/news/survey-artificial-intelligence-use-public-sector-2021-06-11_en) | Reasoning | Knowledge representation | Optimisation | decision support | 10/11/2023 | |||||||||||||||||||
| PSTW-1670 | Borås Municipality assesses AI chatbot improvements to customer service during pilot | https://www.boras.se/2.523bcbe41242f62104e80002082.html | An AI-enabled chatbot named Kommun-Kim offers virtual assistance to website visitors during the six-month pilot. The bot started with answers to frequently asked questions noted by municipal staff. Kommun-Kim improves its knowledge base with each interaction and refers users to customer service as necessary. Borås will evaluate the quality of user experiences when considering how the bot will be used in the future. | Local | Sweden | SE | Borås Municipality | Local Government | General public services | General public services n.e.c. | Implemented | 2.020 | Public services and engagement | Service personalisation (various) | No | No | Artificial Intelligence | G2C | x | x | x | x | x | x | https://govlaunch.com/projects/boras-se-assesses-ai-chatbot-improvements-to-customer-service-during-pilot | Communication | Natural language processing | AI Services | chatbot | 10/04/2024 | |||||||||||||||
| PSTW-1674 | Derby City Council connects residents to city services with AI-powered digital assistants | https://govlaunch.com/projects/derby-city-council-gb-connects-residents-to-city-services-with-ai-powered-digital-assistants | Since April visitors to Derby City Council’s website and those who call the council’s main phone line can seek help and assistance from AI “helpers”. Darcie can help with council services and Ali is available to help Derby Homes customers with housing enquiries. Senior bosses at the council delivered a presentation at the meeting and said the use of AI technology since April has already met a savings target of £200,000 within the council’s budget plan. They said the main goal is trying to allow residents to access council services all in one place. | Local | United Kingdom | UK | Derby City Council | Local Government | General public services | General public services n.e.c. | Implemented | 2.023 | Public services and engagement | Service personalisation (various) | No | No | Artificial Intelligence | G2C | x | x | x | x | x | x | https://www.derbytelegraph.co.uk/news/derby-news/derby-city-councils-new-ai-8625382 | Communication | Natural language processing | chatbot | 10/01/2024 | ||||||||||||||||
| PSTW-1675 | Project-A.I.R (Artificial Intelligence Guided Retrofit) | https://govlaunch.com/projects/london-borough-of-harrow-gb-develops-solar-glass-structure-concept-for-social-housing | The project, known as Project-A.I.R (Artificial Intelligence Guided Retrofit), is the first AI-enabled concept to deliver proven efficiencies in the field of housing decarbonisation. The concept being presented is the creation of a standalone transparent glass garden space where solar power-generating materials are integrated with glass, serving as a dual function of structure and power generation unit in one. The AI-enabled concept is designed to deliver proven efficiencies in reducing carbon emissions and energy usage. The pergola-canopy semi-transparent PV glass creates a 3 Kilowatt (KW)/Peak solar array, capable of delivering a 45% reduction in individual household energy bills throughout the year. | Local | United Kingdom | UK | London Borough of Harrow | Local Government | Economic Affairs | Fuel and energy | Pilot | 2.023 | Analysis, monitoring and regulatory research | Prediction and planning | No | No | Artificial Intelligence | G2C | x | x | https://harrowonline.org/2023/05/02/harrow-council-and-polysolar-partner-to-showcase-groundbreaking-renewable-energy-solution/ | Planning | Planning and Scheduling | 10/01/2024 | |||||||||||||||||||||
| PSTW-1676 | Dudley Metropolitan Borough Council creates smart intersection with AI-powered road sensors | https://govlaunch.com/projects/dudley-metropolitan-borough-council-gb-creates-smart-intersection-with-vivacity-road-sensors | Dudley Metropolitan Borough Council has begun during 2023 to deploy road sensors in an effort to improve traffic flows and reduce congestion. | Local | United Kingdom | UK | Dudley Metropolitan Borough Council | Local Government | Economic Affairs | Transport | Implemented | 2.023 | Analysis, monitoring and regulatory research | Prediction and planning | No | No | Artificial Intelligence | G2G | x | x | x | x | https://www.ukauthority.com/articles/dudley-council-deploys-sensors-for-smart-junctions/ | Perception | Computer vision | Planning and Scheduling | image processing | 10/01/2024 | |||||||||||||||||
| PSTW-1678 | Leeds City Council pursues smart traffic management with AI for Detection technology | https://govlaunch.com/projects/leeds-city-council-gb-pursues-smart-traffic-management-with-vivacitys-ai-for-detection-technology | The city has installed more than 180 AI for Detection sensors across 25 sites to tackle congestion thanks to the real-time detection of road users at junctions. | Local | United Kingdom | UK | Leeds City Council | Local Government | Economic Affairs | Transport | Implemented | 2.023 | Analysis, monitoring and regulatory research | Prediction and planning | No | No | Artificial Intelligence | G2G | x | x | https://www.smartcitiesworld.net/ai-and-machine-learning/leeds-becomes-early-adopter-of-vivacity-ai-traffic-tool | Perception | Computer vision | Planning and Scheduling | image processing | 10/01/2024 | |||||||||||||||||||
| PSTW-1680 | Powys County Council builds AI-enabled system for expedited Fuel Support Scheme reviews | https://govlaunch.com/projects/powys-county-council-gb-builds-ai-enabled-system-for-expedited-fuel-support-scheme-reviews | The council's developers spent a year designing a platform for automated reviews of local applications to the national support program. Applicants meeting all of the scheme's criteria received automatic approvals from the system. Duplicate applications were filtered out by AI, while potentially fraudulent applications were sent for council review. Residents benefitted from an easy-to-use application for £200 payments, while the council saved money on administration costs. | Local | United Kingdom | UK | Powys County Council | Local Government | Social protection | Social protection n.e.c. | Implemented | 2.023 | Adjudication | Taking decisions on benefits | No | No | Artificial Intelligence | G2G | x | x | x | x | https://en.powys.gov.uk/article/13864/AI-is-being-used-to-speed-up-the-payment-of-cost-of-living-grants | Reasoning | Automated reasoning | Machine learning | 10/01/2024 | ||||||||||||||||||
| PSTW-1683 | Bournemouth, Christchurch & Poole Council monitors coastal water quality with AI sensors | https://www.bcpcouncil.gov.uk/news-hub/news-articles/world-first-for-ai-water-quality-tool | Council officials and Poole Harbour Commissioners worked with UnifAI to install AI-powered sensors on coastal buoys. UnifAI's platform turns raw data on water pollutants and industrial discharges into in-depth analyses of quality levels. Real-time insights on quality changes lead to targeted cleanup or mitigation efforts. This two-year pilot created a template for low-cost, low-maintenance water quality monitoring for other councils. | Local | United Kingdom | UK | Bournemouth, Christchurch & Poole Council | Local Government | Environmental Protection | Pollution abatement. | Implemented | 2.022 | Analysis, monitoring and regulatory research | Monitoring policy implementation | No | No | Artificial Intelligence | G2G | x | x | x | https://govlaunch.com/projects/bournemouth-christchurch-poole-council-gb-monitors-coastal-water-quality-with-ai-sensors | Reasoning | Knowledge representation | Automated reasoning | sensor network | 10/04/2024 | ||||||||||||||||||
| PSTW-1689 | The City of Edinburgh Council continues smart city evolution with CCTV Control Centre | https://www.edinburgh.gov.uk/news/article/13404/the-city-of-edinburgh-council-set-to-invest-2-6m-in-smart-cctv | The new Control Centre will see the provision of high-definition CCTV cameras, expanded security coverage, and the introduction of advanced analytics and artificial intelligence that can provide situational awareness and predict and alert new and existing threats. The Council has partnered with North, the UK’s leading IoT service and solution provider, to lead on this transformational project which is set for completion in September this year (2022). The project will see North intelligently integrate the security system with traffic and transportation platforms to enhance the management of city operations. It will improve efficiency, quickly identify and address issues, provide simple and rapid retrieval of footage, and integrate with remote security systems that are currently not connected to the existing Control Room. The new system will allow for better city planning and will be able to provide a richer view of how people interact with the urban environment – whether on foot, bicycle or vehicle. | Local | United Kingdom | UK | City of Edinburgh Council | Local Government | Public order and safety | Public order and safety n.e.c. | Implemented | 2.022 | Enforcement | Smart Recognition processes | No | No | Artificial Intelligence | G2G | x | x | x | https://www.edinburgh.gov.uk/news/article/13404/the-city-of-edinburgh-council-set-to-invest-2-6m-in-smart-cctv | Perception | Computer vision | 10/04/2024 | ||||||||||||||||||||
| PSTW-1690 | Sunderland City Council converts data into improved services with AI-powered platform | https://govlaunch.com/projects/sunderland-city-council-gb-converts-data-into-improved-services-with-connexinos-platform | Sunderland in north-east England is implementing a new data platform to inform action on issues such as anti-social behaviour, social care, health, and environmental incidents. The ConnexinOS platform, which uses artificial intelligence and machine learning to identify trends in datasets and suggest the best course of action, will pool data from the council and third parties to support early intervention and coordinated multi-agency responses. | Local | United Kingdom | UK | Sunderland City Council | Local Government | Public order and safety | Public order and safety n.e.c. | Implemented | 2.022 | Analysis, monitoring and regulatory research | Monitoring policy implementation | No | No | Artificial Intelligence | G2G | x | x | https://cities-today.com/sunderland-targets-anti-social-behaviour-with-data-platform/ | Reasoning | Automated reasoning | Knowledge representation | data analytics | 10/01/2024 | |||||||||||||||||||
| PSTW-1697 | Derby City Council embarks on next phase of using AI to streamline services | https://www.derby.gov.uk/news/2024/february/council-embarks-next-phase-of-ai/ | The City Council is pioneering the use of AI technology in local government in partnership with ICS.AI, a leader in developing AI solutions in the public sector, and has now signed a £7 million contract to deliver the next stage of its project. Staff working in three service areas will soon be using AI copilots to help them carry out their jobs more effectively. AI technology is called a copilot because it acts as a smart helper for staff, supporting them in their day-to-day work, while staff members are the pilots who guide them. During phase 1, teams working in adult social care will use the emerging technology to review care packages and help them decide if someone who needs support living at home is receiving the right level of care. They will also use AI to answer more simple and straightforward enquiries from the public and professionals, so they can focus on dealing with queries which need their expertise. Across Customer Services, the Darcie and Ali (for Derby Homes) digital assistants for web-based and telephone enquiries will be upgraded and expanded to meet needs of our citizens. We will also use AI to answer emails quickly, or flag them with Council colleagues to deal with. | Local | United Kingdom | UK | Derby City Council | Local Government | General public services | General public services n.e.c. | Pilot | 2.024 | Internal management | Internal primary processes | No | No | Artificial Intelligence | G2G | x | x | x | https://www.derby.gov.uk/news/2024/february/council-embarks-next-phase-of-ai/ | Planning | Planning and Scheduling | Optimisation | 10/04/2024 | |||||||||||||||||||
| PSTW-170 | Project ROMATRIS | https://robotik.dfki-bremen.de/en/research/projects/romatris/ | The aim of the project is to design and develop a partially automated, mobile assistance robot to support material transport through impassable terrain. The main areas of application are rescue operations in disaster scenarios, such as collapsed buildings, operations in impassable terrain, train or traffic accidents, and other major emergencies. The system to be developed should be able to follow a person through difficult terrain (gravel, obstacles, slopes), transport material needed for the rescue operation and react to the user's gestures, as well as provide feedback. | National | Germany | DE | Federal Agency for Technical Relief | Central-Government | Public order and safety | Public order and safety n.e.c. | Pilot | 2.021 | 2025 | Internal management | Internal primary processes | No | No | Artificial Intelligence | G2C | x | x | x | Survey Use and impact of AI in the public sector. 2021 (https://ai-watch.ec.europa.eu/news/survey-artificial-intelligence-use-public-sector-2021-06-11_en) | Integration and Interaction | Robotics and Automation | Machine learning | 10/11/2023 | ||||||||||||||||||
| PSTW-1700 | Ministry of Labour and Social Policies chatbot | https://urponline.lavoro.gov.it/s/topic/0TO070000004Y4XGAU/bonus-trasporti?langu\age=it | The chatbot replies to general enquiries from citizens in relation to social policies, such as the "bonus trasporti" (Italian citizens could apply for a cash benefit of maximum 60 euros to buy transportation monthly passes). | National | Italy | IT | Ministry of Labour and Social Policies | Central-Government | Social protection | Social protection n.e.c. | Implemented | 2.023 | Public services and engagement | Service personalisation (various) | No | No | Artificial Intelligence | G2C | x | x | x | x | x | x | https://urponline.lavoro.gov.it/s/topic/0TO070000004Y4XGAU/bonus-trasporti?language=it | Communication | Natural language processing | AI Services | chatbot | 02/10/2023 | |||||||||||||||
| PSTW-1705 | Multiple chatbots on the spanish Agenzia Tributaria website | https://sede.agenciatributaria.gob.es/Sede/ayuda/herramientas-asistencia-virtual.html | In this section users can find a whole set of virtual assistance tools for Personal Income Tax, Censuses, VAT, SII and Collection, made up of virtual assistants, Informants, Income Tax and Censuses, search engines for economic activities, Locators of operations for the delivery of goods and provision of services. services, real estate transaction qualifier, calculators for payment terms, billing, late payment interest, modification of tax bases, and finally aid for the preparation of VAT models 303 and 390. | National | Spain | ES | Agencia Tributaria | Central-Government | General public services | Executive and legislative organs, financial and fiscal affairs, external affairs. | Implemented | 2.024 | Public services and engagement | Service personalisation (various) | No | No | Artificial Intelligence | G2C | x | x | x | x | x | x | https://sede.agenciatributaria.gob.es/static_files/Sede/Biblioteca/Folleto/Folleto_Herramientas_virtuales.pdf | Communication | Natural language processing | AI Services | chatbot | 10/04/2024 | |||||||||||||||
| PSTW-1706 | Chatbot - City of Rosealare | https://www.roeselare.be/# | Chatbot answering general enquiries. | Local | Belgium | BE | City of Rosealare | Local Government | General public services | General public services n.e.c. | Implemented | 2.024 | Public services and engagement | Service personalisation (various) | No | No | Artificial Intelligence | G2C | x | x | x | x | x | x | https://www.roeselare.be/# | Communication | Natural language processing | AI Services | chatbot | 10/04/2024 | |||||||||||||||
| PSTW-1719 | Real time network, text, and speaker analytics for combating organised crime - ROXANNE | https://orbi.uliege.be/bitstream/2268/252237/1/DS0220605ENN.en.pdf | The project will produce a tool for the investigation and mitigation of organised crime and illegal activities. It will allow the visualisation of generated maps of criminal relations and will allow interoperability and integration with more conventional tools already used by law enforcement. Usage of this tool will speed up investigations, reduce the workload per investigative case, and help map relationships based on speech, language, and video analysis. ROXANNE will provide law enforcement agencies with new technical tools and a clear and efficient legal framework for tracking and uncovering organised (often cross-border) criminal networks. The system will make use of the combined strengths of available technologies. The platform is under development; implementation is expected in 2022. | National | Lithuania | LT | Forensic Science Centre of Lithuania | Central-Government | Public order and safety | Law courts | In development | 2.022 | Internal management | Internal primary processes | No | No | Artificial Intelligence | G2G | x | x | x | https://orbi.uliege.be/bitstream/2268/252237/1/DS0220605ENN.en.pdf | Reasoning | Knowledge representation | Automated reasoning | 25/10/2023 | |||||||||||||||||||
| PSTW-1730 | AI for Water in Garda Lake area | https://www.trentinoinnovation.eu/en/public-ai-challenge-premiata-la-sfida-di-progetto-fondo-caproni/ | Niris startup is working on public water depurators (implants are in Lake Garda area and in some other Trentino Valleys), they are working with data collection and data representations to enable remote management. They developed a new use case with some AI students in a previous AI challenge that is using historical data of the purifiers (about 30 years) and the weather data in Stenico (Trento, Italy). Through an ML algorithm they made a forecast of the variation of incoming water (rain forecast), with an energy saving of about 5% (depurators consume high levels of energy). | Regional | Italy | IT | Provincia Autonoma di Trento | Regional Government | Environmental Protection | Waste water management. | Implemented | 2.022 | Analysis, monitoring and regulatory research | Prediction and planning | No | No | Artificial Intelligence | G2G | x | x | x | x | https://www.trentinoinnovation.eu/en/public-ai-challenge-premiata-la-sfida-di-progetto-fondo-caproni/ | Learning | Machine learning | Automated reasoning | 25/10/2023 | ||||||||||||||||||
| PSTW-1733 | I-CAN Police Crime Predictive System against Ndrangheta Network Crime | https://www.interpol.int/en/Crimes/Organized-crime/INTERPOL-Cooperation-Against-Ndrangheta-I-CAN | The Project is doing research, develop and publish the Toolkit for Responsible AI Innovation in Law Enforcement. The Toolkit will contain, amongst others, the following resources: 1) Guidance documents: Introductory Guide to AI for Law Enforcement Principles for Responsible Use of AI in Law Enforcement Organizational Roadmap for Implementing Responsible AI 2) Interactive tools: Organizational Readiness Assessment for Responsible AI Responsible AI in Action Tool AI Risk Assessment Tool 3) Target audience-specific briefs | Across Countries | Italy | IT | Italian Department of Public Security | Central-Government | Public order and safety | Public order and safety n.e.c. | In development | 2.020 | 2023 | Analysis, monitoring and regulatory research | Prediction and planning | No | No | Artificial Intelligence | G2G | x | x | x | x | x | https://www.wired.it/article/ndrangheta-algoritmo-polizia-i-can-interpol/ | Learning | Machine learning | Natural language processing | Searching | 25/10/2023 | |||||||||||||||
| PSTW-174 | Tracing potential victims of human trafficking and labour exploitation with AI | https://nos.nl/artikel/2273390-mensenhandel-opgespoord-via-bankgegevens | Inspectorate SZW works together with ABN-Amro and the University of Amsterdam to trace labor exploitation (human trafficking) by applying pattern recognition to baking information. SZW has supplied various risk patterns, which are traced in banking data with scripts. These connections are then checked by persons. If approved, this can be a motive for a further investigation by the Financial Intelligence Unit into suspicious transactions. Based on that investigation, the public prosecutor can decide to write a warrant, which the judge can use as cause for a further investigation. If so, address and transaction details will be supplied by the bank. These are used to trace potential victims – not perpetrators – of human trafficking. This pilot uses linear scripts which are then vetted for false positives by a human controller. The possibility of using machine learning to hone this process with machine learning in the future is under investigation, as well as possible expansion to 4 other large banks. | National | Netherlands | NL | Social Affairs and Employment Inspectorate (SZW) | Central-Government | Social protection | Social protection n.e.c. | Implemented | 2.019 | Analysis, monitoring and regulatory research | Information analysis processes | No | No | Artificial Intelligence | G2G | x | x | x | x | Survey Use and impact of AI in the public sector. 2021 (https://ai-watch.ec.europa.eu/news/survey-artificial-intelligence-use-public-sector-2021-06-11_en) | Reasoning | Automated reasoning | Machine learning | pattern recognition | 10/11/2023 | |||||||||||||||||
| PSTW-1743 | Automated transcripts to speed up judicial proceedings | https://dt4regions.eu/dt-stories/automated-transcripts-speed-judicial-proceedings | Legal proceedings have a peculiarity when it comes to the drafting of judgments. Sometimes the transcriptions of the meetings are needed, especially when the judgment is escalated to higher instances. Given the recording of the meeting, the video clip is examined to find out, for example, where exactly something was said or who was named. At the moment, in the Basque Country, administration transcripts are made by manually reviewing the videos of all the sessions. Thus, it's not possible to easily search for words, phrases, and generic entities across the video clip and there isn't any correlation between the speech and the person who pronounced it. Expected benefits Converting voice data into searchable text using automated transcription services may save significant time and create actionable value. With this solution, 100% manual transcription is no longer necessary, and efforts can be focused on correction and completion. In addition, if a court case is taken to a higher level, it will also save time by making it easier to find the exact points in the video in which some information has been said. | Regional | Spain | ES | Basque Country | Regional Government | Public order and safety | Law courts | Implemented | 2.023 | Internal management | Internal primary processes | No | No | Artificial Intelligence | G2G | x | x | x | x | x | https://dt4regions.eu/dt-stories/automated-transcripts-speed-judicial-proceedings | Reasoning | Automated reasoning | Natural language processing | Audio processing | 25/10/2023 | ||||||||||||||||
| PSTW-1744 | ISA2 Action 1.7 AI Pilot | https://ec.europa.eu/isa2/sites/isa/files/2018.01_innovative_public_services.pdf | An AI Pilot will tackle the use of machine learning for document review/classification in administrations. The pilot will identify different use-cases in document classification, with a focus on investigative activities, where huge volumes of unstructured data (documents, emails) need to be reviewed by given deadlines to identify documents that are relevant for a particular matter. The AI Pilot will: (i) compare different machine learning algorithms and different model approaches; (ii) evaluate the added value of applying machine learning; (iii) assess the interoperability requirements for operating them, i.e. to integrate and exploit machine learning on top of existing document repository and document review systems; (iv) assess legal and organisational aspects that could result from using machine learning by administrations for document classification | Across Countries | Belgium | BE | EU DG COMP | Central-Government | Economic Affairs | General economic, commercial and labour affair | In development | 2.023 | Analysis, monitoring and regulatory research | Information analysis processes | No | No | Artificial Intelligence | G2G | x | x | x | x | x | https://ec.europa.eu/isa2/sites/isa/files/2018.01_innovative_public_services.pdf | Learning | Machine learning | Natural language processing | Searching | Planning and Scheduling | 25/10/2023 | |||||||||||||||
| PSTW-176 | AI for detecting illegal substances - AI to index seized data carrier | https://www.forensischinstituut.nl/ | The Netherlands Forensic Institute uses AI to index seized data carriers, and search the contents for images containing illegal substances. This accelerates the work of detectives and makes their work more effective and more efficient. Development followed these steps: labeling illegal substances, applying a suitable model architecture (using pre-trained deep learning), fine-tuning (for low-quality pictures). | National | Netherlands | NL | Netherlands Forensic Institute | Central-Government | Public order and safety | Police Services | Implemented | 2.020 | Enforcement | Smart Recognition processes | No | No | Artificial Intelligence | G2G | x | x | x | Survey Use and impact of AI in the public sector. 2021 (https://ai-watch.ec.europa.eu/news/survey-artificial-intelligence-use-public-sector-2021-06-11_en) | Perception | Computer vision | Machine learning | Deep learning | 10/11/2023 | ||||||||||||||||||
| PSTW-1763 | Semantic Analyser – Smart Text Search Engine | https://nio.gov.si/nio/asset/semanticni+analizator+pametni+iskalnik+besedil?lang=en | Every day, civil servants and officials are confronted with many voluminous documents that need to be reviewed and applied according to the information requirements of a specific task. This is the case when making decisions, drafting legislation and policies, reviewing legislation and policies, assessing the impact of legislation and policies, carrying out various analyses, describing data sources and services, and many other tasks. To enhance the processing efficiency and comprehensive analysis of collections, the Ministry of Public Administration of Republic Slovenia, together with the University of Ljubljana, developed a Semantic analyser - an open-source smart engine using AI for text processing in Slovene language. The prototype enables easy and efficient algorithmic processing of large corpuses of documents and texts with finding content similarities using advanced grouping and visualisation. | National | Slovenia | SI | Ministry of Public Administration | Central-Government | General public services | General services. | Implemented | 2.022 | Analysis, monitoring and regulatory research | Information analysis processes | No | No | Artificial Intelligence | G2G | x | x | https://oecd-opsi.org/innovations/semantic-analyser-smart-text-search-engine/ | Communication | Natural language processing | Knowledge representation | text mining | 26/02/2024 | |||||||||||||||||||
| PSTW-177 | Debt relief - Chatbot to assist people with debts | https://nederlandseschuldhulproute.nl/, https://geldfit.nl/ | The goal of this project is to make (local) debt relief easily and quickly accessible to debtors, done partially with a chatbot that helps people with their questions about their debts. There are different entry routes to debt relief. The best next step is determined on the basis of several key questions that determine the best next step for the person in question. This project is the product of a collaboration between IBM and the Rotterdam Municipality. | National | Netherlands | NL | Rotterdam | Local Government | Social protection | Social protection n.e.c. | Implemented | 2.020 | Public services and engagement | Service personalisation (various) | No | No | Artificial Intelligence | G2C | x | x | x | x | Survey Use and impact of AI in the public sector. 2021 (https://ai-watch.ec.europa.eu/news/survey-artificial-intelligence-use-public-sector-2021-06-11_en) | Communication | Natural language processing | Machine learning | chatbot | 10/11/2023 | |||||||||||||||||
| PSTW-1770 | Me@Gis - AI-powered webcams in the Municipality of Messina to enhahnce public security | https://messina.gazzettadelsud.it/articoli/cronaca/2023/11/02/telecamere-con-intelligenza-artificiale-piu-sicurezza-sul-territorio-di-messina-b1e01458-377c-42eb-9daf-ccfe3af2ef71/ | The implementation of surveillance and data/video stream reading systems is planned, with the aim of monitoring and mitigating criminal phenomena that stain the territory and at the same time strengthening the investigative capacity of the police forces. | Local | Italy | IT | Municipality of Messina | Local Government | Public order and safety | Police Services | Pilot | 2.023 | Enforcement | Supporting inspection processes | No | No | Artificial Intelligence | G2G | x | x | x | x | https://messina.gazzettadelsud.it/articoli/cronaca/2023/11/02/telecamere-con-intelligenza-artificiale-piu-sicurezza-sul-territorio-di-messina-b1e01458-377c-42eb-9daf-ccfe3af2ef71/ | Perception | Computer vision | Machine learning | Automated reasoning | 26/02/2024 | |||||||||||||||||
| PSTW-1771 | Vaxjo Kommun chatbot | https://www.vaxjo.se/ | Chatbot for general enquiries on the municipality website. | Local | Sweden | SE | Vaxjo Kommun | Local Government | General public services | General services. | Implemented | 2.024 | Public services and engagement | Service personalisation (various) | No | No | Artificial Intelligence | G2C | x | x | x | x | x | x | https://www.vaxjo.se/ | Communication | Natural language processing | chatbot | 26/02/2024 | ||||||||||||||||
| PSTW-1772 | Syddjurs, DK and neighboring cities map employment service processes with AI-powered platform | https://smartsyddjurs.dk/projekter-initiativer/ai-databaseret-process-mining/ | Syddjurs and four partner cities used artificial intelligence for a process mining initiative. Municipal data on unemployment benefits, city services, and department contacts resulted in maps of user experiences. The resulting platform recommends the optimal path for each resident's employment search based on predictive analytics. Participating municipalities received 4.1 million kroner from a national innovation fund for the project. | Local | Denmark | DK | Municipality of Syddjurs | Local Government | General public services | General services. | Pilot | 2.022 | 2023 | Analysis, monitoring and regulatory research | Prediction and planning | No | No | Artificial Intelligence | G2G | x | x | x | https://digst.dk/digital-transformation/signaturprojekter/ | Planning | Planning and Scheduling | Optimisation | data mining | 26/02/2024 | |||||||||||||||||
| PSTW-1773 | Hertfordshire County Council implemented a AI-powered traffic monitoring platform | https://www.ukauthority.com/articles/failing-fast-for-better-automation-of-traffic-surveys/ | County officials wanted a monitoring solution for automated and standardized data collection. Videos from local traffic cameras are sent through an app built on AWS Amplify to the AWS Rekognition tool for analysis. Traffic types, directions, and speeds are documented before image deletion. Twelve-hour sections of video can be correctly categorized in as little as two hours. The platform is easy to access without training and reduces personnel time spent on traffic counts | Local | United Kingdom | UK | Hertfordshire County Council | Local Government | Public order and safety | Police Services | Implemented | 2.023 | Enforcement | Smart Recognition processes | No | No | Artificial Intelligence | G2G | x | x | x | x | https://govlaunch.com/projects/hertfordshire-county-council-gb-partners-with-aws-on-ai-powered-traffic-monitoring-platform-3hi1m4s1 | Perception | Computer vision | Automated reasoning | image processing | 26/02/2024 | |||||||||||||||||
| PSTW-1775 | Graz outfits intersection with smart sensors to improve cyclist commute | https://www.traffictechnologytoday.com/news/intersections/graz-outfits-intersection-with-smart-sensors-by-lmt-to-improve-cyclist-commute.html | Municipal officials sought a low-cost tool for capturing traffic trends and potential violations. latvian firm LMT's AI-powered platform evaluates video footage and categorizes different types of traffic. This system monitors bus lane use by passenger vehicles, illegal turns, and red-light violations. Light-mounted sensors are installed and maintained without additional construction. Pilot data from a high-traffic intersection will shape Graz's future use of the technology. | Local | Austria | AT | Municipality of Graz | Local Government | Public order and safety | Public order and safety n.e.c. | Implemented | 2.023 | Enforcement | Smart Recognition processes | No | No | Artificial Intelligence | G2G | x | x | x | https://govlaunch.com/projects/graz-ste-tests-lmts-traffic-monitoring-tool-for-improved-road-safety-and-enforcement | Perception | Computer vision | 26/02/2024 | ||||||||||||||||||||
| PSTW-1776 | Staffordshire County Council implemented AI technology for road assessments | https://govlaunch.com/projects/staffordshire-county-council-gb-implements-vaisala-roadai-technology-for-road-assessments | The county's highways team previously used manual inspections and ReportIt submissions for assessments. Highway inspectors now use the Vaisala RoadAI tool on their mobile devices for ongoing evaluations of road conditions. Vaisala RoadAI turns video footage into maps of local roads highlighting defects ranging from potholes to pavement settling. Consistent data on road conditions can be used for faster road repairs and more accurate planning for future projects. | Local | United Kingdom | UK | Staffordshire County Council | Local Government | Economic Affairs | Transport | Implemented | 2.023 | Analysis, monitoring and regulatory research | Information analysis processes | No | No | Artificial Intelligence | G2G | x | x | x | x | https://govlaunch.com/projects/staffordshire-county-council-gb-implements-vaisala-roadai-technology-for-road-assessments | Perception | Computer vision | Machine learning | 26/02/2024 | ||||||||||||||||||
| PSTW-18 | WaterAnalytics - Water quality monitoring | https://www.wateranalytics.eu/ | The Water Development Department in Cyprus is using AI algorithms for the analysis of water monitoring data (such as hydraulics and water quality). | National | Cyprus | CY | The Water Development Department, The Water Development Department, Cyprus | Central-Government | Housing and community amenities | Water supply. | Pilot | 2.018 | 2020 | Analysis, monitoring and regulatory research | Monitoring policy implementation | No | No | Artificial Intelligence | G2G | x | x | x | Mail to AI Watch (25-5-2020), Updated with mail to AI Watch 3-2-2021 | Learning | Machine learning | Optimisation | 06/10/2023 | ||||||||||||||||||
| PSTW-1802 | Chatbot alicante | https://www.suma.es/ | Chatbot on the municipal website answering to general enquiries | Local | Spain | ES | Suma Gestión Tributaria. Diputación de Alicante | Local Government | General public services | General public services n.e.c. | Implemented | 2.024 | Public services and engagement | Service personalisation (various) | No | No | Artificial Intelligence | G2C | x | x | x | x | x | x | https://www.suma.es/ | Communication | Natural language processing | chatbot | 10/01/2024 | ||||||||||||||||
| PSTW-1807 | The Flemish public employment service reinvents orientation tests with AI | https://orientatie.vdab.be/ | VDAB, the Flemish public employment service, worked together with Radix, a Belgium-based company providing AI tools, to update and streamline its orientation test by making use of machine learning. Orient 2.0, a digital and AI-supported tool that creates a personalised orientation test and uses machine learning to predict professional interests. | Regional | Belgium | BE | Flemish public employment service (VDAB) | Regional Government | Social protection | Unemployment. | Implemented | 2.021 | Public services and engagement | Service personalisation (various) | No | No | Artificial Intelligence | G2C | x | x | x | x | x | x | https://radix.ai/cases/flemish-orientation-test-faster-and-more-accessible-than-ever-thanks-to-collaboration-between-radix-and-vdab/ | Reasoning | Machine learning | AI Services | recommender system | 15/01/2024 | |||||||||||||||
| PSTW-181 | Object Detection Kit Amsterdam - Automatic detection of garbage | https://openresearch.amsterdam/nl/page/54917/object-detection-kit, https://www.odk.ai/#/roadmap | Object Detection Kit (ODK) is an open source platform for municipalities, initiated by Amsterdam. Garbage in public spaces is automatically detected. This information is then transmitted to the service responsible for the removal of that kind of garbage. There is a lot of garbage in certain locations in Amsterdam, especially near underground containers. The Amsterdam municipality aims to keep its streets as clean as possible, while employing its garbage removal services as efficiently as possible. ODK detects garbage in public spaces and enables more effective interventions to make sure streets are clean. ODK reduces the impact of garbage on public spaces. Thanks to automatic scanning and reporting, locals don’t need to report as much wrongly placed garbage. | Local | Netherlands | NL32 | City of Amsterdam | Local Government | General public services | Executive and legislative organs, financial and fiscal affairs, external affairs. | Implemented | 2.021 | Enforcement | Smart Recognition processes | No | No | Artificial Intelligence | G2G | x | x | x | x | x | x | Survey Use and impact of AI in the public sector. 2021 (https://ai-watch.ec.europa.eu/news/survey-artificial-intelligence-use-public-sector-2021-06-11_en) | Perception | Computer vision | Machine learning | 10/11/2023 | ||||||||||||||||
| PSTW-1811 | Analyzing Public Sentiment for Statistics Flanders with AI | https://radix.ai/cases/statistiek-vlaanderen/ | Statistics Flanders is the network of Flemish government agencies that develop, produce and publish official statistics. Their goal is to make reliable statistics while utilizing various data sources. They decided to experiment with publicly available data to see how Artificial Intelligence can contribute to producing reliable statistics, for example leveraging on social media data that allows to acquire insights on public sentiment.For example, they wanted to understand how much discomfort was sparked by COVID-19 and how it changed over time and how the Ukrainian war made Flemish citizens feel. The pilot regards consists of an AI-powered dashboard displaying public sentiment on various relevant topics (e.g., Ukrainian War, COVID-19), based on analyzing up to 50k Flemish tweets per month. | Regional | Belgium | BE | Statistics Flanders | Regional Government | General public services | General services. | Pilot | 2.022 | Analysis, monitoring and regulatory research | Information analysis processes | No | No | Artificial Intelligence | G2G | x | x | x | https://radix.ai/cases/statistiek-vlaanderen/ | Reasoning | Automated reasoning | Knowledge representation | sentiment analysis | 15/01/2024 | ||||||||||||||||||
| PSTW-182 | Detection causes early school leavers Kungsbacka - Analysing data of early school leavers | https://www.kungsbacka.se | Utilize AI technology to analyze data concerning students who transition from primary school to upper secondary school without eligibility. Annually, there are approximately 100 students in this category. Discovering the underlying factors of this issue and initiating proactive intervention is of significant interest. Currently, the analysis is limited to grades and is conducted manually. AI technology is expected to uncover additional contributing factors to the problem. This initiative will serve as the inaugural case for the organization, with the intention of expanding the use of AI technology to address other areas. | Local | Sweden | SE | Kungsbacka municipality | Local Government | Education | Pre-primary and primary education. | Pilot | 2.020 | Analysis, monitoring and regulatory research | Prediction and planning | No | No | Artificial Intelligence | G2G | x | x | x | Survey Use and impact of AI in the public sector. 2021 (https://ai-watch.ec.europa.eu/news/survey-artificial-intelligence-use-public-sector-2021-06-11_en) | Learning | Planning and Scheduling | Machine learning | 10/11/2023 | |||||||||||||||||||
| PSTW-1838 | The City of Helsinki is investigating the benefits of generative artificial intelligence in various work tasks | https://www.hel.fi/en/news/the-city-of-helsinki-is-investigating-the-benefits-of-artificial-intelligence-in-various-work-tasks | This year, a group of City of Helsinki employees will experiment with the use of the new Microsoft Copilot artificial intelligence tool. Copilot is an integrated tool for applications in the M365 work environment that uses generative artificial intelligence and machine learning. Copilot can be used to manage files, create presentations and ease email overload, for example. | Local | Finland | FI | City of Helsinki | Local Government | General public services | R&D general public services. | Pilot | 2.024 | Internal management | Internal support processes | No | No | Artificial Intelligence | G2G | x | x | https://www.hel.fi/en/news/the-city-of-helsinki-is-investigating-the-benefits-of-artificial-intelligence-in-various-work-tasks | Learning | Machine learning | Generative AI | 10/04/2024 | ||||||||||||||||||||
| PSTW-185 | IRIS - Support system for classification of citizen inquiries or complaints | https://atencioenlinia.ajuntament.barcelona.cat | IRIS is the service that allows citizens to report incidents or send complaints to the Barcelona City Council for resolution. Through IRIS, citizens can send information and queries, as well as complaints and suggestions for improvement. In this process, the citizen who reports the incident has to classify it using a tree of topics offered through the computer application. This classification is important because it is used to direct the incident directly to the responsible department, thus speeding up the response process. Errors in the thematic classification cause inadequate responses and delays in the resolution of incidents, thus affecting the quality of the service offered. As part of the IRIS service update project, a module called MARIO has been developed, based on machine learning algorithms to simplify the incident classification process for citizens. From the analysis of the free text describing the incident, MARIO suggests to the citizen the most likely categories where the incident fits because he/she chooses the most appropriate category. MARIO, which is currently being tested, minimizes the error rate in the initial classification of incidents by greatly reducing manual reclassification processes. Previously, 50% of the communications made needed to be reassigned; now, with MARIO, a hit rate of over 85% is being achieved. | Local | Spain | ES51 | City of Barcelona | Local Government | General public services | General public services n.e.c. | Implemented | 2.021 | Public services and engagement | Engagement management | No | No | Artificial Intelligence | G2C | x | x | x | x | x | x | Survey Use and impact of AI in the public sector. 2021 (https://ai-watch.ec.europa.eu/news/survey-artificial-intelligence-use-public-sector-2021-06-11_en) | Communication | Natural language processing | Machine learning | Searching | Q&A | 10/11/2023 | ||||||||||||||
| PSTW-1852 | AI-powered “Gestore Emendamenti” (GEM) at the Italian Senate | https://www.ipu.org/innovation-tracker/story/how-ai-helps-italian-senate-manage-amendments | The Italian Senate utilizes an AI system, “Gestore Emendamenti” (GEM), to manage amendments. The system employs text clustering algorithms to quickly identify groups of similarly worded amendments in order to schedule their simultaneous voting. While the system produces near-instant results, staff members review, approve, modify, and integrate the machine-generated analysis to ensure that no decisions are made without human oversight. | National | Italy | IT | Italian Senate | Central-Government | General public services | Executive and legislative organs, financial and fiscal affairs, external affairs. | Implemented | 2.022 | Internal management | Internal primary processes | No | No | Artificial Intelligence | G2G | x | x | x | x | https://static1.squarespace.com/static/60450e1de0fb2a6f5771b1be/t/659d49c8c62d136f72890838/1704806866772/Representative_Bodies_in_the_AI_Era_Vol_1.pdf | Reasoning | Machine learning | Automated reasoning | text classification | 10/04/2024 | |||||||||||||||||
| PSTW-186 | Chatbot Sigma | https://eportugal.gov.pt/en/inicio | Sigma is the chatbot of the portuguese public services portal (eportugal.gov.pt). This chatbot responds, in natural language, to user interactions with the information available on the information pages on public services available on the ePortugal portal. In addition to answer with information, the user can, in a conversation, change his address on the Citizen Card (Portuguese identification document). In the last Portuguese elections, the citizen was able, through a conversation with Sigma, to know where to vote. The administration and configuration of Sigma goes through 3 platforms: (1) LUIS - platform that interprets natural language. When trained, he's able to identify what the user wants to know (intention) about a certain service (entity). (2) QnA - platform where the ePortugal portal services are loaded so that the bot can identify them, and also where chitchat interactions are loaded (quick chat). (3) Cognitive Services APIs Reference - platform where groups of synonyms are loaded in form of keywords to facilitate the bot to interpret a service. | National | Portugal | PT | Agency for Administrative Modernisation - AMA | Central-Government | General public services | Executive and legislative organs, financial and fiscal affairs, external affairs. | Implemented | 2.021 | Public services and engagement | Engagement management | No | No | Artificial Intelligence | G2C | x | x | Survey Use and impact of AI in the public sector. 2021 (https://ai-watch.ec.europa.eu/news/survey-artificial-intelligence-use-public-sector-2021-06-11_en) | Communication | Natural language processing | Searching | chatbot | 10/11/2023 | |||||||||||||||||||
| PSTW-188 | Chatbot Trade Register - Development of Chatbot for Trade Register matters | https://www.prh.fi/en/kaupparekisteri.html | The Finnish Patent Registration Office is currently building a Finnish-speaking chatbot which helps customers with Trade Register matters. | National | Finland | FI | Finnish Patent and Registration Office PRH | Central-Government | Economic Affairs | Economic affairs n.e.c | Implemented | 2.020 | Public services and engagement | Service personalisation (various) | No | No | Artificial Intelligence | G2C | x | x | x | Survey Use and impact of AI in the public sector. 2021 (https://ai-watch.ec.europa.eu/news/survey-artificial-intelligence-use-public-sector-2021-06-11_en) | Communication | Natural language processing | Optimisation | chatbot | 10/11/2023 | ||||||||||||||||||
| PSTW-1884 | Smartmail - intelligent handling of mails | https://digst.dk/digital-transformation/signaturprojekter/ | The project in Norddjurs Municipality aimed to spread a solution that can contribute to reducing case processing times for citizens while simultaneously ensuring transparency in case processing within municipalities by optimizing postal and journaling processes. The project scaled the Smartmail solution to 10 municipalities. Utilizing artificial intelligence, it can deliver mail and emails to the correct recipient within the municipality and journalize these immediately. | Local | Denmark | DK | Norddjurs Municipality | Local Government | General public services | General public services n.e.c. | Pilot | 2.022 | Internal management | Internal support processes | No | No | Artificial Intelligence | G2G | x | x | x | https://digst.dk/digital-transformation/signaturprojekter/ | Reasoning | Automated reasoning | Natural language processing | automatic classification | 02/05/2024 | ||||||||||||||||||
| PSTW-1885 | Decision support for handling municipal document access cases | https://digst.dk/digital-transformation/signaturprojekter/ | The purpose of the project was to create the foundation for increased quality, uniformity and faster internal processing time of cases about document access by making available technical models that can improve the handling of document access. Today, municipalities' processing of document access cases is very resource-intensive. By using artificial intelligence for decision support when processing document access cases, the municipality gets the opportunity to free up resources for, for example, more citizen-related tasks. The project developed a so-called technical natural language process model (NLP), which an read and analyse large amounts of text simultaneously. Thereby, the models can be used for file inspections to efficiently search for files and documents and identify information that should be anonymised. The models can thus contribute to higher quality, uniformity and faster internal processing time of cases about access to documents, where compliance with the GDPR is supported by language technology. | Local | Denmark | DK | Sønderborg Municipality DTU Compute | Local Government | General public services | General public services n.e.c. | Pilot | 2.022 | Internal management | Internal support processes | No | No | Artificial Intelligence | G2G | x | x | x | https://digst.dk/digital-transformation/signaturprojekter/ | Reasoning | Automated reasoning | Natural language processing | text classification | 02/05/2024 | ||||||||||||||||||
| PSTW-1887 | An effective and holistic employment effort through the artificial intelligence technology Process Mining | https://digst.dk/digital-transformation/signaturprojekter/ | The purpose of the project was to create the basis for a more efficient, flexible and holistic effort in the area of employment for the benefit of the citizen by using the technologies Process Mining and Predictive Monitoring. In the project, Process Mining and Predictive Monitoring used existing log files from case-bearing systems, financial systems, etc. to map the citizen's journey through the system from start to finish. It included a mapping of the workflows that make up an employment pathway for insured unemployed and citizens in resource pathways. Including IT systems, departments, teams, employees and relevant efforts. Process Mining was used to create a database-based and comprehensive understanding of which internal and external efforts in the field of employment are actually used and how effective the efforts are towards different citizen groups and the work with the holistic effort. Predictive Monitoring used historical data and Machine Learning to predict which activities and processes should be initiated in order to most effectively get the citizen into employment. | Local | Denmark | DK | Syddjurs Municipality | Local Government | Social protection | Unemployment. | Pilot | 2.022 | Analysis, monitoring and regulatory research | Information analysis processes | No | No | Artificial Intelligence | G2G | x | x | x | x | https://digst.dk/digital-transformation/signaturprojekter/ | Learning | Machine learning | Optimisation | 02/05/2024 | ||||||||||||||||||
| PSTW-1889 | Artificial intelligence to support the visitation of rehabilitation courses (AIR Project) | https://digit.au.dk/research-projects/air | AI-Rehabilitering (AIR) is one of seven government-funded signature projects, that aims to test and evaluate artificial intelligence in a municipal setting. More concretely, the AIR project focuses on the use of artificial intelligence as a tool to support municipal case workers, when they evaluate citizens, that are planned to participate in a rehabilitation course. Artificial intelligence can improve the level of service in the public sector, but there is little experience with such technology in the sector. The Danish Government (Regeringen), KL (Kommunernes Landsforening) and Danish Regions (Danske Regioner) has agreed that Danish municipalities should test artificial intelligence solutions to better understand how these can be utilized to improve the quality and capacity in the public sector in the future. The goal of AIR is to develop a decision-support tool, that can provide case workers with an objective measurement of a citizen’s current eligibility for a certain rehabilitation course, their risk of failing during such a course and an estimate of how well the citizen is thought to do in the course. Current courses span 12 weeks and consist of physical exercises done several times a week by the citizen and evaluated at regular intermediate steps by the care assistant. Performance is measured in terms of improved self-sufficiency and reduced reliance on home help. AIR is anchored in the Municipality of Aalborg and will pave the way for a solution based on models and statistics, that can support the individual professional assessment done by the case worker when it comes to choosing the right course of action of rehabilitation, including specific initiatives, improved utilization of assistive aids and fall prevention. | Local | Denmark | 2.022 | Public services and engagement | Service personalisation (various) | No | No | G2C | x | x | x | https://digst.dk/digital-transformation/signaturprojekter/ | Planning | Planning and Scheduling | Optimisation | |||||||||||||||||||||||||||
| PSTW-189 | Automation of subtitling videos and audios - Improving accessibility of public websites | internal web address | The solution relates to the directive (EU) 2016/2102 of the European Parliament and of the Council of 26 October 2016 on the accessibility of the websites and mobile applications of public sector bodies. The technical solution is intended for subtitling public and internal videos and audios by utilizing Microsoft's Azure cloud computing technology - speech-to-text services and text analytics. The subtitling service is automated in such a way that the user downloads the recording to be subtitled via the web interface and receives an e-mail when the subtitling is completed. The subtitle file (.srt) is returned to the user. | National | Finland | FI | Finnish Tax Administration (FTA) | Central-Government | General public services | Executive and legislative organs, financial and fiscal affairs, external affairs. | Implemented | 2.020 | Internal management | Internal primary processes | No | No | Artificial Intelligence | G2C | x | x | Survey Use and impact of AI in the public sector. 2021 (https://ai-watch.ec.europa.eu/news/survey-artificial-intelligence-use-public-sector-2021-06-11_en) | Perception | Audio processing | Machine learning | 10/11/2023 | ||||||||||||||||||||
| PSTW-1890 | Artificial Intelligence for the prevention of malnutrition and hospitalization of the elderly | https://digst.dk/digital-transformation/signaturprojekter/ | The project aimed to prevent emergency hospital stays by identifying citizens at risk of malnutrition, so that treatment can be initiated in a timely manner. Malnutrition among the elderly is a significant predictor of longer hospital stays, readmissions and mortality. The project can thus contributde to citizens first and foremost receiving better treatment, where efforts against malnutrition are effectively initiated. In the long term, this would lead to citizens with greater self-reliance and an increased quality of life, and in the long term fewer municipal services for personal help. | Local | Denmark | DK | Aarhus University Hospital, Aarhus Municipality,MedTech Innovation Consortium,Regional Hospital Horsens and Skanderborg Municipality | Local Government | Health | Public health services. | Pilot | 2.022 | 2023 | Public services and engagement | Service personalisation (various) | No | No | Artificial Intelligence | G2C | x | x | x | x | https://digst.dk/digital-transformation/signaturprojekter/ | Planning | Planning and Scheduling | Optimisation | Automated reasoning | 06/05/2024 | ||||||||||||||||
| PSTW-190 | Cultural Heritage Tools - AI tools integrated in the National Library of Finland | https://digi.kansalliskirjasto.fi/name-search?set_language=en | Two AI tools have been integrated into the IT system of the National Library of Finland (digi.nationallibrary.fi): 1. Named entity recognition (NER) -Stanford NER software to recognize persons and place names from the Finnish historical newspapers. The first training and evaluation data set was created that consists of pages of both journals and newspapers from the time period 1836–1918. The Stanford NER system was trained using 220 annotated pages and evaluated using 34 pages. The results that were achieved were mostly good: 71 % of person names and 79 % of place names were recognized from the evaluation data. 2. Image classification -Google TensorFlow was used to classify images. A training dataset was created that was used to train the classifier model with TensorFlow. Using the trained model, it was possible to classify images into the following groups: advertisements, drawings, notes, pictures, paintings, maps or garbage. -The trained model was used to classify 50 000 images and its accuracy was about 70-75% when about 10 000 classified images were manually observed. -A graphical user interface was created that enabled an easier way to observe achieved results. | National | Finland | FI | The National Library of Finland | Central-Government | Recreation, culture and religion | Cultural services. | Implemented | 2.020 | Internal management | Internal primary processes | No | No | Artificial Intelligence | G2C | x | x | x | x | Survey Use and impact of AI in the public sector. 2021 (https://ai-watch.ec.europa.eu/news/survey-artificial-intelligence-use-public-sector-2021-06-11_en) | Communication | Natural language processing | Machine learning | text analysis | 10/11/2023 | |||||||||||||||||
| PSTW-191 | Chatbot - Social Insurance Institution of Finland | www.kela.fi/lapsiperheet | Right now the chatbot can answer to questions reqarding family benefits, income support and coronavirus. Chatbot speaks finnish and swedish, and understands english (anwers are given in either finnish or swedish). | National | Finland | FI | Social Insurance Institution of Finland | Central-Government | Social protection | Social protection n.e.c. | Implemented | 2.017 | Public services and engagement | Service personalisation (various) | No | No | Artificial Intelligence | G2C | x | x | x | Survey Use and impact of AI in the public sector. 2021 (https://ai-watch.ec.europa.eu/news/survey-artificial-intelligence-use-public-sector-2021-06-11_en) | Communication | Natural language processing | Searching | Automated reasoning | chatbot | 10/11/2023 | |||||||||||||||||
| PSTW-1910 | How Iceland is using GPT-4 to preserve its language | https://openai.com/customer-stories/government-of-iceland | Iceland partnered with OpenAI to investigate how to improve the Icelandic language abilities of its new model, GPT-4, which was officially announced today. This cooperation results from the visit of the President of Iceland and ministers to the United States in Spring 2022 when, among others, they met Sam Altman, the founder and CEO of OpenAI. One of the key goals of this collaboration was to begin building a resource that could serve to promote the preservation of other low-resource languages, helping to ensure all languages and cultures are represented in digital technologies. | National | Iceland | IS | Language Planning Department of the Government of Iceland | Central-Government | Recreation, culture and religion | Cultural services. | In development | 2.023 | Analysis, monitoring and regulatory research | Innovating Public Policy | No | No | Artificial Intelligence | G2G | x | x | x | https://www.government.is/diplomatic-missions/embassy-article/2023/03/14/Head-start-for-Icelandic/ | Learning | Machine learning | Generative AI | Natural language processing | 01/03/2024 | ||||||||||||||||||
| PSTW-1912 | Better Reykjavik | https://thegovlab.org/static/files/better-reykjavik.pdf | Better Reykjavik is a collaborative initiative between the Citizens Foundation, Reykjavik City, and its residents, aimed at fostering connection, trust, and policy improvement within the community. Serving as a platform for crowdsourcing solutions to urban challenges, it incorporates various democratic functions such as agenda setting, participatory budgeting, and policymaking. The platform uses artificial intelligence and machine learning. Unique features include a distinct debating system, crowd-sourcing capabilities, submission of multimedia content, and extensive utilization of artificial intelligence to enhance user experience and improve submitted content. | Local | Iceland | IS | City of Reykjavik | Local Government | General public services | General public services n.e.c. | Implemented | 2.014 | Public services and engagement | Engagement management | No | No | Artificial Intelligence | G2C | x | x | x | x | x | x | x | x | x | x | https://oecd-opsi.org/innovations/better-reykjavik/ | Learning | Machine learning | Knowledge representation | 06/05/2024 | ||||||||||||
| PSTW-1913 | Generative AI Transformation Project with Derby City Council and ICS.AI | https://www.ics.ai/post/ics-ai-announces-7-million-generative-ai-transformation-project-with-derby-city-council | ICS.AI, a leader in UK public sector AI transformation, accounced its expanded partnership with Derby City Council in an innovative £7 million AI project. This 4-year initiative, launching in 2024, is a pivotal advancement in the Council's strategy, deploying the power of generative AI to transform customer service operations. Across Customer Services, the capabilities of Darcie and Ali, the two digital assistants, will be extended to become generative AI copilots, further streamlining the Council's customer service, and allowing for more complex and nuanced interactions with residents. | Local | United Kingdom | UK | Derby City Council | Local Government | General public services | General public services n.e.c. | Pilot | 2.024 | Public services and engagement | Service personalisation (various) | No | Yes | Artificial Intelligence | G2C | x | x | x | x | x | x | https://govlaunch.com/projects/announcing-7m-generative-ai-transformation-project-with-derby-city-council-and-ics-ai | Learning | Machine learning | Generative AI | 06/05/2024 | ||||||||||||||||
| PSTW-193 | NeRo Chatbot - Chatbot for clients of maternity services | https://digi.hel.fi/english/ds/digital-services-helsinki/child-health-chatbot-247/ | NeRo is an around-the-clock chatbot that answers questions (in Finnish) associated with the health care of infants and small children. NeRo can provide you with information about health issues related to either pregnancy or children’s growth and development. The chatbot can also answer questions about children’s dental care, speech development and nutrition. | Local | Finland | FI1B | City of Helsinki | Local Government | Health | Health n.e.c. | Implemented | 2.019 | Public services and engagement | Engagement management | No | No | Artificial Intelligence | G2C | x | x | Survey Use and impact of AI in the public sector. 2021 (https://ai-watch.ec.europa.eu/news/survey-artificial-intelligence-use-public-sector-2021-06-11_en) | Communication | Natural language processing | Machine learning | chatbot | 10/11/2023 | |||||||||||||||||||
| PSTW-1933 | Bureaucrat on eID website | https://www.kratid.ee/kasutuslood-kratid | The bureaucrat operates on the website of the Information System Authority id.ee and takes on some of the people's inquiries. A bureaucrat is an interoperable network of chatbots on the websites of public authorities, which allows a person to receive information from institutions through colloquial communication through a chat window. He is an opportunity for a person, that is, a user, to use public direct and information services with colloquial communication with the help of virtual assistants. | National | Estonia | EE | Estonian Information System Authority | Central-Government | General public services | General services. | Implemented | 2.023 | Public services and engagement | Engagement management | No | Yes | Artificial Intelligence | G2C | x | x | x | https://www.kratid.ee/kasutuslood-kratid | Communication | Natural language processing | Machine learning | Automated reasoning | chatbot | 04/03/2024 | |||||||||||||||||
| PSTW-1938 | Machine translation customer support communication window on the website of Tartu University Hospital | https://www.kratid.ee/kasutuslood-kratid | On its website, Tartu University Hospital uses a customer support communication window with Askly machine translation, which combines a customer support chat solution, the possibility to send an e-mail and frequently asked questions. | National | Estonia | EE008 | Tartu University Hospital | Local Government | Health | Public health services. | Implemented | 2.023 | Public services and engagement | Engagement management | No | No | Artificial Intelligence | G2C | x | x | x | https://www.kratid.ee/kasutuslood-kratid | Communication | Natural language processing | 04/03/2024 | ||||||||||||||||||||
| PSTW-1939 | Politsei.ee large-language model LLM trained on data | https://www.kratid.ee/kasutuslood-kratid | In order to improve the findability of the necessary information on politsei.ee page, a pilot project was carried out on the data of the State Gazette to train large language models and thus create a customized model. As part of the pilot project, testing was carried out in the Azure Open AI studio. The language model on which the ChatGPT 3.5 Turbo major language model was tested. As a result of the project, it appeared that the model works worse in Estonian than in English, although the input data was in Estonian. | National | Estonia | EE | Ministry of Economic Affairs and Communications | Central-Government | Economic Affairs | Economic affairs n.e.c | Pilot | 2.023 | Internal management | Internal primary processes | No | Yes | Artificial Intelligence | G2G | x | x | x | x | x | https://www.kratid.ee/kasutuslood-kratid | Learning | Machine learning | Generative AI | Natural language processing | 04/03/2024 | ||||||||||||||||
| PSTW-194 | Job Market Finland - Matching employees with right jobs | https://kokeile.tyomarkkinatori.fi/en/Etusivu | Job Market Finland, which is a service developed by KEHA-Centre and the Ministry of Economic Affairs and Employment, is being built up in stages and it will emerge as a new kind of service for the job market, offering a shared platform for public and private suppliers of services for training and for business and industry, and for the jobs offered by various employment exchange platforms. The most important thing in the job market is matching the right employees with the right jobs. The AI-based matching solution matches jobseeker-profiles and job vacancies based on structured information (e.g. skills, occupations) and natural language. The matches are scored and showed to both jobseeker and employer. AI-solution also helps in describing skills needed or provided. | National | Finland | FI | Ministry of Economic Affairs and Employment | Central-Government | Social protection | Unemployment. | Implemented | 2.021 | Public services and engagement | Service personalisation (various) | No | No | Artificial Intelligence | G2C | x | x | x | Survey Use and impact of AI in the public sector. 2021 (https://ai-watch.ec.europa.eu/news/survey-artificial-intelligence-use-public-sector-2021-06-11_en) | Reasoning | Automated reasoning | Searching | 10/11/2023 | |||||||||||||||||||
| PSTW-1942 | Computer Vision for monitoring the condition of streets and the city environment | https://dt4regions.eu/dt-book/dt-solutions/computer-vision-monitoring-condition-streets-and-city-environment | To sort waste, your place for sorting is outside your household. You need an overview of the sorting place, which could be overfilled. So when you take your paper, plastic bottles or glasses and the containers are full, you must take them back or lay them near them, which looks messy and demotivates you from sorting waste. Computer vision model for detecting overflowing containers These detections could be used as information for the people which place for waste separation they can use(is not overflowing). And also for City Service to manage sooner sorted waste disposal. It is using ResNet-32 and Finetune learning. The solution could be extended to other use cases, such as monitoring potholes, broken signs or other street anomalies. Since we didn't have access to the videos from cars, we made Acc 200 images of containers with phones in the streets, and another 100 hundred was obtained from the internet. We prepared a simple frontend application in React using a leaflet framework for monitoring results on the map of the City. | Local | Czechia | CZ | Brno Municipality | Local Government | Environmental Protection | Waste management. | Pilot | 2.023 | Internal management | Internal primary processes | No | Yes | Artificial Intelligence | G2G | x | x | x | https://dt4regions.eu/dt-book/dt-solutions/computer-vision-monitoring-condition-streets-and-city-environment | Learning | Machine learning | 04/03/2024 | ||||||||||||||||||||
| PSTW-1948 | Acquedotto 4.0, Hera invests in artificial intelligence | https://www.firstonline.info/en/acquedotto-4-0-hera-investe-sullintelligenza-artificiale/ | The pilot project Acquedotto 4.0 took place in 3 municipalities in the Emilia-Romagna region. Low-cost sensors were combined with machine learning to monitor the cities' water infrastructure for leaks. It turned out that the water flow has a particular sound, and these sensors can be trained to detect when and where a pipe is leaking. This spares the municipal government from having to tear up the streets and disrupt traffic every time there’s a problem | Local | Italy | IT | City of Rome | Local Government | Housing and community amenities | Water supply. | In development | 2.020 | 2021 | Internal management | Internal support processes | No | Yes | Artificial Intelligence | G2G | x | x | x | https://www.firstonline.info/en/acquedotto-4-0-hera-investe-sullintelligenza-artificiale/ | Learning | Machine learning | Optimisation | 04/03/2024 | ||||||||||||||||||
| PSTW-195 | AI assisted chat service - Chatbot for tax purposes | https://www.vero.fi/sahkoiset-asiointipalvelut/omavero/ | AI assisted chat service provided by Finnish Tax Administration that offers: - Service for individual tax payers: virtual agent advises in most common tax matters. During office hours human agent can be invited into conversation if necessary. - Customer gets a quick reply regardless of time, without any telephone expenses or identification required. - AI assisted chat service uses NLP (natural language processing) to translate customer messages into a format that can be understood by a virtual agent. - AI solution is developed by commercial organisation, whereas governing the virtual agent (AI training, monitoring, and content creation) is done by Finnish Tax Administration chat-product team. | National | Finland | FI | Finnish Tax Administration | Central-Government | Economic Affairs | Economic affairs n.e.c | Implemented | 2.020 | Public services and engagement | Service personalisation (various) | No | No | Artificial Intelligence | G2C | x | x | Survey Use and impact of AI in the public sector. 2021 (https://ai-watch.ec.europa.eu/news/survey-artificial-intelligence-use-public-sector-2021-06-11_en) | Communication | Natural language processing | Searching | chatbot | 10/11/2023 | |||||||||||||||||||
| PSTW-197 | Anomaly detection in e-government administration | https://publications.jrc.ec.europa.eu/repository/handle/JRC134713 | In government administration various critical services are used. In order to maximise these services reability and availability they are introducing various machine learning techniques. They are focusing for the smooth operation of huge amount of services such as in order to minimise the risk of service corruption we are predicting the future load or we are trying to identify the miss usage of a certain services, etc. They are using different algorithms to create models for anomaly detection in order to analyse huge amount of data, which are produced by various general public services used by many people for government administration. | National | Hungary | HU | Idomsoft ZRT | Central-Government | General public services | General services. | In development | 2.021 | Analysis, monitoring and regulatory research | Information analysis processes | No | No | Artificial Intelligence | G2G | x | x | x | x | Survey Use and impact of AI in the public sector. 2021 (https://ai-watch.ec.europa.eu/news/survey-artificial-intelligence-use-public-sector-2021-06-11_en) | Planning | Planning and Scheduling | Machine learning | anomaly detection | 10/11/2023 | |||||||||||||||||
| PSTW-198 | Prediction supply of trucks - Machine Learning to predict truck scheduling | https://www.frontiersin.org/articles/10.3389/ffutr.2022.815267/full | The AI enabled solution (using maching learning), is planned to be used in order to predict the available capacity in trucks scheduled for the next day. This prediction should help to optimize the transport flow. | National | France | FR | La Poste | Central-Government | Economic Affairs | Transport | In development | 2.021 | Analysis, monitoring and regulatory research | Prediction and planning | No | No | Artificial Intelligence | G2B | x | x | x | Survey Use and impact of AI in the public sector. 2021 (https://ai-watch.ec.europa.eu/news/survey-artificial-intelligence-use-public-sector-2021-06-11_en) | Learning | Machine learning | Planning and Scheduling | 10/11/2023 | |||||||||||||||||||
| PSTW-1982 | Central Bohemian Region to test on-demand public transport | https://www.expats.cz/czech-news/article/central-bohemia-to-test-on-demand-public-transportation#:~:text=Prague%20leads%20EU%20in%20public,vehicles%20and%20simplified%20driver%20requirements. | Establishing an innovation partnership to design and deliver a system supporting the optimization of the settings of the transport service system in public transport. The system will use multi-source data aggregation, including big data and access for processing. The partner will develop the system based on the minimum technical conditions specified by the contracting authority. | Regional | Czechia | CZ | The Capital City of Prague | Regional Government | Economic Affairs | Transport | Implemented | 2.020 | Public services and engagement | Service personalisation (various) | No | No | Artificial Intelligence | G2C | x | x | x | x | https://ted.europa.eu/en/notice/-/detail/324287-2020 | Learning | Machine learning | Knowledge representation | big data | 06/03/2024 | |||||||||||||||||
| PSTW-1983 | City of Herne road maintance with AI | https://www.hochtief-pppsolutions.com/news-media/press-release/hochtief-and-the-city-of-herne-launch-innovation-partnership-for-the-future-of-road-maintenance | Innovative hardware and software solution for automated and continuous road condition recording, evaluation, and development. The system will be based on artificial intelligence and will support the maintenance of the municipal transport infrastructure. It aims to identify the optimal time for intervention by continuously assessing road conditions, analyzing damage spread, and considering external influences. The goal is to create a system for optimized maintenance planning. | Local | Germany | DE | City of Herne | Local Government | Economic Affairs | Transport | In development | 2.023 | Internal management | Internal primary processes | No | Yes | Artificial Intelligence | G2G | x | x | x | x | https://ted.europa.eu/en/notice/-/detail/167712-2023 | Perception | Computer vision | Automated reasoning | 06/03/2024 | ||||||||||||||||||
| PSTW-1988 | Automated evaluations of applications at NAV | https://www.nav.no/automatisk-behandling/en | To ensure efficient evaluations of applications, NAV will use automated processing for some benefit applications. This means that a decision of whether to grant the application, and if so, to what extent, will be made without a person having been involved. The applications that will be automated concerns the following areas: child benefit, child maintenance, unemployment benefit, retirement pension, parental benefit and lump-sum grants and care benefits. The system checks to see whether applicants meet the criteria for the application, as defined by relevant laws and regulations. The system then determines whether applicants qualify for the benefit, and if so, the time period they qualify for the benefit, and create a notice of decision. | National | Norway | NO | NAV | Central-Government | Social protection | Social protection n.e.c. | Implemented | 2.024 | Adjudication | Taking decisions on benefits | No | No | Artificial Intelligence | G2G | x | x | x | x | https://www.nav.no/automatisk-behandling/en | Reasoning | Automated reasoning | 06/05/2024 | |||||||||||||||||||
| PSTW-1989 | New AI-Powered Cameras Spot Distracted Drivers in the UK | https://www.advrider.com/new-ai-powered-cameras-spot-distracted-drivers/ | The new type of technology captures footage of passing motorists. The images are processed using artificial intelligence (AI) to analyse whether the motorists could be using a handheld mobile phone or drivers may be without a seat belt. The images are then passed to police for consideration on any action to be taken. Drivers can be fined up to £500 for not wearing a seatbelt in addition to penalty points. While using a mobile phone while driving can result in a fine of up to £1,000 and six penalty points. | National | United Kingdom | UK | UK government’s National Highways | Central-Government | Public order and safety | Police Services | Pilot | 2.024 | Enforcement | Smart Recognition processes | No | No | Artificial Intelligence | G2G | x | x | x | x | https://www.advrider.com/new-ai-powered-cameras-spot-distracted-drivers/ | Perception | Computer vision | image processing | 06/05/2024 | ||||||||||||||||||
| PSTW-199 | a-z.lu to digitise text documents for Luxembourg's National Library | https://bnl.public.lu/en/bnl/innovation-numerique.html | The Bibliothéque Nationale du Luxembourg digitised textual documents by correcting OCR, extracting entities and organising image content. | National | Luxembourg | 2.020 | Internal management | Internal primary processes | No | No | G2G | x | x | x | Survey Use and impact of AI in the public sector. 2021 (https://ai-watch.ec.europa.eu/news/survey-artificial-intelligence-use-public-sector-2021-06-11_en) | Perception | Computer vision | Natural language processing | |||||||||||||||||||||||||||
| PSTW-1993 | Dublin City Council and OpenAI Announce Partnership to Show the Potential of AI to Support Europe’s Tourism Industry | https://www.dublincity.ie/news/dublin-city-council-and-openai-announce-partnership-show-potential-ai-support-europes-tourism | Co-development of a Dublin Itinerary Planner Proof of Concept “A Day in Dublin”: Leveraging the advanced capabilities of GPT-4, this innovative tool will showcase how bespoke travel recommendations can make Dublin's rich cultural heritage and vibrant city life more accessible to visitors. This prototype has been designed to show the potential of generative AI to support unique, bespoke experiences for visitors instead of generic to-do lists. | Local | Ireland | IE | Dublin City Council | Local Government | Recreation, culture and religion | Cultural services. | In development | 2.024 | Public services and engagement | Service personalisation (various) | No | No | Artificial Intelligence | G2C | x | x | x | x | x | x | https://www.dublincity.ie/news/dublin-city-council-and-openai-announce-partnership-show-potential-ai-support-europes-tourism | Learning | Machine learning | Generative AI | 06/05/2024 | ||||||||||||||||
| PSTW-2 | Mona - Public chatbot for companies on the subject of the economy | https://www.usp.gv.at/Portal.Node/usp/public | The new chatbot "Mona" is intended to cover all relevant questions for companies on the subject of the economy, and previously on the corona crisis. The service of the Federal Ministry for Digitization and Business Location (BMDW) is available online on the "Unternehmens Service Portal" (USP, Company service portal ) website and can also be used on mobile devices. The service can be found on the home page of the USP and is intended to provide companies with important information on essential points such as subsidies, labor law matters such as short-time work and teleworking in a simple way during these difficult times . On the one hand, users can ask freely formulated questions, on the other hand there is a classic information channel in which more detailed information is provided step by step on the three central topics of work, financial aspects and research at the click of a mouse. | National | Austria | AT | Unternehmensservice Portal, Austria | Central-Government | General public services | Executive and legislative organs, financial and fiscal affairs, external affairs. | Implemented | 2.020 | Public services and engagement | Engagement management | No | No | Artificial Intelligence | G2C | x | x | x | x | https://oecd-opsi.org/covid-response/infopoint-mona-unternehmensser-viceportal-usp-chatbot/and https://www.usp.gv.at/Portal.Node/usp/public | Communication | Natural language processing | Machine learning | Searching | chatbot | 06/10/2023 | ||||||||||||||||
| PSTW-200 | Kranj Digital Twin - Representation of the city digitally | https://pametnamlaka.3fs.net/ | Digital twin for representing consuming of water, gas, traffic. | Local | Slovenia | SI042 | City Municipality of Kranj | Local Government | General public services | R&D general public services. | Implemented | 2.021 | Analysis, monitoring and regulatory research | Information analysis processes | No | No | Artificial Intelligence | G2G | x | x | x | Survey Use and impact of AI in the public sector. 2021 (https://ai-watch.ec.europa.eu/news/survey-artificial-intelligence-use-public-sector-2021-06-11_en) | Planning | Optimisation | Machine learning | 15/11/2023 | |||||||||||||||||||
| PSTW-201 | AuroraAI - Ministry of Finance | https://vm.fi/en/auroraai-en | Using the AuroraAI service model, organisations from various sectors of society will create a snapshot of well-being to support human-centric activities and knowledge-based management. In finding, allocating and proactively steering services, the model will make use of the decentralised and open network created by artificial intelligence and smart applications. The model will lead changes in the authorities’ operational model and will support these changes by implementing an ethically functioning artificial intelligence network, which will help to allocate the services correctly. In addition to implementing this AI network, the human-centric operations model will be adopted in the case of selected life events, run by the organisations in charge and supported by the AuroraAI support team. Using artificial intelligence, the AuroraAI network will make it possible to allocate the current, partly silo-like supply of services in a timely manner to citizens or companies in need of such services. The information gained about those utilising the service will make knowledge-based management a more effective aid for the production of the services. | National | Finland | FI | Ministry of Finance | Central-Government | General public services | R&D general public services. | In development | 2.021 | Public services and engagement | Service personalisation (various) | No | No | Artificial Intelligence | G2B | x | x | x | x | x | Survey Use and impact of AI in the public sector. 2021 (https://ai-watch.ec.europa.eu/news/survey-artificial-intelligence-use-public-sector-2021-06-11_en) | Learning | Machine learning | Automated reasoning | Knowledge representation | 15/11/2023 | ||||||||||||||||
| PSTW-202 | DBA - Intelligent Control Platform | https://medium.com/urban-ai/ambient-intelligence-and-the-digital-umbrella-1650edbe3732 | The research unit was established in 2017 when put first two AI models into production, in direct integration with an (internal) Control Systems so they are continually evaluating new data. Every time there's a change in our data, it's machine interprets certain thresholds put up for decision support. Intelligent Control. They have about 30 models in production today and are currently implementing their third generation of our platform now called the Intelligent Control Platform. Currently working with real time graph ML and fraud detection and architecting of the data platform supporting this. | National | Denmark | DK | Danish Business Authority | Central-Government | General public services | Executive and legislative organs, financial and fiscal affairs, external affairs. | Implemented | 2.019 | Enforcement | Predictive enforcement processes | No | Yes | Artificial Intelligence | G2G | x | x | Survey Use and impact of AI in the public sector. 2021 (https://ai-watch.ec.europa.eu/news/survey-artificial-intelligence-use-public-sector-2021-06-11_en) | Learning | Machine learning | Automated reasoning | fraud detection | 15/11/2023 | |||||||||||||||||||
| PSTW-2020 | Albania to speed up EU accession using ChatGPT | https://www.euractiv.com/section/politics/news/albania-to-speed-up-eu-accession-using-chatgpt/ | The aim of the project led by the Albanian government, overseen by Prime Minister Rama, is to utilize ChatGPT, an AI language model developed by Mira Murati and her team at OpenAI, to translate and integrate EU legal measures and provisions into Albanian. This initiative seeks to expedite paperwork processes and facilitate quicker accession to the EU for Albania. By leveraging AI technology, the project aims to streamline the alignment of local legislation with EU rules, eliminating the need for extensive manual translation and legal analysis, thus speeding up the process of EU integration. | National | Albania | ALB | Albanian government | Central-Government | General public services | Executive and legislative organs, financial and fiscal affairs, external affairs. | Planned | 2.024 | Analysis, monitoring and regulatory research | Innovating Public Policy | No | No | Artificial Intelligence | G2G | x | x | x | https://www.euractiv.com/section/politics/news/albania-to-speed-up-eu-accession-using-chatgpt/ | Learning | Machine learning | Generative AI | 06/05/2024 | |||||||||||||||||||
| PSTW-205 | Prediction of heart failure from exacerbations in chronic obstructive pulmonary disease (COPD) patients | https://en.digst.dk/media/27445/bilag-2a-knowledge-assessment-of-projects-of-the-national-artificial-intelligence-uptake-fund.pdf | The aim of this project is to prevent exacerbation in chronic obstructive pulmonary disease (COPD) patients as well as patients with heart failure by detecting at-risk patients and initiating early, preventive treatment. By intervening before exacerbation occurs, it is possible to reduce the number of admissions and prevent deterioration. Based on patient reported measurements of blood pressure, oxygen saturation, and heart rate, the algorithm identifies whether there is a risk of exacerbation or heart failure, even before the event occurs. A deterioration in the patient’s condition warns the healthcare professionals and early preventive treatment can be initiated. | Local | Denmark | DK | TeleCare Nord | Local Government | Health | R&D health. | Pilot | 2.020 | 2023 | Analysis, monitoring and regulatory research | Prediction and planning | No | No | Artificial Intelligence | G2G | x | x | x | Mail to AI Watch 15-05-2021 | Planning | Planning and Scheduling | Automated reasoning | 15/11/2023 | ||||||||||||||||||
| PSTW-206 | Artificial Intelligence for faster and better diagnosis of emergency patients | https://en.digst.dk/media/27445/bilag-2a-knowledge-assessment-of-projects-of-the-national-artificial-intelligence-uptake-fund.pdf | To assist healthcare professionals in deciding whether or not to admit an emergency patient a tool that can provide a quick diagnosis of the 15 most common acute illnesses will be developed. This provides better opportunities to differentiate between non-critical patients and critical patients who need hospital admission. Thus, resources can be used better for the benefit of the patients. Based on analyses of blood and urine samples, the algorithm can detect the 15 most critical diagnoses and infections. The algorithm can also rank the probability of these within 60 minutes of the patient's arrival. | Local | Denmark | DK03 | Sugehus Lillebaelt | Local Government | Health | R&D health. | Pilot | 2.019 | 2022 | Internal management | Internal support processes | No | No | Artificial Intelligence | G2C | x | x | x | Mail to AI Watch 15-05-2021 | Planning | Planning and Scheduling | Automated reasoning | 15/11/2023 | ||||||||||||||||||
| PSTW-2066 | Virtual Power Station Optimization in Espoo | https://www.bable-smartcities.eu/it/esplora/prodotti/prodotto/virtual-power-plant-optimization.html | The aim of the project is to implement and demonstrate the effectiveness of Virtual Power Plants (VPPs) in achieving decarbonization and energy efficiency objectives within the smart energy grid. Led by the demonstration in the Leppävaara district of Espoo, Finland, this project is overseen by experts aiming to coordinate local energy resources including generation, storage, and consumption. The focus is on addressing challenges stemming from renewable energy variability, limited energy storage, and insufficient flexibility in energy demand. Key to the project is the development and implementation of advanced forecasting models to optimize energy balance and consumption, particularly in urban environments. | Local | Finland | FI | City of Espoo | Local Government | Economic Affairs | Fuel and energy | In development | 2.024 | Analysis, monitoring and regulatory research | Prediction and planning | No | No | Artificial Intelligence | G2G | x | x | x | https://www.bable-smartcities.eu/it/esplora/prodotti/prodotto/virtual-power-plant-optimization.html | Planning | Planning and Scheduling | Optimisation | 06/05/2024 | |||||||||||||||||||
| PSTW-2068 | AI predicts cardian arrest in Copenhagen | https://healthcaredenmark.dk/media/pramwpdr/white-paper-ems-pdf-uk.pdf | In Copenhagen, the Emergency Medical Services (EMS) has taken a unique approach to increase the recognition of cardiac arrests. An innovative device based on artificial intelligence is trained to identify cardiac arrest from the ongoing calls to 112. By analyzing the call, ‘listening’ for patterns in the dialogue referring to cardiac arrest, it can alert the medical dispatcher who is handling the call. When analyzing the call in real-time, the solution compares the ongoing call to the history of calls and calculates the probability of a cardiac arrest. Currently, the artificial intelligence solution can correctly identify approximately 85 percent of cardiac arrests – compared to approximately 75 percent recognized by medical dispatchers. This translates into 150 more patients now being recognized prior to the ambulance arriving. | Local | Denmark | DK | Copenhagen Emergency Medical Services | Local Government | Health | Hospital services. | Implemented | 2.018 | Analysis, monitoring and regulatory research | Information analysis processes | No | No | Artificial Intelligence | G2G | x | x | x | https://healthcaredenmark.dk/media/pramwpdr/white-paper-ems-pdf-uk.pdf | Communication | Natural language processing | Machine learning | Audio processing | 07/05/2024 | ||||||||||||||||||
| PSTW-207 | Artificial Intelligence in general practice | https://en.digst.dk/media/27445/bilag-2a-knowledge-assessment-of-projects-of-the-national-artificial-intelligence-uptake-fund.pdf | In general practice, physicians need to handle and process a lot of information, including patients’ test results. However, not all test results require action from physicians. By automating the handling of these types of test results, physicians’ attention can instead be allocated to patients and their treatment. The algorithm will support physicians’ work in general practice by, for example, automatically handling received test results or sorting blood test results and making physicians aware of results that require immediate response. | Local | Denmark | DK | Medcom | Local Government | Health | Hospital services. | Pilot | 2.019 | 2021 | Internal management | Internal primary processes | No | No | Artificial Intelligence | G2C | x | x | x | Mail to AI Watch 15-05-2021 | Integration and Interaction | Robotics and Automation | Planning and Scheduling | 15/11/2023 | ||||||||||||||||||
| PSTW-208 | Real-time predictions and essential information for clinicians | https://en.digst.dk/media/27445/bilag-2a-knowledge-assessment-of-projects-of-the-national-artificial-intelligence-uptake-fund.pdf | To manage the planning of staff resources and patient processes information about e.g. discharges and the current occupancy is required. The purpose is to provide health professionals with real-time predictions of the occupancy at the hospital wards. This allows for making better use of the hospital’s capacity and organising patient pathways more efficiently., To manage the planning of staff resources and patient processes information about e.g. discharges and the current occupancy is required. The purpose is to provide health professionals with real-time predictions of the occupancy at the hospital wards. This allows for making better use of the hospital’s capacity and organising patient pathways more efficiently. The algorithm provides predictions for the bed occupancy rate of the hospital wards, the number of discharges and the risk of patient readmission in order to provide a real-time picture of the capacity. | Local | Denmark | DK | Regionshospitalet Randers | Local Government | Health | Hospital services. | Pilot | 2.019 | 2020 | Internal management | Internal support processes | No | No | Artificial Intelligence | G2G | x | x | Mail to AI Watch 15-05-2021 | Planning | Planning and Scheduling | Knowledge representation | 15/11/2023 | |||||||||||||||||||
| PSTW-2084 | SAVIO - Data mining to score sickness certificates for the purpose of controlling their truthfullness | https://www.inps.it/content/dam/inps-site/it/scorporati/circolari-e-messaggi/2024/04/Circolare_14541/Allegati/14885_Messaggio-numero-1384-del-08-04-2024_Allegato-n-1.pdf | The project aims to reactivate the software component SAVIO used for data mining for the scoring of sickness certificates for the purposes of medical check-ups ordered ex officio by the Institute. Workers who apply for sick leave need to do medical check-ups. The data mining component validates their truthfullness. | National | Italy | 2.023 | 2025 | Enforcement | Supporting inspection processes | No | No | G2G | x | x | x | x | DIRETTIVA DEL DIRETTORE GENERALE N. 8 DEL 8 aprile 2024 | Learning | Machine learning | data mining | |||||||||||||||||||||||||
| PSTW-2086 | Calendaring medical examination management, communication and medical examination | https://www.inps.it/content/dam/inps-site/it/scorporati/circolari-e-messaggi/2024/04/Circolare_14541/Allegati/14885_Messaggio-numero-1384-del-08-04-2024_Allegato-n-1.pdf | The aim is the creation of an automated and standardized calendar through the use of artificial intelligence and machine learning algorithms that implement resource management (medical staff, facilities, stocks) and PPC (planning and control) guidelines in order to introduce a new prioritization logic for medical visits and streamline the process. In addition, a procedure for notifying citizens of appointment scheduling and proposing a new calendar through the Institute's various channels is planned. | National | Italy | IT | INPS | Central-Government | Social protection | Sickness and disability. | Planned | 2.024 | Internal management | Internal management processes | No | No | Artificial Intelligence | G2G | x | x | x | x | DIRETTIVA DEL DIRETTORE GENERALE N. 8 DEL 8 aprile 2024 | Learning | Machine learning | Planning and Scheduling | Optimisation | 08/05/2024 | |||||||||||||||||
| PSTW-2087 | Implementation of AI chatbot to guide the compilation of UNIEMENS flows | https://www.inps.it/content/dam/inps-site/it/scorporati/circolari-e-messaggi/2024/04/Circolare_14541/Allegati/14885_Messaggio-numero-1384-del-08-04-2024_Allegato-n-1.pdf | The aim of the project is to develop an AI-based chatbot that can support employers and intermediaries in the correct compilation of UNIMENS, a compulsory report sent monthly to INPS by private sector employers which act as tax substitutes. The aim is to provide guidance on compilation, rules, reference regulations and underlying controls in order to improve transparency, guide the user in information and operational activities and reduce compilation errors. | National | Italy | IT | INPS | Central-Government | Social protection | Social protection n.e.c. | Planned | 2.024 | Public services and engagement | Service personalisation (various) | No | No | Artificial Intelligence | G2B | x | x | x | x | x | x | DIRETTIVA DEL DIRETTORE GENERALE N. 8 DEL 8 aprile 2024 | Communication | Natural language processing | AI Services | chatbot | 08/05/2024 | |||||||||||||||
| PSTW-209 | Better diagnosis of prostate cancer | https://en.digst.dk/media/27445/bilag-2a-knowledge-assessment-of-projects-of-the-national-artificial-intelligence-uptake-fund.pdf | Prostate cancer is often diagnosed at such an early stage that the cancer has not yet spread from the prostate. However, the vast majority of patients still have their prostate removed, which causes discomforts or complications. The project will develop a solution that can assess the risk of the cancer spreading, ensuring the patient does not undergo unnecessary surgery. Based on data from previous disease patterns, the algorithm will assess the risk of the cancer spreading from the prostate. The result will support the medical assessment of which patients need surgery to avoid the formation of metastases and which patients can be exempted from surgical treatment. | Local | Denmark | DK031 | Odense Universitetshospital | Local Government | Health | R&D health. | Pilot | 2.019 | 2023 | Internal management | Internal support processes | No | No | Artificial Intelligence | G2G | x | x | x | Mail to AI Watch 15-05-2021 | Planning | Planning and Scheduling | Optimisation | 15/11/2023 | ||||||||||||||||||
| PSTW-2098 | Autonomous Inspection service - Monitoring Work Zones for Bizkaia Regional Council and Interbiak | https://asimob.es/en/references/ | The spanish company ASIMOB develops AI-driven solutions to increase road safety and management. Their Autonomous Road Inspector monitors road asset, transitioning from manual inspections to regular, automated checks. The inspector evaluates the status of traffic signs, road markings, and protective barriers, predicts road deterioration, supervises construction zones, and alerts to slippery conditions and other driving hazards. This pilot test was implemented with the Bizkaia Regional Council. | Regional | Spain | ES | Bizkaia Regional Council | Regional Government | Economic Affairs | Transport | Pilot | 2.023 | 2024 | Enforcement | Supporting inspection processes | No | No | Artificial Intelligence | G2G | x | x | x | x | x | x | Self-reporting tool | Perception | Computer vision | Machine learning | image processing | 16/04/2024 | ||||||||||||||
| PSTW-21 | Erhvervsstyrelsen - Detection of errors in business statements | https://datacvr.virk.dk/data/offentliggorelse?dl_ref=ZG9rdW1lbnRsYWdlcjovLzAzLzdkLzJlL2U3LzM4LzFkZWUtNGVlYy04YThmLTUzODk3OTlmNjAwMw | A project by the Danish Business Authority (Erhvervsstyrelsen) to use ML to identify fraud and highlight material errors in financial statements. | National | Denmark | DK | Danish Business Authority | Central-Government | Economic Affairs | General economic, commercial and labour affair | Implemented | 2.017 | Enforcement | Supporting inspection processes | No | No | Artificial Intelligence | G2B | x | x | x | https://joinup.ec.europa.eu/sites/default/files/custom-page/attachment/2020-07/Study%20on%20public%20sector%20data%20strategies%2C%20policies%20and%20governance%20%E2%80%93%20ANNEX%20Case%20studies.pdf | Learning | Machine learning | Automated reasoning | 06/10/2023 | |||||||||||||||||||
| PSTW-210 | Artificial Intelligence for better planning of cancer treatments | https://en.digst.dk/media/27445/bilag-2a-knowledge-assessment-of-projects-of-the-national-artificial-intelligence-uptake-fund.pdf | The purpose of the project is to be able to stratify cancer patients and identify high-risk and low-risk patients. This allows for better adaptation of patient treatment plans. It will be possible to optimize the use of resources and offer treatment for the benefit of the individual patient., The purpose of the project is to be able to stratify cancer patients and identify high-risk and low-risk patients. This allows for better adaptation of patient treatment plans. It will be possible to optimize the use of resources and offer treatment for the benefit of the individual patient. The project will use Artificial Intelligence to offer a more individualised and risk-based cancer treatment. The algorithm will, among other things, divide patients into high-risk and low-risk groups in order to be able to adapt the treatment to the individual’s needs. | Local | Denmark | DK | Rigshospitalet | Local Government | Health | R&D health. | Pilot | 2.020 | 2022 | Internal management | Internal support processes | No | No | Artificial Intelligence | G2G | x | x | x | Mail to AI Watch 15-05-2021 | Planning | Planning and Scheduling | Automated reasoning | 15/11/2023 | ||||||||||||||||||
| PSTW-2100 | Municipality of Messina pilots the Recycleye robot to select garbage and improve reciclying | https://messina.gazzettadelsud.it/articoli/cronaca/2024/04/10/intelligenza-artificiale-svolta-innovativa-a-messinaservizi-ecco-il-robot-recycleye-af13c954-2c02-4300-8ff4-ad395457213a/ | Messinaservizi Bene Comune and Recycleye started a collaboration aimed at installing an artificial intelligence-managed waste sorting robot, the first of its kind in Sicily, at the Pace sorting centre. Recycleye is a robotic system equipped with artificial intelligence that will be used for the selection of specific classes of materials, capable of picking with high granularity and continuity, 24 hours a day, 7 days a week, guaranteeing cost containment and bringing added value to the treated flows. | Local | Italy | IT | Municipality of Messina | Local Government | Environmental Protection | Waste management. | Implemented | 2.024 | Internal management | Internal primary processes | No | No | Artificial Intelligence | G2G | x | x | x | x | https://www.rainews.it/tgr/sicilia/articoli/2024/04/messina-intelligenza-artificiale-dei-robot-per-la-selezione-dei-rifiuti-1a0748a4-ea5f-4f72-a4ff-8f3fa12531ff.html#:~:text=Un%20robot%2C%20gestito%20dall'intelligenza,Centro%20di%20selezione%20di%20Pace. | Integration and Interaction | Robotics and Automation | service robot | 10/04/2024 | ||||||||||||||||||
| PSTW-2106 | Controlling and balancing public power grids with AI: TenneT usecase | https://www.aihub-oost.nl/en/news/how-the-grid-keeps-becoming-smarter | TenneT will renew the (IT) systems that it uses for controlling and balancing its grids in the period 2021-2031. In connection with this renewal, TenneT expects to be needing extensive external expertise, related to existing and new technologies and ways of working, in particular related to the challenges that TenneT faces in the energy transition.The subject of this tender is a Dynamic Purchasing System (DPS) for 'EMS/SCADA expertise and tool development'. In particular, this refers to expertise (including the development of algorithms and IT Tools) related to the control and balancing of the electricity transmission grid as operated by TenneT. | National | Netherlands | NL | TenneT TSO B.V. | Central-Government | Economic Affairs | Fuel and energy | Implemented | 2.022 | Internal management | Internal primary processes | No | No | Artificial Intelligence | G2G | x | x | x | https://ted.europa.eu/udl?uri=TED:NOTICE:226573-2021:TEXT:EN:HTML | Reasoning | Automated reasoning | Planning and Scheduling | 08/03/2024 | |||||||||||||||||||
| PSTW-211 | Artificial Intelligence to prevent complications after bowel cancer surgery | https://en.digst.dk/media/27445/bilag-2a-knowledge-assessment-of-projects-of-the-national-artificial-intelligence-uptake-fund.pdf | One in four bowel cancer patients develops complications after surgery, and one in three experiences relapse. The purpose is to identify patients at high risk of complications, death, or relapse after bowel cancer surgery. The treatment plan can thus be adapted in advance, reducing the risk after the operation., One in four bowel cancer patients develops complications after surgery, and one in three experiences relapse. The purpose is to identify patients at high risk of complications, death, or relapse after bowel cancer surgery. The treatment plan can thus be adapted in advance, reducing the risk after the operation.The algorithm is trained using health registry data on bowel cancer patients. The model is embedded in a software module, and is to be used with data from the individual patient to estimate risk of death, complications, readmission, re-operation, etc. | Local | Denmark | DK02 | West Zealand Region | Local Government | Health | R&D health. | Pilot | 2.019 | 2023 | Internal management | Internal support processes | No | No | Artificial Intelligence | G2G | x | x | x | Mail to AI Watch 15-05-2021 | Planning | Planning and Scheduling | Machine learning | 15/11/2023 | ||||||||||||||||||
| PSTW-212 | Reduction of radiation dose in relation to scans used in cancer treatment | https://en.digst.dk/media/27445/bilag-2a-knowledge-assessment-of-projects-of-the-national-artificial-intelligence-uptake-fund.pdf | In PET scans, a radioactive tracer is injected into the patient. Higher doses of tracer provide a clearer scan image. However, the radiation dose may increase the risk of cancer development later on. The purpose is to reduce the radiation dose without reducing the quality of the scan image. This can reduce the risk of cancer and the cost of the radioactive tracer. The algorithm processes scan images produced using a reduced radiation dose. Reducing the radiation dose increases the amount of noise in the image. The algorithm reduces this noise and the image can therefore still be used for diagnostics. | Local | Denmark | DK | Rigshospitalet | Local Government | Health | Hospital services. | Pilot | 2.019 | 2023 | Analysis, monitoring and regulatory research | Information analysis processes | No | No | Artificial Intelligence | G2G | x | x | Mail to AI Watch 15-05-2021 | Perception | Computer vision | Optimisation | 15/11/2023 | |||||||||||||||||||
| PSTW-213 | AI-Rehabilitering (AIR) - Intelligent rehabilitation and targeted healthcare services for citizens | https://www.aalborg.dk/om-kommunen/presse-og-kommunikation/nyheder/kunstig-intelligens-skal-styrke-genoptraening-af-borgere-i-aalborg | Not all citizens who could potentially benefit from physical exercise treatment are offered this at the optimal time. The goal of AIR is to develop a decision-support tool, that can provide case workers with an objective measurement of a citizen’s current eligibility for a certain rehabilitation course, their risk of failing during such a course and an estimate of how well the citizen is thought to do in the course. AIR is anchored in the Municipality of Aalborg and will pave the way for a solution based on models and statistics, that can support the individual professional assessment done by the case worker when it comes to choosing the right course of action of rehabilitation, including specific initiatives, improved utilization of assistive aids and fall prevention. | Local | Denmark | DK050 | Municipality of Aalborg | Local Government | Health | Public health services. | Pilot | 2.020 | 2021 | Analysis, monitoring and regulatory research | Prediction and planning | No | No | Artificial Intelligence | G2G | x | x | x | Mail to AI Watch 15-05-2021 | Planning | Automated reasoning | Knowledge representation | 15/11/2023 | ||||||||||||||||||
| PSTW-214 | Faster case processing when granting cleaning services using new technology | https://en.digst.dk/media/27445/bilag-2a-knowledge-assessment-of-projects-of-the-national-artificial-intelligence-uptake-fund.pdf | When deciding whether to provide cleaning assistance for citizens, the caseworker must assess the individual citizen's needs. However, there is great variation in how demanding each case is to process. The purpose of the project is to increase the quality of the process for the citizen and to free up resources for complicated cases that require more attention. The algorithm will serve as a decision support tool for the caseworker in questions of whether a citizen should be granted cleaning services. The algorithm will base this on structured data regarding e.g. the citizen's condition, housing situation, and potential cohabitants. | Local | Denmark | DK032 | Esbjerg Kommune | Local Government | General public services | General public services n.e.c. | Pilot | 2.020 | 2021 | Adjudication | Taking decisions on benefits | No | No | Artificial Intelligence | G2G | x | x | x | x | x | x | Mail to AI Watch 15-05-2021 | Reasoning | Automated reasoning | Knowledge representation | decision support | 15/11/2023 | ||||||||||||||
| PSTW-215 | Intelligent sorting and filing of mail to provide citizens with faster case processing | https://en.digst.dk/media/27445/bilag-2a-knowledge-assessment-of-projects-of-the-national-artificial-intelligence-uptake-fund.pdf | Every day, Norddjurs Municipality receives large amounts of digital mail and emails into a main inbox. The mail must be sorted and sent out to relevant case-workers and filed. These are resource-intensive and routine tasks. By automating these tasks, the municipality can free up resources and shorten the case-processing time for citizens. The algorithm sorts incoming mail - both emails and digital mail. The algorithm then automatically distributes the mail to the right recipients. The algorithm will also be able to automatically file incoming mail. | Local | Denmark | DK042 | Norddjurs Municipality | Local Government | General public services | General services. | Pilot | 2.020 | 2021 | Internal management | Internal primary processes | No | No | Artificial Intelligence | G2G | x | x | x | x | Mail to AI Watch 15-05-2021 | Perception | Automated reasoning | Robotics and Automation | automatic classification | 15/11/2023 | ||||||||||||||||
| PSTW-2152 | Titormos - the citizens assist chatbot in the Municipality of Agrinio | https://www.agrinio.gr | "Titormos", from an ancient local hero of the city of Agrinio in Greece, is the new chatbot available on the municipality's official website. The Municipality of Agrinio is a municipality with a wide geographical span which includes both mountainous and lowland areas with different problems emerging. Prior to Titormos, citizens could only submit requests by calling a phone number during limited working hours on weekdays. With this specific solution, citizens can be informed about information concerning the city but also, most importantly, submit a problem that concern them and is of a local nature in matters of cleanliness, such as garbage collection, matters of city lighting, policing, management of stray animals, complaints, etc. After collecting the necessary information, Titormos saves it and displays the ticket – request ID and sends a relevant confirmation email. The bot is also connected to chatgpt and can answer free form questions from citizens. Finally, in the future, there will be a different version for city administrators such as the Mayor, which will be able to connect the chatbot directly to the database of requests and also to the Human Recourses (HR) database via AI, so that it can accept questions in natural language and give administrative responses such as request statistics. Also, for citizens who do not have access to or do not use computers, a voice portal for Citizens who can also submit a request and receive relevant information has been created and is active. | Regional | Greece | EL | Municipality of Agrinio | Regional Government | General public services | General services. | Pilot | 2.024 | Public services and engagement | Service personalisation (various) | No | No | Artificial Intelligence | G2C | x | x | x | x | x | x | x | Self-reporting tool | Communication | Natural language processing | Generative AI | Machine learning | chatbot | 29/05/2024 | |||||||||||||
| PSTW-2153 | Large-scale high-engagement citizen participation with generative AI | https://innovationorigins.com/en/eindhoven-pioneers-with-ai-driven-city-consultation/ | Enabling more citizen participation in governmental decision making could increase the quality of decisions. It is in any case likely to increase their adoption, if participation was genuinely conducted in pursuit of the best possible decision for the greatest public interest. Using ChatGPT a consortium from Eindhoven, The Netherlands, created an AI-mediated engagement app. This project was financed with $100k by OpenAI, after having been selected as one of out 10 projects from over 860 project submissions. After having conducted an initial trial during development with 450 people, it was launched as the start of a new type of city consultation in Eindhoven on 22-02-2024. Currently the EIndhoven library and the biggest youth center are supporting new events, aiming for a decision in December '24 on the city consultation becoming a monthly opportunity or people to discuss matters close to their heart. | Local | Netherlands | NL | Municipality of Eindhoven | Local Government | General public services | Executive and legislative organs, financial and fiscal affairs, external affairs. | Implemented | 2.024 | 2024 | Public services and engagement | Engagement management | No | No | Artificial Intelligence | G2C | x | x | x | x | x | x | x | x | Self-reporting tool | Communication | Natural language processing | Generative AI | Machine learning | 29/05/2024 | ||||||||||||
| PSTW-2155 | MODUL-F: empowering public administration through low-code/no-code | https://www.digitale-verwaltung.de/Webs/DV/DE/onlinezugangsgesetz/rahmenarchitektur/basisdienste-basiskomponenten/modul-f/modul-f-node.html | MODUL-F (Modular Solution for IT Specialist Procedures) is a rule-based platform that accelerates and simplifies internal administrative digitisation in Germany. Software applications specially developed for the internal public administration, the so-called IT specialist procedures, are intended to replace analogue administrative services. Thanks to its no-code approach, the platform enables easy creation of IT specialist procedures following the modular construction principle. Thereby, specialist procedures are created using pre-programmed modules and reused across different administrative entities. The platform is a cloud-based software-as-a-service solution, offered nationwide to all administrations (federal, state, and local). The aim of the platform thus is to support administrative staff digitally and to further promote end-to-end digitisation in public administration, based on the German Online Access Act (OZG). | Regional | Germany | DE | Senatskanzlei Hamburg | Regional Government | General public services | General public services n.e.c. | Implemented | 2.023 | Internal management | Internal support processes | No | Yes | Artificial Intelligence | G2G | x | x | x | Self-reporting tool | Integration and Interaction | Robotics and Automation | 07/10/2024 | ||||||||||||||||||||
| PSTW-2156 | "Responsible use of AI"- pilot project to enhahnce environmental monitoring within the Province of Fryslân in collaboration with Rijks ICT Gilde and the Z-Inspection® Initiative | https://www.rijksorganisatieodi.nl/rijks-ict-gilde/mycelia/pilot-kunstmatige-intelligentie | A pilot project investigating AI in environmental monitoring was conducted from May 2022 to January 2023. The project involved a collaboration between the Province of Friesland, Rijks ICT Gilde (part of the Ministry of the Interior and Kingdom Relations), and members of the Z-Inspection® Initiative. The focus of the pilot was to evaluate the practical application of a deep learning algorithm developed by the province of Friesland. This AI tool utilized satellite imagery to map heathland grasslands within nature reserves, aiding in their monitoring and preservation. Environmental monitoring plays a crucial role in various societal activities, from ensuring water quality standards to quantifying carbon emissions. Satellite imagery combined with machine learning is emerging as a valuable tool in this field, supporting informed decision-making. The pilot project contributed to the responsible development and implementation of AI technologies in environmental monitoring. | Local | Netherlands | NL | Province of Fryslân and Rijks ICT Gilde | Local Government | Environmental Protection | Environmental protection n.e.c. | Pilot | 2.022 | 2023 | Analysis, monitoring and regulatory research | Monitoring policy implementation | No | No | Artificial Intelligence | G2C | x | x | x | x | x | x | Self-reporting tool | Perception | Computer vision | Machine learning | Deep learning | 28/06/2024 | ||||||||||||||
| PSTW-2159 | AI4Justice, Intelligent assistant to support judges in drafting sentences by locating texts of previous judgments and jurisprudence | https://innobuyer.eu/selected_projects/ai-for-justice/ | The time dedicated by judges to search for precedents and legal foundations to write a sentence is high and an impediment to being more agile in the drafting of sentences, causing a high response time and a sense of slow justice. Currently, the location of paragraphs of interest of legal or procedural references, of any documentary information or the entirety of the magistrates' own judgments or resolutions previously issued, which may be applicable or reusable in the drafting of new judgments or resolutions, becomes a manual and costly process that causes magistrates to spend a lot of time locating, remembering, and reviewing previous judgments, relying on their memory, both for their content and the date they were issued. In Catalonia, the judge usually performs a manual search in the procedural management application for justice (eJusticia.cat), in the archive of the magistrate's own judgments, or through the Judicial Documentation Center (CENDOJ), depending on the General Council of the Judiciary (CGPJ), as well as other repositories or jurisprudential databases. The search is more or less effective depending on what the magistrate remembers at that time from similar cases or parts of an old judgment that may be applicable to the current one. The unmet need is to locate reusable information within judicial documents, such as sentences issued in any instance and jurisdiction, in order to speed up and facilitate the drafting of new sentences by judges. Currently, the location of paragraphs of interest (headings, legal foundations, dispositive part or judgment), legal or procedural references or the entirety of the judges' previous sentences, that are applicable or reusable in the drafting of new sentences, becomes a manual and costly process that causes judges to spend a lot of time locating, remembering and reviewing previous judgments, based on memory, both of their content and of the date they were issued. The solution proposed is an assistant to judges and magistrates that, by entering an open text or prompt, can quickly, accurately, and relatedly obtain all applicable historical information for the sentence being drafted. In the same way, the assistant must provide the applicable legal foundations and sentence draft for a better management of mass litigation cases with hundreds of very similar claims accumulate that has also similar resolutions. It is important that the judicial powers have the necessary resources to ensure agile and efficient justice, such as having digital tools that facilitate the location of reusable information from previous sentences and jurisprudence to draft new sentences. | Regional | Spain | ES | Centre de Telecomunicacions i Tecnologies de la Informació de la Generalitat de Catalunya (CTTI) | Regional Government | Public order and safety | Law courts | In development | 2.024 | Analysis, monitoring and regulatory research | Innovating Public Policy | No | No | Artificial Intelligence | G2G | x | x | x | x | Self-reporting tool | Communication | Natural language processing | Automated reasoning | Knowledge representation | 30/07/2024 | |||||||||||||||||
| PSTW-216 | Shorter response time to construction applications and help submitting correct documents | https://en.digst.dk/media/27445/bilag-2a-knowledge-assessment-of-projects-of-the-national-artificial-intelligence-uptake-fund.pdf | Construction applications often have long case-processing times. Additionally, many applications are filled in incorrectly, prolonging case-processing times. The purpose of the project is to reduce the case-processing time by screening the applications for errors and presenting the case workers with information on decisions in previous and similar cases.The algorithm will be a decision support tool for caseworkers processing construction applications. The algorithm will present decisions from previous, comparable cases and thus support the case workers in their assessment and decision. | Local | Denmark | DK01 | Kobenhavns Kommune | Local Government | Housing and community amenities | Housing development. | Pilot | 2.020 | 2021 | Internal management | Internal primary processes | No | No | Artificial Intelligence | G2G | x | x | Mail to AI Watch 15-05-2021 | Learning | Machine learning | Automated reasoning | anomaly detection | 15/11/2023 | ||||||||||||||||||
| PSTW-2161 | Application of Generative AI to the Generalitat de Catalunya to facilitate citizens' understanding of legal texts | https://govern.cat/salapremsa/notes-premsa/622202/el-govern-utilitza-el-llenguatge-planer-per-facilitar-la-comprensio-dels-textos-juridics-a-la-ciutadania | In the legal field, the Autonomous Entitat Autònoma del Diari Oficial i de Publications (EADOP) has as its mission, on the one hand, the official publication, through the DOGC, of the laws of the Generalitat of Catalonia, of the general provisions issued by the Government and the Administration of the Generalitat, and also of acts, announcements and other documents of the Generalitat and of other entities or persons, when it corresponds in accordance with the legal system. On the other hand, it is the mission of the 'EADOP to contribute to the knowledge and dissemination of current law applicable in Catalonia. Very often, legal language is a barrier that prevents citizens from easily understanding legal texts. To eliminate this obstacle, the Government makes available to users of the Legal Portal of Catalonia and to the general public the summaries of Catalan law rules in plain language obtained from generative artificial intelligence. It is already available in, the Legal Portal of the Generalitat of Catalonia summaries of the rules of Catalan law prepared with generative artificial intelligence. Artificial intelligence (AI) generated summaries of legal documents are provided for informational purposes only and should not be considered legal advice. These summaries are unofficial and do not replace information published in official newspapers and bulletins. They may contain expressions susceptible to linguistic improvement. | Regional | Spain | ES | Autonomous Entitat Autònoma del Diari Oficial i de Publications (EADOP) | Regional Government | Public order and safety | Law courts | Implemented | 2.024 | Public services and engagement | Service personalisation (various) | No | No | Artificial Intelligence | G2C | x | x | x | x | x | x | Self-reporting tool | Learning | Machine learning | Generative AI | 30/07/2024 | ||||||||||||||||
| PSTW-2162 | Mapping Portugal: leveraging Machine Learning for land registration | https://tek.sapo.pt/multimedia/artigos/tecnologia-ao-servico-do-registo-de-terrenos-para-conhecer-mais-e-melhor-o-territorio-portugues | The BUPi project modernises Portuguese property management by making property information accessible, improving market efficiency, and supporting sustainable development. It addresses challenges such as lack of information about rural properties, encourages participation in public initiatives, and ensures widespread adoption. BUPi also promotes partnerships and reduces geographic disparities. Machine learning enhances BUPi's accuracy and efficiency, enabling precise property identification and quick processing of data. It improves land management, facilitates access to information, and promotes transparency. It automates processes, enhances data quality, and provides actionable insights for strategic decisions. Practical examples include property identification, anomaly detection, and land use classification. Overall, machine learning significantly benefits BUPi's accuracy, efficiency, and quality, facilitating better territory management and understanding. | National | Portugal | PT | Ministry of Justice and Ministry of Territorial Cohesion | Central-Government | General public services | General public services n.e.c. | Implemented | 2.017 | Public services and engagement | Service personalisation (various) | No | No | Artificial Intelligence | G2G | x | x | x | Self-reporting tool | Reasoning | Machine learning | Automated reasoning | 31/07/2024 | |||||||||||||||||||
| PSTW-2163 | Using Artificial Intelligence to detect and predict river overflows | https://govern.cat/salapremsa/notes-premsa/620482/govern-utilitza-tecnologia-robotica-ia-analitzar-qualitat-laigua-lembassament-sau-predir-zones-inundables-al-riu-tordera | The main objective of this initiative is to improve decision-making in emergency planning using AI algorithms applied to combined datasets that include flow information and geospatial data. Specifically, this project aims to investigate the feasibility of using artificial intelligence (AI) algorithms to simulate or estimate flood risks in a more computationally efficient way than traditional mathematical and hydraulic models. It focuses on assessing the ability of AI to provide agile real-time predictions of possible flooding in river basins, particularly for this proof of concept, initially the Tordera river basin has been chosen. Although in later phases the model has been scaled up to other river basins. | Regional | Spain | ES | Centre de Telecomunicacions i Tecnologies de la Informació de la Generalitat de Catalunya (CTTI) | Regional Government | Environmental Protection | Environmental protection n.e.c. | Pilot | 2.024 | Analysis, monitoring and regulatory research | Prediction and planning | No | No | Artificial Intelligence | G2G | x | x | Self-reporting tool | Perception | 31/07/2024 | ||||||||||||||||||||||
| PSTW-2165 | Streamlining administrative tasks through robotic process automation in the administration of Justice | https://www.mjusticia.gob.es/es/institucional/gabinete-comunicacion/noticias-ministerio/Premio-transformacion-digital | This initiative applies Robotic Process Automation (RPA) to allow repetitive to be carried out quickly and automatically, accelerating the processing of procedures, such as delays in granting nationality and late cancellations of criminal records. | National | Spain | ES | Ministerio de la Presidencia, Justicia y Relaciones con las Cortes | Central-Government | General public services | General services. | Implemented | 2.021 | Internal management | Internal primary processes | No | No | Artificial Intelligence | G2G | x | x | x | x | x | Self-reporting tool | Integration and Interaction | Robotics and Automation | 07/10/2024 | ||||||||||||||||||
| PSTW-2168 | Boosting efficiency and transparency in processing of Official Publications with AI tools - AI for summaries | https://cido.diba.cat/media/pdf/IA_anuncis_oficials_SBOPiDiPO.pdf | To enhance efficiency and transparency, SBOPiDiPO has implemented solutions such as the CIDOBOT and the automation of summaries of publications from the Official Barcelona Provincial Gazette (BOPB), optimizing processes and improving public services. The SBOPiDiPO ensures access to public information, contributing to transparency in compliance with the state (Law 19/2013) and Catalan (Law 19/2014) transparency laws. The service is provided through the BOPB and the Official Information and Documentation Searcher (CIDO). The BOPB is the official journal where the provisions and official acts of the public administrations of Barcelona are published. Since 1998, universal and free access to the electronic edition of the bulletin has been guaranteed. The CIDO disseminates information from Catalan public administrations, ensuring transparency by publishing official data and allowing the public to know the status and stage of regulations and public procedures. Among the AI solutions implemented, a system that automatically generates summaries of official publications for the BOPB stands out. Using supervised machine learning techniques and neural networks, the system has been trained with 275,000 publications published between 2013 and 2022. This system generates summaries of up to 100 words for publications in Catalan or Spanish and records manual modifications to improve accuracy. The AI solutions have significantly improved the quality and efficiency of public services, optimizing the processes of summary writing and publication classification, reducing time and effort. Furthermore, they have increased governmental openness and transparency, facilitating access to information and improving the user experience. These technologies are scalable and replicable, allowing their adaptation in other environments, contributing to the modernization and improvement of administrative processes. In conclusion, the adoption of AI solutions by SBOPiDiPO of the Barcelona Provincial Council has represented a significant advance in the modernization of administrative processes, improving the quality and efficiency of public services and increasing transparency and access to public information. These initiatives serve as a model for other public administrations seeking to leverage technology to address current and future challenges. | Local | Spain | ES | Barcelona Provincial Council | Local Government | General public services | General services. | Implemented | 2.019 | Internal management | Internal support processes | No | No | Artificial Intelligence | G2G | x | x | x | x | x | x | x | Self-reporting tool | Integration and Interaction | Robotics and Automation | 31/07/2024 | ||||||||||||||||
| PSTW-2169 | Boosting efficiency and transparency in processing of Official Publications with AI tools - AI for thematic classification | https://cido.diba.cat/media/pdf/IA_anuncis_oficials_SBOPiDiPO.pdf | To enhance efficiency and transparency, SBOPiDiPO has implemented solutions such as the CIDOBOT and the automation of summaries of publications from the Official Barcelona Provincial Gazette (BOPB), optimizing processes and improving public services. The SBOPiDiPO ensures access to public information, contributing to transparency in compliance with the state (Law 19/2013) and Catalan (Law 19/2014) transparency laws. The service is provided through the BOPB and the Official Information and Documentation Searcher (CIDO). The BOPB is the official journal where the provisions and official acts of the public administrations of Barcelona are published. Since 1998, universal and free access to the electronic edition of the bulletin has been guaranteed. The CIDO disseminates information from Catalan public administrations, ensuring transparency by publishing official data and allowing the public to know the status and stage of regulations and public procedures. The CIDOBOT is an AI solution for thematic classification of publications in official gazettes. Based on neural networks, it classifies publications by thematic or procedural areas, such as personnel selection processes, grants, procurement, local regulations, and collective agreements. To do this, it has been trained with summaries of publications made manually by a human team from various official gazettes. The AI solutions have significantly improved the quality and efficiency of public services, optimizing the processes of summary writing and publication classification, reducing time and effort. Furthermore, they have increased governmental openness and transparency, facilitating access to information and improving the user experience. These technologies are scalable and replicable, allowing their adaptation in other environments, contributing to the modernization and improvement of administrative processes. In conclusion, the adoption of AI solutions by SBOPiDiPO of the Barcelona Provincial Council has represented a significant advance in the modernization of administrative processes, improving the quality and efficiency of public services and increasing transparency and access to public information. These initiatives serve as a model for other public administrations seeking to leverage technology to address current and future challenges. | Local | Spain | ES | Barcelona Provincial Council | Local Government | General public services | General services. | Implemented | 2.019 | Internal management | Internal support processes | No | No | Artificial Intelligence | G2G | x | x | x | x | x | x | x | Self-reporting tool | Integration and Interaction | Robotics and Automation | 31/07/2024 | ||||||||||||||||
| PSTW-217 | Correct and uniform case management when sanctioning unemployed citizens | https://en.digst.dk/media/27445/bilag-2a-knowledge-assessment-of-projects-of-the-national-artificial-intelligence-uptake-fund.pdf | The decision to sanction unemployed citizens is a complicated task for the caseworkers. Practices for when citizens should be economically sanctioned are not always uniform. The purpose of the project is therefore to develop a tool that can support caseworkers' assessment of whether economic sanctions will have the desired effect or not. The algorithm will analyse which factors have a negative or positive impact on citizens’ probability of becoming more or less available for employment. The algorithm will also provide support the assessment of whether adverse events (i.e. absences from activation offers or interviews) should trigger economic sanctions. | Local | Denmark | DK01 | Frederiksberg Municipality | Local Government | Social protection | Unemployment. | Pilot | 2.020 | 2021 | Enforcement | Supporting inspection processes | No | No | Artificial Intelligence | G2G | x | x | x | x | x | x | x | Mail to AI Watch 15-05-2021 | Planning | Planning and Scheduling | Automated reasoning | 15/11/2023 | ||||||||||||||
| PSTW-2171 | MitosLOD: Exporting Linked Open Data from the Greek National Registry of Administrative Public Services | https://search.mitos.gov.gr/ | The MitosLOD project has successfully integrated Artificial Intelligence (AI) technologies to develop advanced semantic search capabilities, significantly enhancing the functionality and user experience of the Greek National Registry of Administrative Public Services (MITOS). By leveraging the power of AI and semantic technologies, MitosLOD has transformed the way users interact with and retrieve information from the public service registry. Semantic search goes beyond traditional keyword-based search methods by understanding the contextual meaning and intent behind user queries. In the context of MitosLOD, AI algorithms have been employed to analyze and interpret the semantic relationships between public service descriptions, enabling more accurate and relevant search results. One of the key innovations in MitosLOD's semantic search implementation is the use of natural language processing (NLP) techniques. NLP allows the system to comprehend and process user queries expressed in natural language, making it more intuitive and user-friendly. Users can input their queries using everyday language, and the AI-powered semantic search engine translates these queries into structured, machine-readable formats for efficient retrieval of relevant public service information. A primary day of the semantic (and multilingual) search of Mitos can be found at (https://search.mitos.gov.gr/). | National | Greece | EL | Ministry of Digital Governance and Ministry of Interior | Central-Government | General public services | General public services n.e.c. | Pilot | 2.024 | Public services and engagement | Service personalisation (various) | No | No | Artificial Intelligence | G2C | x | x | x | x | x | x | x | Self-reporting tool | Communication | Natural language processing | natural language processing | 30/08/2024 | |||||||||||||||
| PSTW-2174 | GPT-NL - A language model for the Dutch language and culture | https://chat.bggpt.ai/ | The GPT-NL will be the Netherlands' open language model. The development of GPT-NL is in line with the General Data Protection Regulation (GDPR) and AI Regulation to arrive at a model that is not trained on sources that violate privacy or IP rights. The GPT-NL aims to strengthen the strategic autonomy and knowledge of the Netherlands in the field of AI, Data Science, and Data Spaces. Financing for the model comes from RVO/Ministry of Economic Affairs and Climate Policy. The project plan “Facility for a sovereign Dutch language model†was submitted for this in May 2023 and awarded at the end of October 2023. An amount of 13.5 million euros has been made available for the project. | National | Netherlands | NL | Ministry of Economic Affairs and Climate | Central-Government | General public services | R&D general public services. | Implemented | 2.023 | Public services and engagement | Service personalisation (various) | No | Yes | Artificial Intelligence | G2B | x | x | x | https://gpt-nl.nl/gpt-nl/ | Learning | Machine learning | Generative AI | Natural language processing | natural language generation | 31/07/2024 | |||||||||||||||||
| PSTW-2175 | BgGPT - A bulgarian LLM | https://eufarmbook.eu/it/about, https://www.tno.nl/en/digital/digital-innovations/data-sharing/generative-ai/ | INSAIT – Institute for Computer Science, Artificial Intelligence and Technology is developing BgGPT, a series of state-of-the-art generative AI for the Bulgarian language, created for the Bulgarian users, institutions, public, and private organisations. BgGPT is released as a series of free and open language models. | National | Bulgaria | BG | INSAIT – Institute for Computer Science, Artificial Intelligence and Technology | Academic-Research | General public services | General public services n.e.c. | In development | 2.024 | 2029 | Public services and engagement | Service personalisation (various) | No | Yes | Artificial Intelligence | G2C | x | x | x | x | https://bggpt.ai/blog/ | Learning | Machine learning | Generative AI | Natural language processing | chatbot | 07/10/2024 | |||||||||||||||
| PSTW-2178 | GPT-SW3 - The first large-scale generative language model for the Swedish language | https://www.ai.se/en/project/shared-digital-assistant-public-sector | AI Sweden, together with RISE and WASP WARA Media & Language, have developed a large-scale generative language model for the Nordic languages, primarily Swedish. GPT-SW3 is the first truly large-scale generative language model for the Swedish language. Based on the same technical principles as the much-discussed GPT-4, GPT-SW3 will help Swedish organisations build language applications never before possible. AI Sweden is the national center for applied AI and brings together more than 120 partners across the public and private sectors as well as academia. AI Sweden is funded by the Swedish government and our partners, both public and private. | National | Sweden | SE | AI Sweden | Academic-Research | Economic Affairs | R&D economic affairs | In development | 2.024 | Public services and engagement | Service personalisation (various) | No | Yes | Artificial Intelligence | G2B | x | x | x | x | x | x | https://www.ai.se/en/project/gpt-sw3 | Learning | Machine learning | Generative AI | Natural language processing | 31/07/2024 | |||||||||||||||
| PSTW-2179 | Svea - A shared digital assistant for the public sector | https://www.lighton.ai/fr/success-stories | The project, a shared digital assistant for the public sector, is a collaboration between Swedish authorities, municipalities, regions, and the business sector, coordinated by AI Sweden. The objective is to promote national cooperation on AI for text tasks and create conditions for shared solutions in the public sector.The ultimate goal is to support public sector employees and free up their time so they can focus on more creative and interpersonal tasks. Success requires public sector organisations to share critical resources while sharing the burden of gathering the data needed to create truly competent and flexible solutions. The first phase of this initiative focuses on data generation, change management, identifying use cases, and developing a prototype for an AI assistant using LLMs. Svea is the prototype for a shared digital assistant, which is under development in this project. The AI-based prototype will be designed to help public sector workers with text-based tasks. Currently, based on the Mixtral open language model from the French company Mistral, more models will be tested in phase 2. Employees will interact with Svea via a web-based chat. Svea can already answer business-specific questions, summarise documents, extract information, rewrite texts in easy-to-read Swedish, and much more. As of today, the following public administrations are involved in the project: Kungsbacka municipality, Tjörn municipality, Gothenburg city, Region Skåne, Region Halland, and Västra Götaland Region. | Local | Sweden | SE | Kungsbacka municipality, Tjörn municipality, Gothenburg city, Region Skåne, Region Halland, and Västra Götaland Region | Local Government | General public services | General public services n.e.c. | Implemented | 2.024 | Internal management | Internal support processes | No | Yes | Artificial Intelligence | G2G | x | x | x | x | x | x | https://www.ai.se/en/project/shared-digital-assistant-public-sector | Learning | Machine learning | Generative AI | Natural language processing | 31/07/2024 | |||||||||||||||
| PSTW-218 | Targeted employment programmes for unemployed citizens | https://en.digst.dk/media/27445/bilag-2a-knowledge-assessment-of-projects-of-the-national-artificial-intelligence-uptake-fund.pdf | To offer better and more targeted employment programmes to unemployed citizens, knowledge is needed about what creates the greatest effect and helps citizens the most. The purpose of the project is to reduce the period of unemployment and provide more beneficiary services to citizens. The algorithm provides a decision support tool for caseworkers to help them offer unemployed, job-ready citizens a targeted programme. The algorithm will make proposals for specific activities that can reduce the expected period of unemployment based on the individual citizen's information. | Local | Denmark | DK031 | Odense Kommune | Local Government | Social protection | Unemployment. | Pilot | 2.020 | 2021 | Public services and engagement | Service personalisation (various) | No | No | Artificial Intelligence | G2C | x | x | x | Mail to AI Watch 15-05-2021 | Planning | Planning and Scheduling | Automated reasoning | decision support | 15/11/2023 | |||||||||||||||||
| PSTW-2180 | LightOn's Paradigm platform - Generative AI at the ÃŽle-de-France Regional Council | https://ai4science-amsterdam.github.io/ai4smm_projects/#machine-learning-based-models-of-plant-protein-mixtures-for-sustainable-food-design | Agents in the Ile-de-France Region struggle to find the relevant information to properly use their internal software, which impacts their ability to carry out their operations, and takes up a lot of the IT team's time. The Region's Digital Transformation Hub team added the necessary technical documentation to LightOn's Paradigm platform. This allows their agents to access instant support by easily searching through their documentation. Plans are underway to extend these benefits to the general public, demonstrating the impact of AI on public service management. Paradigm, an intelligent assistant serving agents in the digital transformation hub (who are responsible for managing the information systems, infrastructures and applications for all agents at headquarters). Designed by the startup LightOn, the tool quickly provides a precise response to questions asked in natural language. To do this, it uses existing technical documentation. | Regional | France | FR | ÃŽle-de-France Regional Council | Regional Government | General public services | General services. | In development | 2.024 | Internal management | Internal support processes | No | No | Artificial Intelligence | G2G | x | x | x | x | x | https://www.smartcitymag.fr/article/1378/ia-point-d-etape-sur-les-8-cas-d-usage-testes-en-ile-de-france | Learning | Machine learning | Generative AI | Natural language processing | 10/10/2024 | ||||||||||||||||
| PSTW-219 | Better match between unemployed citizens and companies | https://en.digst.dk/media/27445/bilag-2a-knowledge-assessment-of-projects-of-the-national-artificial-intelligence-uptake-fund.pdf | Although companies demand labour, it can be difficult to match unemployed citizens with the right skills to the right jobs. The purpose of the project is to develop a tool that can help case workers offer a more targeted job search and thus increase the effect of the employment programme., Although companies demand labour, it can be difficult to match unemployed citizens with the right skills to the right jobs. The purpose of the project is to develop a tool that can help case workers offer a more targeted job search and thus increase the effect of the employment programme. The algorithm matches the described professional and personal abilities from unemployed citizens’ CVs with requirements in current job openings to propose alternative jobs in other industries or alternative job types. In this way, case workers can better help the unemployed towards a more targeted job search. | Local | Denmark | DK011 | Kobenhavns Kommune | Local Government | Social protection | Unemployment. | Pilot | 2.020 | 2021 | Public services and engagement | Service personalisation (various) | No | No | Artificial Intelligence | G2C | x | x | x | x | x | Mail to AI Watch 15-05-2021 | Planning | Planning and Scheduling | Searching | 15/11/2023 | ||||||||||||||||
| PSTW-2195 | F13, the LLM used by the State of Baden-Württemberg in collaboration with Aleph Alpha | https://www.cnr.it/it/news/12868/il-progetto-genai4lex-b-premiato-alla-camera-dei-deputati-intelligenza-artificiale-generativa-per-i-lavori-parlamentari | The system, F13, was developed primarily by the Heidelberg-based AI start-up Aleph Alpha, which has been touted as a German response to OpenAI's ChatGPT, though aimed at government, administration and industry in particular. The Innovation Lab Baden-Württemberg (InnoLab_bw) presents the new text assistance "F13" for the administration in the state. Based on generative artificial intelligence, this programme was developed to sustainably relieve the employees of the state administration. New functions are introduced to optimize workflows. The summary function allows staff to select different compression levels for pasted texts. The Cabinet Template (KV) Note converts uploaded cabinet templates into a summarised note template. The research assistant supports the preparation of large amounts of information, while the "Vermerkomat" enables the creation of a comprehensive flow text. The "Vermerkomat" is currently in the test phase. It is important to note that the summarised texts must always be checked and controlled by one person. Complete automation of the processes is not planned. Close involvement of the users plays a decisive role in the further development of the functions of "F13" in terms of quality. For this reason, a diverse group of testers from different areas was integrated into the feedback process at an early stage. From May 2023, all employees who have access to the state administration network will be able to use "F13". | Regional | Germany | DE | State of Baden-Württemberg | Regional Government | General public services | General services. | Pilot | 2.023 | Internal management | Internal support processes | No | Yes | Artificial Intelligence | G2G | x | x | x | https://www.yahoo.com/news/baden-w-rttemberg-first-german-170630420.html?guccounter=1 | Learning | Machine learning | Generative AI | 31/08/2024 | |||||||||||||||||||
| PSTW-2199 | Open Spanish LLM model in collaboration with IBM | https://www.banquedesterritoires.fr/la-region-ile-de-france-presente-son-demonstrateur-dia-de-service-public | In a new effort announced today, the government of Spain and IBM said they would come together to develop and deploy cutting-edge AI technologies. This will include a new open-source large language model (LLM) in Spanish. Together, they plan to revolutionise how Spanish-speaking countries and organisations can do business in the age of AI. | National | Spain | ES | Government of Spain | Central-Government | General public services | R&D general public services. | Implemented | 2.024 | Analysis, monitoring and regulatory research | Innovating Public Policy | No | Yes | Artificial Intelligence | G2B | x | x | https://research.ibm.com/blog/new-spanish-llm-ai | Learning | Machine learning | Generative AI | 31/08/2024 | ||||||||||||||||||||
| PSTW-2202 | Developing a Generative AI platform for construction cost management | https://assets.publishing.service.gov.uk/media/66cdb0cc239c5e6b4dc0533a/Use_cases_for_generative_AI_in_education_technical_report.pdf | The Futures of Systems, People and Projects (FUSP) laboratory has been awarded a £1.18m Innovate UK grant to produce a generative AI platform for boosting the productivity and accuracy of cost planning in construction. This new research project follows on from a successful feasibility study funded by Innovate UK. We have now been awarded follow-on funding to produce a “BIM-enabled Generative AI Platform for Productivity and Accuracy Enhancement of Construction Cost Planning (BIM-GAIcost)â€. The potentials of generative AI will become a useful tool to reduce cost overruns which are prevalent in 69% of projects and the 15% increase in UK construction costs. Our successful pilot project produced costplan.ai – we will now upgrade this with new features that merge a data-driven Building Information Modelling (BIM) for early cost advice through generative AI. The prompting feature of the AI digital platform will enhance productivity by up to 85% by reducing the time taken to produce initial cost plans and produce accuracy measures for UK contractors and clients. The research will enhance the web application – costplan.ai - to produce construction cost estimation documents through large language models (LLM) of cost data and support the automation of BIM cost related documents with accuracy indications to predict and avoid cost overruns in the planning phase. | National | United Kingdom | UK | Leeds Beckett University | Academic-Research | Economic Affairs | Mining, manufacturing and construction. | Pilot | 2.024 | Analysis, monitoring and regulatory research | Prediction and planning | No | No | Artificial Intelligence | G2B | x | x | x | https://www.ukri.org/wp-content/uploads/2024/08/IUK-070824-TMF-announcement-7.8.24-project-list.pdf | Learning | Machine learning | Generative AI | Planning and Scheduling | 31/08/2024 | ||||||||||||||||||
| PSTW-2205 | Qra - The first Polish open-source LLM | https://tech.eu/2024/08/07/monumos-innovations-in-electric-drive-design-a-ps750000-boost-from-innovate-uk/ | Gdańsk University of Technology and AI Lab from the Information Processing Center (OPI) - National Research Institute have developed Polish-language generative neural language models based on a terabyte of text data exclusively in Polish. Qra is the first of its kind and the best in Polish language modeling equivalent of open tools such as Meta or Mistral AI. Qra understands content in Polish better, understands questions asked in Polish better and creates coherent texts better. it is available as open-source on the huggingface platform and it is still being finetuned. | National | Poland | PL | Gdańsk University of Technology | Academic-Research | General public services | R&D general public services. | Pilot | 2.024 | Public services and engagement | Service personalisation (various) | No | No | Artificial Intelligence | G2C | x | x | https://huggingface.co/OPI-PG/Qra-1b | Learning | Machine learning | Generative AI | Natural language processing | 31/08/2024 | |||||||||||||||||||
| PSTW-2206 | OpenLLM-Ro - The first LLM in Romanian language | https://www.weforum.org/agenda/2024/07/generative-ai-smart-cities/, https://www.uva.nl/en/shared-content/faculteiten/en/faculteit-der-natuurwetenschappen-wiskunde-en-informatica/news/2024/02/shaping-the-future-of-materials-using-artificial-intelligence.html?cb | Starting from the second part of 2023, a team of researchers from POLITEHNICA Bucharest, the University of Bucharest and the Institute of Logic and Data Science worked on the development and training of this LLM. The academic partners contributed researchers who worked pro-bono and, in addition, POLITEHNICA Bucharest also provided the computing power needed to train the model. It is available online and it is currently being finetuned. | National | Romania | RO | POLITEHNICA Bucharest, the University of Bucharest and the Institute of Logic and Data Science | Academic-Research | General public services | R&D general public services. | Pilot | 2.024 | Public services and engagement | Service personalisation (various) | No | No | Artificial Intelligence | G2C | x | x | https://therecursive.com/romania-launches-its-first-open-source-llm-model/ | Learning | Machine learning | Generative AI | Natural language processing | 31/08/2024 | |||||||||||||||||||
| PSTW-221 | Creation and management of semantic OTL relationships | https://www.innovatieveoverheidsopdrachten.be/en/projects/creation-and-management-semantic-otl-relationships | With the implementation of Construction Information Management (BIM) , which (generally) relates to virtual construction and digital collaboration between all project partners within a construction project, the Roads and Traffic Agency (AWV) of the Flemish government is fully committed to the evolution towards a data-driven organization. AWV makes maximum use of the possibilities of modern digital methods and technologies to collect, manage and use correct, complete and up-to-date information about its assets. The 'assets' are the road infrastructure objects that AWV manages, maintains and operates: roads, cycle paths, tunnels, bridges and all peripheral infrastructure. With BIM, AWV can efficiently collect and manage all available information about its assets during their entire life cycle (study and design phase / construction and installation / management and maintenance / replacement or removal) in a central database. By collecting the asset data once and exchanging it in a standardized manner, this data can be made uniformly available to all parties involved at any time during the life cycle of the assets. | Regional | Belgium | BE2 | Roads and Traffic Agency of the Flemish Government | Regional Government | Economic Affairs | Other industries | In development | 2.021 | Internal management | Internal primary processes | No | No | Artificial Intelligence | G2B | x | x | https://innovatieveoverheidsopdrachten.be/projecten/aanmaak-en-beheer-van-semantische-otl-relaties | Reasoning | Automated reasoning | Knowledge representation | 15/11/2023 | ||||||||||||||||||||
| PSTW-2210 | NorGPT - The open LLM "Made in Norway" | https://www.ntnu.edu/norwai/norgpt-language-models | LLM using Norwegian Language developed by NorwAI and the Norwegian University of Science and Technology (NTNU) | National | Norway | NO | NorwAI and NTNU | Academic-Research | General public services | R&D general public services. | In development | 2.024 | Public services and engagement | Service personalisation (various) | No | Yes | Artificial Intelligence | G2C | x | x | x | x | https://www.ntnu.edu/norwai/norgpt-language-models | Learning | Machine learning | Generative AI | Natural language processing | 31/08/2024 | |||||||||||||||||
| PSTW-2211 | ‘Democratic Engagement through a Public Chatbot’ (DepuChat) - How GenAI can increase transparency | https://turkunlp.org/gpt3-finnish | The Chamber of Deputies is more transparent and closer to the citizens thanks to the project ‘Democratic Engagement through a Public Chatbot’ (DepuChat), developed by the European Interdepartmental Research Centre for Advanced Studies on Digital Innovation IDEAS (Research Center IDEAS - Innovation Digital European Advanced Studies) of the University of Roma Tre in collaboration with the Department of Legal Sciences of the University of Florence. This is a proposal for a chatbot that, through generative AI, will make data and information on the Chamber, its bodies and procedures, individual MPs, and the political positions expressed by MPs and the Government more usable, including graphically. The purpose of this technological tool is to bring citizens closer to the Institutions. | National | Italy | IT | University of Roma Tre | Academic-Research | General public services | R&D general public services. | Implemented | 2.024 | Public services and engagement | Service personalisation (various) | No | Yes | Artificial Intelligence | G2C | x | x | x | x | x | x | https://www.wired.it/article/intelligenza-artificiale-generativa-camera-dei-deputati-anna-ascani/ | Learning | Machine learning | Generative AI | Natural language processing | chatbot | 11/09/2024 | ||||||||||||||
| PSTW-2213 | Supporting Civil Servant with Generative AI | https://www.ntnu.edu/norwai/norgpt-language-models, https://www.uio.no/dscience/english/news-and-events/news/presentation-from-nordic-perspectives-on-ai/4jon-atle-gulla_norgpt_131023-np.pdf, https://www.ntnu.edu/norllm/four-models-built-four-new-ones-in-the-pipeline | The civil service, the largest employer in France, cannot remain on the sidelines of this technological revolution, at the risk of suffering it. In order to measure the concrete consequences, 1000 volunteer agents will be equipped with a tool using artificial intelligence to help them write online responses to users' opinions and comments, during their online procedures. Agents will supervise and modify the response before sending it to the user. The data is completely anonymised, so confidentiality is completely preserved for the user. These tools must be put at the service of agents to enable them to be more efficient on certain tasks in order to save time and thus strengthen human contact between public service agents and the French people. This experiment, led by the Interministerial Directorate for Public Transformation (DITP) and the Interministerial Digital Directorate (DINUM), will be extended, by the end of the year, to the agents of the France services houses in their support for users at the counter. The solutions experimented is made by https://www.allobrain.com/ | National | France | FR | Ministry of Processing and Function Public Interministerial Directorate for Public Transformation (DITP) and the Interministerial Digital Directorate (DINUM), | Central-Government | General public services | R&D public order and safety. | Implemented | 2.023 | Internal management | Internal primary processes | No | Yes | Artificial Intelligence | G2G | x | x | x | x | Stanislas GUERINI experiments with generative artificial intelligence in public services | Interdepartmental Directorate for Public Transformation (modernisation.gouv.fr) | Learning | Machine learning | Generative AI | 11/09/2024 | ||||||||||||||||||
| PSTW-2215 | Legislab - monitoring legislative quality with GenAI | https://www.quotidiano.net/politica/lintelligenza-generativa-camera-deputati-44462545 | The project is designed to help and monitor, through an artificial intelligence agent, the quality of the legislative system. This analysis occurs objectively, in the sense that the laws that are to be analyzed are compared with all those issued from the Constitution onwards. The project is based on the work of building a database of Italian laws, which is constantly updated. A second part of the platform aims to help the parliamentarian or the legislator to write the laws. Through a screen it is possible to insert an input text, for example the title of a new law, and the tool searches for the articles and laws, in the entire database, that may be important to cite or look at if you want to write a law on a certain topic. It does not help to write the law, that remains the task of the expert. To avoid "hallucinations" the model is forced to rely only on data from other laws, objective data and linguistic metrics that derive from scientific literature. | National | Italy | IT | The Polytechnic University of Milan | Academic-Research | General public services | Executive and legislative organs, financial and fiscal affairs, external affairs. | Planned | 2.024 | Public services and engagement | Internal primary processes | No | Yes | Artificial Intelligence | G2G | x | x | https://www.quotidiano.net/politica/lintelligenza-generativa-camera-deputati-44462545 | Learning | Machine learning | Generative AI | 13/09/2024 | ||||||||||||||||||||
| PSTW-2225 | INNOAIR - Green public transport on-demand in the Municipality of Sofia | https://portico.urban-initiative.eu/uia/making-transitions-affordable-all/innoair | The INNOAIR project was funded through the European Regional Development fund, through a Urban Innovative Actions initiative. The project has multiple objectives, predominantly to improve mobility in the city of Sofia through a series of actions to design, develop, and deploy greener forms of public transport to residents, improving health and reducing air pollution. The project is coordinated by the Municipality of Sofia, with project management duties delegated to a distinct organisation, entitled the Sofia Development Association (SDA). The project tested in a real environment new for Bulgaria and Europe transport services and pilot solutions in the neighborhoods of “Manastirski Livadi” and “Baxton”, which provided citizens travel alternatives, reduced car traffic and improved air quality. Artificial intelligence was used to determine the optimal routes for the on-demand e-buses. The AI used both first-hand data (information/data from the Municipality, number of registered cars, presence of schools, hospitals, etc.) and secondary data collected in the field through urban walks with residents and other co-creative processes. It was determined that routes should stay fixed once set and that times of passage should be on demand. Five pilot electric on-demand buses, each with a 20-person capacity, began a one-year trial in 2023. | Local | Bulgaria | 2.020 | 2024 | Public services and engagement | Service personalisation (various) | No | No | G2C | x | x | x | x | https://innoair-sofia.eu/en/project.html | Learning | Machine learning | Planning and Scheduling | |||||||||||||||||||||||||
| PSTW-2226 | A new virtual assistant for the city of Kortrijk | https://www.kortrijk.be/gesubsidieerde-projecten/de-virtuele-assistent#:~:text=Via%20de%20Virtuele%20Assistent%20zullen,%2C%20laptop%2C%20tablet%20%C3%A9n%20smartphone. | ‘De Virtuele Assistent’ (The Virtual Assistant) is funded as part of wider digitalisation plan for Flanders Region in Belgium, implemented and part funded by the City of Kortrijk trhough the NextGenerationEU funds. The Virtual Assistant, by combining transactional chatbot technology with Artificial Intelligence (AI), can answer questions from citizens about the city's services, and helps citizens, associations and companies alike to make an appointment, request documents, deeds and certificates or make/consult reports. | Local | Belgium | 2.022 | 2025 | Public services and engagement | Service personalisation (various) | No | No | G2C | x | x | x | x | https://www.kortrijk.be/gesubsidieerde-projecten/de-virtuele-assistent#:~:text=Via%20de%20Virtuele%20Assistent%20zullen,%2C%20laptop%2C%20tablet%20%C3%A9n%20smartphone. | Communication | Natural language processing | chatbot | |||||||||||||||||||||||||
| PSTW-2227 | ‘Fix the Streets’ - AI that leverages citizen-produced data to improve the streets | https://www.youtube.com/watch?v=4FE4pLXw2fU | The project ‘Fix the Streets’ is funded through the Vaasa City, as part of the ‘Innovation activity Ecosystem Agreement 2021-2027’ between Vaasa city region and the Government of Finland. The ecosystem agreements harness the region’s ability to develop and deploy digital technologies and carbon neutral activities, helping them to meet Twin Transition goals. The Fix the Streets initiative in Vaasa, managed by the Municipal Engineering Department and supported by Tampere-based technology company Crowdsorsa, used a mobile app to crowdsource geo-located data on road conditions from citizens. Over two years, the project built a multi-format knowledge base (text, images, videos) on street health, leveraging AI to analyze issues like potholes and damaged signage. The app integrated with Vaasa's digital signage system for precise data mapping, prioritizing data minimization and enhancing city infrastructure monitoring and decision-making. | Local | Finland | 2.020 | 2022 | Analysis, monitoring and regulatory research | Innovating Public Policy | No | No | G2G | x | x | x | x | x | x | x | https://interoperable-europe.ec.europa.eu/collection/portal/news/study-ai-and-genai-adoption-local-regional-administrations | Planning | Planning and Scheduling | Computer vision | ||||||||||||||||||||||
| PSTW-2229 | The 'Wet Index’ project - an AI tool to predict local floods | https://www.dtu.dk/english/newsarchive/2024/03/ai-predicts-flooding | In response to severe rainfall impacts on its citizens and landowners, Jammerbugt Municipality in Denmark developed an AI-based early warning tool called the "wet index." This innovative system leverages regional geo and climate data to support flood forecasting and inform decision-making for urban and rural planning. Developed in collaboration with researchers from the Technical University of Denmark (DTU), the tool provides 48-hour advance warning of potential flooding in local rivers, streams, and coastal areas—making it the first system of its kind to deliver localized flood alerts. The initiative is part of a broader national effort by the Danish Agency for Digitalisation to test and develop AI applications, and received funding through an investment fund established by the Danish government, Local Government Denmark, and Danish regions. | Local | Denmark | 2.023 | Analysis, monitoring and regulatory research | Prediction and planning | No | No | G2G | x | x | x | x | x | https://interoperable-europe.ec.europa.eu/collection/portal/news/study-ai-and-genai-adoption-local-regional-administrations | Planning | Machine learning | Planning and Scheduling | |||||||||||||||||||||||||
| PSTW-2230 | Policies for Holistic Urban Mobility and Accessibility | https://ai4publicpolicy.eu/optimal-urban-mobility-policies-for-citizens/ | The project carried out by the Nicosia Municipality is part of the 'AI4PublicPolicy’ initiative, funded by the EU Horizon 2020 programme. The project is oriented towards the development of a citizen-centric solution and its specific aim is to develop evidence-driven policies that enhance citizens' mobility and reduce travel time. It specifically focuses on two policies aiming at (1) improving the accessibility for people with disabilities and at (2) optimising parking accessibility for individuals with disabilities. The development of the first policy implies the combined use of AI algorithms to analyse traffic data, the whitelist of the Smart City platform and License Plate Recognition (LPR) cameras to improve access for individuals with disabilities to streets with limited vehicle entry during periods of traffic congestion. For the development of the second policy, the predictive power of AI is used to forecast congested areas and enhance parking accessibility in specific support of individuals with disabilities. Multiple co-creation workshops with Nicosia's and Cyrpus' stakeholders have been conducted. | Local | Cyprus | 2.023 | 2024 | Analysis, monitoring and regulatory research | Prediction and planning | No | No | G2C | x | x | x | https://interoperable-europe.ec.europa.eu/collection/portal/news/study-ai-and-genai-adoption-local-regional-administrations | Planning | Machine learning | Planning and Scheduling | ||||||||||||||||||||||||||
| PSTW-2232 | RECITAL' Project: Immediate and Long-Term Energy Reduction | https://www.citegestion.fr/news/projet-recital-transition-energetique-noisy-le-grand | The project is part of the Municipality’s “smart strategy” and it consists of an ‘energy hypervisor’ that uses AI to collect and analyze consumption data from the city’s buildings, with a ten-year history. This enables the tracking of consumption on a daily basis and the identification of episodes of over consumption by means of alerts. The project also focuses on the installation of smart meters and sensors in each building to measure energy consumption, exploiting IoT to make process of decarbonization more efficient. | Local | France | 2.023 | 2025 | Analysis, monitoring and regulatory research | Prediction and planning | No | No | G2G | x | x | x | x | https://interoperable-europe.ec.europa.eu/collection/portal/news/study-ai-and-genai-adoption-local-regional-administrations | Planning | Machine learning | Optimisation | Planning and Scheduling | internet of things | |||||||||||||||||||||||
| PSTW-224 | ALTRUIS - Alternative Use of Imaging Systems through Artificial Intelligence | https://www.innovatieveoverheidsopdrachten.be/evenementen/meetup-altruis-alternative-use-imaging-systems-through-artificial-intelligence | With the project Alternative Use of Imaging Systems through Artificial Intelligence (ALTRUIS), Digipolis wants to help tackle the mobility problem in and around the city of Antwerp by using camera images alternatively and using Artificial Intelligence (AI). The city of Antwerp is confronted daily with one of the heaviest traffic congestions in Europe. To remedy this, the city's main mobility axes are being thoroughly reorganized. The accompanying works (also known as 'the yard of the century') put even greater pressure on mobility and quality of life in and around the city. A disruptive approach is therefore imperative to face these challenges. ALTRUIS must translate the street footage, which in itself has little value, through its interpretation to mobility context and insights that can lead to smart mobility solutions in the city of Antwerp (primarily the Smart Zone). | Local | Belgium | BE211 | DigiPolis, IT provider for the City of Antwerp | Local Government | Economic Affairs | Transport | In development | 2.018 | Analysis, monitoring and regulatory research | Prediction and planning | No | No | Artificial Intelligence | G2G | x | x | https://innovatieveoverheidsopdrachten.be/projecten/alternative-use-imaging-systems-through-artificial-intelligence-altruis | Perception | Computer vision | Machine learning | 15/11/2023 | ||||||||||||||||||||
| PSTW-2243 | Inter-municipal Chatbot MUNI - Aarhus | https://aarhus.dk/borger/borgerservice/bestil-tid-i-borgerservice/ | MUNI is an innovative chatbot project that brings together 36 municipalities (and potentially up til 78 municipalities) in Denmark to explore how AI and chatbot technology can enhance the interface between citizens and government services. In 2022, the "MUNI project" was awarded the Danish Innovation Award. The chatbot project aims to supplement and potentially replace traditional self-service solutions with AI-powered alternatives that allow for more efficient and user-friendly interactions between citizens and the government. MUNI has been able to integrate with various municipal call centers and self-service systems such as Puzzel and Selvbetjening.nu, among others. Since the launch in 2020, 10,000 citizens rated their experience with the chatbot, and on average they rated the service 2.43 out of 3. For the citizens who did not get the help they needed, there is an alternative. It is essential that the citizens always receive the help they need, so if the chatbot is not able to give a sufficient answer, the citizens can choose to talk to an agent from the call center in the Digital Hotline. It works seamlessly - If the chatbot cannot provide a helpful answer, and the citizen keeps asking the same question, the chatbot will simply offer to make a callback, and the citizen will be contacted by an agent from the call center. Since the launch of the chatbot 950 citizens have asked for a callback. | Local | Denmark | 2.020 | Public services and engagement | Service personalisation (various) | No | No | G2C | x | x | x | x | https://www.usercentricities.eu/services/inter-municipal-chatbot-muni | Communication | Natural language processing | AI Services | chatbot | |||||||||||||||||||||||||
| PSTW-2245 | Humanising Authonomy - Behavioural AI to improve the safety of public transport | https://humanisingautonomy.com/ | Transport for London’s Freight Lab and other freight operators are deploying Humanising Autonomy’s real time intent prediction software in their vehicles to work on the next generation of London’s Bus Safety Standard. This is part of London’s effort to reach Vision Zero by 2041 — put an end to deaths and injuries on the roads. The software specialises in analysing camera data in real-time to interpret and predict pedestrian, passenger, and vehicle behaviour to better inform automated decision-making engines for driver alerts and vehicle motion. It integrates with all levels of autonomy, including driver-assist features for human-driven vehicles such as Automated Emergency Brakes, front and near-side driver alerts, or rear-mirror camera monitoring systems. | Local | United Kingdom | 2.020 | Analysis, monitoring and regulatory research | Prediction and planning | No | No | G2C | x | x | x | https://gouai.cidob.org/atlas/ | Perception | Computer vision | Planning and Scheduling | |||||||||||||||||||||||||||
| PSTW-225 | Capsat - Information from satellite images for a better agricultural policy in Flanders and Europe | https://www.innovatieveoverheidsopdrachten.be/en/projects/capsat-satellites-imagery-information-better-agricultural-policy-flanders-and-europe | Every Flemish farmer who receives 'direct support' within the European Common Agricultural Policy (CAP) is obliged to adhere to a number of climate and environmentally friendly principles and practices with a view to sustainable, liveable and competitive agriculture. This concerns, for example, crop diversification, the maintenance of grassland and the creation of ecological focus areas. The Department of Agriculture and Fisheries supervises the correct and timely implementation of these types of policy measures. Currently, the control is based on spot checks in the field. High-resolution images from various satellites are able to quickly map the correct information. This allows for better follow-up, guidance and control of the farmers. Also possibly. crop damage due to drought or flooding can be objectified more quickly. | Regional | Belgium | BE2 | Department of Agriculture and Fisheries | Regional Government | Economic Affairs | Agriculture, forestry, fishing and hunting | In development | 2.021 | Analysis, monitoring and regulatory research | Monitoring policy implementation | No | No | Artificial Intelligence | G2B | x | x | x | https://innovatieveoverheidsopdrachten.be/projecten/capsat-informatie-uit-satellietbeelden-voor-een-beter-landbouwbeleid-vlaanderen-en-europa | Perception | Computer vision | Machine learning | 15/11/2023 | |||||||||||||||||||
| PSTW-2252 | Generative AI Assistant PARLA for the City of Berlin | https://www.parla.berlin/ | For many other actors, such as associations, chambers, the media and civil society organisations, it is often time-consuming to obtain an overview of current issues and decisions. An AI assistant for researching for written requests into a large documental repositories (thousands of administrative, legislative or other types of documents), using AI to support this process of information retrieval could help on this. The text corpus includes also all answers to written questions from members of parliament as well as the important main committee procedures (so-called "red numbers"). If you ask to Parla.ai Assistant a question, the system formulates a suggested answer based on this text and references the documents used for this purpose, so that traceability is guaranteed. Parla.ai can thus not only digitally support the daily work of parliament and administration. | Local | Germany | 2.024 | Public services and engagement | Service personalisation (various) | No | No | G2C | x | x | x | x | https://citylab-berlin.org/en/projects/parla/ | Communication | Natural language processing | Generative AI | chatbot | |||||||||||||||||||||||||
| PSTW-226 | CATE - Continuous Auditing based on Technological Evolution and Data Mining | https://innovatieveoverheidsopdrachten.be/projecten/cate-continuous-auditing-based-technological-evolution-and-data-mining | The Flemish Audit Authority is responsible for the (financial and operational) auditing of the projects that are subsidized through European structural funds and Flemish co-financing. A significant proportion of audits must be outsourced. This outsourcing is done at a relatively high cost, for not always the same amount of added value; In outsourcing it is often noted that the performers of these assignments are often young auditors with little or no knowledge of public procurement and state aid, which makes the quality control by the Flemish Audit Authority very intensive and time-consuming, which is not the intention of outsourcing. This project wants to rethink the audit process methodologically and technologically with the following objectives: greater certainty, at a lower cost, within a shorter period of time with greater added value and less loss of (European) resources. | Regional | Belgium | BE2 | Flemish Audit Office | Regional Government | General public services | Executive and legislative organs, financial and fiscal affairs, external affairs. | In development | 2.021 | Enforcement | Management of auditing and logging | No | No | Artificial Intelligence | G2B | x | x | x | https://innovatieveoverheidsopdrachten.be/projecten/cate-continuous-auditing-based-technological-evolution-and-data-mining | Planning | Planning and Scheduling | Automated reasoning | 15/11/2023 | |||||||||||||||||||
| PSTW-227 | Smart Personalization of the cultural offer in Antwerp Testing (SOCRATES) | https://www.innovatieveoverheidsopdrachten.be/en/projects/smart-personalisation-cultural-offer-antwerp-testing-socrates | With the PIP project Smart Personalization of the Cultural Supply in Antwerp Testing (SOCRATES), the city of Antwerp and Digipolis want to investigate the feasibility and effectiveness of an individual cultural user profile. Via such a profile, the city of Antwerp wants to offer personalized recommendations to Antwerp culture lovers (tailor-made culture) at their own request and on the basis of their digital cultural DNA. The intended technological solution for SOCRATES is a Digital Experience Platform (DXP) that, as mentioned, is nourished by a personal culture profile and enriched with a wonder algorithm . The aim is to build the DXP in a modular way so that a maximum link with existing and future IT architecture, in particular the Antwerp City Platform as a Service (ACPaaS), is possible. ACPaaS offers a 'block box' of reusable (generic) backend services via engines so that (specific) frontend applications can be made faster, simpler and more powerful. The DXP intended with SOCRATES as an extension of ACPaaS extends this line to the application frontends, or all digital touchpoints with the (cultural) users. Based on the digital cultural profile of the user, Artificial Intelligence (AI) can make suggestions for, for example, literature and all kinds of cultural activities. | Local | Belgium | BE211 | City of Antwerp | Local Government | Recreation, culture and religion | Cultural services. | In development | 2.021 | Public services and engagement | Service personalisation (various) | No | No | Artificial Intelligence | G2C | x | x | https://innovatieveoverheidsopdrachten.be/projecten/slimme-personalisatie-van-het-cultuuraanbod-antwerpen-testen-socrates | Communication | Natural language processing | Searching | Q&A | 15/11/2023 | |||||||||||||||||||
| PSTW-228 | Smart regulation - Using Artificial Intelligence to train computers to interpret regulation | https://www.innovatieveoverheidsopdrachten.be/en/projects/smart-regulation | Regulations are extremely valuable information that is relevant to everyone in our society. However, the large amount of divergent and incoherent regulation leads to information silos. There are so many different types of documents that there is little structure to be found in them. Moreover, the regulations on a particular subject are often spread over various (basic) laws, amendments to, additions to and improvements to those laws. That is impractical. Lawyers are working to clarify this by harmonizing (coordinating) and bringing together (codifying) this fragmented legislation. But this does not yet solve the problem sufficiently. With the project 'Smart Regulations' the agency wants to offer a solution by using Artificial Intelligence to train computers to interpret regulations. For example, computers can very accurately extract the correct information from those regulations for specific target groups (this can be people, applications or machines). The goal is therefore to be able to offer an 'engine' on unstructured information sources from legislation, regulations and decision-making that users can subscribe to in order to get data and additional insights from these information sources more quickly according to their needs. | Regional | Belgium | BE2 | Flemish Domestic Governance Agency | Regional Government | General public services | Executive and legislative organs, financial and fiscal affairs, external affairs. | In development | 2.021 | Internal management | Internal support processes | No | No | Artificial Intelligence | G2G | x | x | https://innovatieveoverheidsopdrachten.be/projecten/slimme-regelgeving | Communication | Natural language processing | Searching | Machine learning | text analysis | 15/11/2023 | ||||||||||||||||||
| PSTW-229 | Turing - Automatically control Flemish road lighting with local and current data | https://www.innovatieveoverheidsopdrachten.be/en/projects/turing-automatically-controlling-flemish-road-lighting-local-and-current-data | On Flemish motorways, road lighting is only on where it is needed. Specifically, the light goes out when possible and stays on when necessary. In 2011, the Agency for Roads and Traffic (AWV) developed a light vision in response to the European Union's climate target to reduce energy consumption by 20% by 2020. Since then, the number of illuminated road sections has fallen by almost half. Currently, the road lighting is controlled on the basis of historical traffic intensities and weather forecasts per province. However, local and real time data on traffic intensity and weather conditions are available. Through a combination of rule-based algorithms and machine learning, internal and external data sources can be integrated into the current system that controls the road lighting. AWV wishes to use this data to make a more accurate and location-based decision whether or not road lighting should be on on a specific road segment. In this way, AWV can make a more efficient contribution to climate objectives and to promoting road safety. Moreover, the system will also allow to significantly reduce the workload of the operators. | Regional | Belgium | BE2 | Agency for Roads and Traffic (AWV) | Regional Government | Housing and community amenities | Street lighting. | In development | 2.021 | Analysis, monitoring and regulatory research | Monitoring policy implementation | No | No | Artificial Intelligence | G2C | x | x | x | https://innovatieveoverheidsopdrachten.be/node/6418 | Reasoning | Automated reasoning | Machine learning | 15/11/2023 | |||||||||||||||||||
| PSTW-2293 | Assess your entitlement to 906 aids: OpenFisca, a tool to writing rules as code | https://mes-aides.1jeune1solution.beta.gouv.fr/ | The most widely adopted free and open-source engine to write rules as code Government departments, lawmakers and civil society finally share a common language to debate and activate social and fiscal policies: OpenFisca enables collaboratively modelling laws and regulations and making them computable over open APIs for developers, datascientists and researchers. OpenFisca is a leading Rules as Code solution, but it is primarily aimed at microsimulation. Microsimulation is where you create a data model that represents small elements of a population, like people and households, and then encode the effects of different tax and benefit regimes. You can then load data that is representative of your actual population, and look at the effects on those individuals or groups in aggregate. Or, you can load a smaller number of specific examples and see how those particular fact scenarios are affected by the rules. It uses OpenFisca OSS software framework. OpenFisca is a policy simulation framework that utilizes various techniques from data science and computer science to model and analyze the impact of social and fiscal policies. While OpenFisca does not rely on Artificial Intelligence (AI) as its primary component, it does employ some AI-related techniques and concepts to enhance its capabilities. AI-related techniques used in OpenFisca: 1) Machine Learning (ML): OpenFisca uses ML algorithms to estimate the effects of policies on specific outcomes, such as poverty rates or government revenues. For example, it can employ regression analysis to model the relationship between policy parameters and outcomes. 2) Decision Trees: OpenFisca's policy modeling engine uses decision trees to represent complex policy rules and regulations. Decision trees are a type of ML model that can be used to classify inputs and make predictions. 3) Optimization Techniques: OpenFisca's scenario analysis capabilities utilize optimization techniques, such as linear programming, to find the optimal policy parameters that achieve specific goals, like minimizing poverty rates or maximizing government revenues. 4) Data Mining: OpenFisca's data integration and analysis capabilities involve data mining techniques to extract insights from large datasets and identify patterns in policy-relevant data. | National | France | 2.024 | Public services and engagement | Service personalisation (various) | No | No | G2C | x | x | x | x | https://openfisca.org/en/ | Learning | Machine learning | Automated reasoning and Automated Decision Making (ADM) | Optimisation | |||||||||||||||||||||||||
| PSTW-2296 | AI Sweeps new govs in UK | https://www.politico.eu/article/tony-blairs-ai-mania-sweeps-britains-new-government/ | Microsoft has also been promoting its own AI product suite to central and local government. The company recently published a report championing its tech, including its Copilot tool, which integrates OpenAI’s ChatGPT, as useful for central and local government to summarize emails, generate text and create documents. The tool has already been adopted by more than 100 local councils. Trials of the tool are underway in a handful of central government departments, too. | Local | United Kingdom | 2.024 | Public services and engagement | Service integration (various) | No | Yes | G2G | x | x | x | https://govern.cat/salapremsa/notes-premsa/622202/el-govern-utilitza-el-llenguatge-planer-per-facilitar-la-comprensio-dels-textos-juridics-a-la-ciutadania | Learning | Machine learning | Generative AI | Knowledge representation | ||||||||||||||||||||||||||
| PSTW-23 | CHAIN - Smart Water optimising energy consumption | https://iwa-network.org/climate-smart-utility-aarhus/ | Sensors analyse the water consumption in order to optimise energy consumption in Aarhus municipality. AI will be used to analyze the big amounts of data from sensors about water consumption and to monitor its quality. | Local | Denmark | DK | Aarhus Municipality | Local Government | Housing and community amenities | Water supply. | Pilot | 2.016 | Enforcement | Supporting inspection processes | No | No | Artificial Intelligence | G2C | x | x | x | https://www.aquatechtrade.com/news/article/video-story-digital-denmark/ | Learning | Machine learning | Optimisation | 06/10/2023 | |||||||||||||||||||
| PSTW-230 | Elsa - AI-assisted spreading decisions | https://innovatieveoverheidsopdrachten.be/projecten/elsa-door-ai-ondersteunde-strooibeslissingen | The Agency for Roads and Traffic (AWV) is responsible for the control of slippery conditions on Flemish roads under its own management. The AWV winter service is supported for this with various data sources and technical tools. AWV has been investing for some time in its own ice cream measurement system (GMS) that combines real-time results from measuring points and measuring stations with weather forecasts from the RMI.The knowledge and expertise of the employees is very different and is translated into a not very consistent spreading policy across the districts. However, the roads do not stop at the boundary line between two districts. That is why AWV wants to have a system developed that can support district employees in their choice of spreading and that can lead to more uniform spreading decisions across the districts. By combining physical rules and machine learning techniques , the system can help make the assessment and indicate which type of spreading material, in what quantity and at what time, is most appropriate to make and keep the roads in the district ice-free. | Regional | Belgium | BE2 | Agency for Roads and Traffic (AWV) | Regional Government | Economic Affairs | Transport | In development | 2.021 | Analysis, monitoring and regulatory research | Monitoring policy implementation | No | No | Artificial Intelligence | G2C | x | x | x | https://innovatieveoverheidsopdrachten.be/projecten/elsa-door-ai-ondersteunde-strooibeslissingen | Reasoning | Automated reasoning | Planning and Scheduling | 15/11/2023 | |||||||||||||||||||
| PSTW-2309 | Curve Real Time - Monitoring TV udience | https://www.osservatori.net/artificial-intelligence/convegno-ai-application-talk-2024-convegno/ | RAI's project focuses on integrating artificial intelligence (AI) to enhance its public broadcasting services, aiming to become a data-driven media company. Key areas of AI application include improving data governance, automating production processes, and creating a more user-centric experience through tools like metadata enrichment, recommendation engines, and entity recognition. A significant use case is the "Curve Real Time" project, which tracks TV audiences and analyzes real-time reactions to broadcast content. RAI aims to optimize operations, increase sustainability, and support social inclusion, while also ensuring regulatory compliance with the AI Act. Challenges include competing with American and Chinese tech giants and avoiding technological lock-in by adopting open-source solutions. Collaboration at national and European levels is necessary for tailored AI development. Different types of AI, such as descriptive, predictive, and generative AI, are employed to enhance both content creation and consumption. | National | Italy | 2.024 | Internal management | Internal primary processes | No | No | G2G | x | x | x | https://www.osservatori.net/artificial-intelligence/convegno-ai-application-talk-2024-convegno/ | Learning | Machine learning | Generative AI | Knowledge representation | ||||||||||||||||||||||||||
| PSTW-231 | Innovative functionalities and AI for energy saving in the public sector | https://www.innovatieveoverheidsopdrachten.be/en/projects/innovative-functionalities-and-artificial-intelligence-energy-saving-public-sector | Terra is the patrimony and energy database, originated in the bosom of Flanders Radical Digital. The database bundles energy information and characteristics about the buildings and infrastructure of the Flemish public sector. One of the tasks of the VEB is to ensure that the data is optimally and actively used for initiating and monitoring energy saving processes and renewable energy projects. Within this PIO project, VEB, Facilities and Services and VEA work together to achieve the following objectives through smart use of this data: detect energy-saving potential in public buildings faster thanks to AI applications and smart algorithms; develop comprehensive real estate strategies with a lasting impact thanks to asset analyzes and professionally managed energy management; initiating measures and facilitating and monitoring OEPC contracts for the public sector through measurement and verification models; increase the impact of specific functionalities thanks to synergies with other projects and initiatives. It will be examined where AI can be used to achieve these objectives and whether a Software-as-a-Service (SaaS) model can offer added value. | Regional | Belgium | BE2 | Felmish Energy Company (VEB), Agency for Facility Operations (HFB) and Flemish Energy Agency (VEA) | Regional Government | Economic Affairs | Fuel and energy | In development | 2.021 | Analysis, monitoring and regulatory research | Prediction and planning | No | No | Artificial Intelligence | G2G | x | x | x | https://innovatieveoverheidsopdrachten.be/projecten/innovatieve-functionaliteiten-en-ai-voor-energiebesparing-de-publieke-sector | Reasoning | Automated reasoning | Planning and Scheduling | 15/11/2023 | |||||||||||||||||||
| PSTW-2314 | GLADGPT | https://www.sn.dk/art542048/gladsaxe/teknologi/borgmester-vi-har-60-robotter-i-fast-drift/ | The municipality of GLADSAXE will launch a form of municipal ChatGPT, which they call GladGPT, and they are launching a municipal, AI-based "GladGBT" aimed at employees in the municipality. The ChatGBT will help with idea generation, speech writing, proofreading | Local | Denmark | 2.024 | Internal management | Internal primary processes | No | No | G2G | x | x | https://www.linkedin.com/posts/gladsaxekommune_gladsaxe-digitalisering-ai-activity-7137789235339612162-Ak4F?utm_source=share&utm_medium=member_desktop | Learning | Machine learning | Generative AI | Automated reasoning and Automated Decision Making (ADM) | |||||||||||||||||||||||||||
| PSTW-2332 | Three judges under suspicion of ‘cheating’ with artificial intelligence | https://www.portugalresident.com/three-judges-under-suspicion-of-cheating-with-artificial-intelligence/ | Three judges involved in the ruling are under suspicion of having drafted a judgement with the help of artificial intelligence. This particular case involves a process brought against former PSD MP Helena Lopes da Costa and various other defendants connected at the time with Santa Casa da Misericórdia for suspicions of economic participation in business and abuse of power. | National | Portugal | 2.024 | Enforcement | Predictive enforcement processes | No | No | G2G | x | x | x | https://www.portugalresident.com/three-judges-under-suspicion-of-cheating-with-artificial-intelligence/ | Ethics and Philosophy | Natural language processing | Generative AI | |||||||||||||||||||||||||||
| PSTW-2334 | Camilla, Virtual assistant for public competitions | https://www.formez.it/notizie/ia-al-via-primo-assistente-virtuale-concorsi | Artificial intelligence at the service of public competitions. The collaboration between Formez and CSI Piemonte has created the first virtual assistant that uses generative AI to answer questions from those interested in open notices relating to competitions managed by Formez. Starting today, in fact, on the institutional website www.formez.it at the link https://camilla.formez.it, candidates' questions on competitions managed by the Institute in-house at the Department of Public Function will be answered on an experimental basis by Camilla, the digital assistant, operating 24/7, which will help reduce waiting times for answers, while at the same time helping citizens to find their way more easily in the world of public competitions. The digital assistant is the result of over 500 tests, by a task force composed of 14 Formez officials, with an average age of 32, and the technical contribution of a partner of excellence such as CSI Piemonte. | National | Italy | 2.024 | Public services and engagement | Engagement management | No | No | G2C | x | https://www.corrierecomunicazioni.it/pa-digitale/intelligenza-artificiale-arriva-camilla-il-chatbot-che-rivoluziona-i-concorsi-pubblici/ | Learning | Machine learning | Generative AI | Automated reasoning and Automated Decision Making (ADM) | Knowledge representation | |||||||||||||||||||||||||||
| PSTW-234 | Customer call analysis - Finding patterns in the reasons for customer inquiries | https://www.kratid.ee/en/eng-kratid | The Social Insurance Board, in cooperation with Feelingstream, conducted five pilot projects aimed at analyzing customer calls and web chats in detail and finding patterns in the reasons for customer inquiries. As part of the pilot, the Feelingstream application transcribed the Social Insurance Board's calls from May to August 2020 (3 months) in Estonian and Russian. The Feelingstream application provides an opportunity to get both a statistical overview and a detailed understanding of customers' concerns across several customer communication channels - calls, emails and chatbot. Customer contact analysis is the fastest and most immediate way to find places in services that the customer is in trouble with and that can be changed quickly. The analysis creates insights for managerial decision-making, which in turn leads to better and more efficient public services. The pilot project involved an information line manager and two service managers. In the pilot project, SKA chose Feelingstream as a partner, which specializes in analyzing customer contacts in Estonian and Russian. The analysis creates insights for managerial decision-making, which in turn leads to better public services to make them faster and more convenient for citizens to use. | National | Estonia | EE | Social Insurance Board | Central-Government | Social protection | Social protection n.e.c. | Pilot | 2.021 | Public services and engagement | Engagement management | No | No | Artificial Intelligence | G2C | x | x | https://www.kratid.ee/kasutuslood-kratid | Communication | Natural language processing | Machine learning | text analysis | 15/11/2023 | |||||||||||||||||||
| PSTW-237 | Bürokratt – a virtual assistant for the Public Administration | https://www.ria.ee/en/state-information-system/machine-learning-and-language-technology-solutions/burokratt#implementation | A bureaucrat is not just an IT development project to create an Estonian national virtual assistant, i.e. a kratt interface for using services – although this may be necessary as an intermediate step. Instead, in the future, a bureaucrat will allow a person from any device and through a virtual assistant to get everything they need done in one communication session. The bureaucrat is thus an interoperable network of public sector kratts attached to national information systems, as well as those provided by the private sector, which, from the user's point of view, acts as a single channel for obtaining public direct and information services. | National | Estonia | EE | Information System Authority of the Republic of Estonia | Central-Government | General public services | General public services n.e.c. | In development | 2.022 | Public services and engagement | Engagement management | No | No | Artificial Intelligence | G2C | x | x | x | x | x | https://www.kratid.ee/kasutuslood-kratid | Communication | Natural language processing | Machine learning | Automated reasoning | automatic translation | 15/11/2023 | |||||||||||||||
| PSTW-238 | Forecasting models Road Administration (Roads conditions and return of investments) | https://its-estonia.com/2022/02/08/road-traffic-accident-prediction-model/ | The Estonian Road Administration is developing forecasting models to determine the condition of roads and the return on investment. This allows you to predict where investments should be directed to get the most out of your projects. | National | Estonia | EE | Estonian Road Administration | Central-Government | Economic Affairs | Transport | In development | 2.020 | Analysis, monitoring and regulatory research | Prediction and planning | No | No | Artificial Intelligence | G2G | x | x | x | x | https://www.kratid.ee/kasutuslood-kratid | Planning | Planning and Scheduling | Machine learning | 15/11/2023 | ||||||||||||||||||
| PSTW-2394 | Assistente Virtuale Julia | https://julia.comune.roma.it/it/ | Julia is an advanced virtual assistant developed by the Municipality of Rome in collaboration with Microsoft and OpenAI, designed to enhance the experience of tourists and residents, especially during significant events like the 2025 Jubilee. Julia offers personalised services to meet diverse user needs. With an estimated 35 million visitors expected during the 2025 Jubilee, Julia serves as a crucial tool for managing tourism flow, reducing congestion at major sites, and promoting sustainable tourism by highlighting diverse locations. This initiative exemplifies Rome's commitment to leveraging artificial intelligence to improve urban services and enrich the experiences of both visitors and residents. It is available 24/7 and it understands more than 80 languages. | Local | Italy | 2.025 | Public services and engagement | Service personalisation (various) | No | No | G2C | x | x | x | x | Self-reporting tool | Learning | Machine learning | Generative AI | chatbot | |||||||||||||||||||||||||
| PSTW-241 | PPA Information Phone call transcription for customers analysis different languages | https://www.kratid.ee/kasutuslood-kratid | Pilot project of Police and Border Guard Board (PPA), use an AI application based on the analysis of customer contacts in several different languages, including Estonian and Russian. During the pilot, the PBGB took on two focuses: directing customers to use more e-channels and improving the display and content of customer information. The pilot project focused on calls concerning the issuance of documents. This was already known to be the biggest reason customers call. The self-service for applying for identity cards and travel documents created by the PBGB has led a quarter of applications to the e-channel. The analysis carried out indicated that since the request for documents takes place every 5-10 years, a long enough time has passed since the previous procedure that next time the clients will no longer remember the right steps to do. The analysis identified those bottlenecks that prevent customers from getting in trouble and further digitizing the document issuance service. | National | Estonia | EE | Police and Border Guard Board (PPA) | Central-Government | Public order and safety | Police Services | Implemented | 2.020 | Analysis, monitoring and regulatory research | Monitoring policy implementation | No | No | Artificial Intelligence | G2G | x | x | x | x | https://www.kratid.ee/kasutuslood-kratid | Perception | Audio processing | Machine learning | 15/11/2023 | ||||||||||||||||||
| PSTW-2417 | AI assistant Hankintavälkky - Hilma Procurement Manual Assistant | http://annualreport2024.hansel.fi/renewing-procurement/digital-services-to-assist-customers-developed/ | Hansel, Finland’s central procurement unit, has developed and implemented an AI chatbot designed to simplify access to information on public procurement for both internal and external users. This initiative is part of Hansel’s broader strategy to leverage digital services and generative AI to enhance operational efficiency, transparency, and user experience in public sector procurement. Developed using a third-party AI solution developed by twoday hosted on Microsoft Azure, the assistant leverages OpenAI’s language models to generate answers based solely on the Procurement Manual. The aim was to create an AI assistant capable of answering user queries based on the manual’s content, thus making procurement information easier to search and use. | National | Finland | 2.024 | Public services and engagement | Service personalisation (various) | No | No | G2B | x | x | x | x | https://www.ipa.government.bg/sites/default/files/report_generative_ai_in_public_administration_en.pdf | Learning | Machine learning | Generative AI | chatbot | |||||||||||||||||||||||||
| PSTW-2419 | NeuraBot - Chabot for German municipal citizen services | https://www.neuraflow.de/loesungen/neurabot | NeuraBot is an intelligent chatbot developed by Neuraflow GmbH to enhance municipal citizen services. It addresses routine inquiries, such as administrative procedures, event information, and general city-related questions, by understanding natural language inputs and providing precise answers from the city's knowledge base. Operating 24/7 in 95 languages, NeuraBot ensures citizens receive timely responses without waiting, thereby freeing municipal staff to focus on more complex tasks that require personal attention. | Local | Germany | 2.024 | Public services and engagement | Service personalisation (various) | No | No | G2C | x | x | x | x | https://ecatalogue.firabarcelona.com/smartcityexpo2024/product/64883/detail?lang=en_GB | Learning | Machine learning | Generative AI | chatbot | |||||||||||||||||||||||||
| PSTW-242 | Identification of forest tree species, forest clearing and forest height | https://sciendo.com/it/article/10.2478/fsmu-2020-0016 | Together with the development partner, the Environmental Agency and KEMIT have created a remote forest monitoring information system that enables the keeping of records of forest resources in georeferenced form and the collection and sharing of operational forest information. The created solution is semi-automatic, based partly on machine learning algorithms, partly on visual inspection of remote sensing data and partly on third party software solutions. Remote sensing data are mainly used as source data, but forest notifications, soil maps and other data (incl. Teaching and validation data) are also input. As a result of the processing, all-Estonian map layers are completed for the most important assessment features, such as a raster map of tree vegetation tree species (for identification by main tree species). | National | Estonia | EE | Environmental Agency | Central-Government | Environmental Protection | Protection of biodiversity and landscape. | In development | 2.020 | Analysis, monitoring and regulatory research | Prediction and planning | No | No | Artificial Intelligence | G2G | x | x | x | https://www.kratid.ee/kasutuslood-kratid | Perception | Computer vision | Machine learning | 15/11/2023 | |||||||||||||||||||
| PSTW-2420 | Neuropolis - Information System rethought in the City of Freiburg | https://www.neuraflow.de/loesungen/neurapolis | In modern administrations, the volume of documents, minutes, and resolutions is constantly increasing. Locating the right information for well-informed decisions can be a time-consuming task, particularly when dealing with complex matters or events that occurred years ago. neurapolis offers a new approach to research. This intelligent search solution comprehends questions posed in natural language and scans thousands of documents within the council information system in a matter of seconds. It delivers source-supported answers directly to the user, presenting even complex issues in a clear and accessible manner. As a result, employees are able to dedicate their time to working with the information itself, rather than spending significant effort searching for it. | Local | Germany | 2.024 | Public services and engagement | Service personalisation (various) | No | No | G2G | x | x | x | x | https://www.neuraflow.de/referenzen | Learning | Machine learning | Generative AI | natural language generation | |||||||||||||||||||||||||
| PSTW-2421 | AI System for Autonomous Shuttle in the City of Tartu | https://prd-mediarepository.cwsfirabarcelona.com/ecatalogue/J078024/files/products/64568/Public%20articles%20about%20AI%20Add-On%20System%20for%20Autonomous%20Shuttle%20from%20Avanti%20R&D%20Inc.pdf | Add-on AI System for Autonomous Shuttles enhances public transportation with advanced AI-driven safety, efficiency, and user experience improvements. It features sit/stand detection for passenger safety, demographic-targeted multilingual media, VRU collision avoidance using real-time roadside sensor data, origin-destination metrics for travel pattern analysis, and an onboard LLM for GDPR-compliant, localised passenger information. This comprehensive solution optimises shuttle operations, making smart city transit safer and more user-friendly. This was tested in the City of Tartu in the path between the Tartu City Museaum and the Estonian National Museum. | Local | Estonia | 2.024 | Public services and engagement | Service integration (various) | No | No | G2C | x | x | x | x | https://prd-mediarepository.cwsfirabarcelona.com/ecatalogue/J078024/files/products/64568/Public%20articles%20about%20AI%20Add-On%20System%20for%20Autonomous%20Shuttle%20from%20Avanti%20R&D%20Inc.pdf | Integration and Interaction | Connected and Automated vehicles | Computer vision | ||||||||||||||||||||||||||
| PSTW-2422 | AI-Traffic solutions used in multiple Italian public administrations to monitor traffic | https://prd-mediarepository.cwsfirabarcelona.com/ecatalogue/J078024/files/products/65103/202305_Flyer_AITRAFFIC_EN.pdf | AI-TRAFFIC is a video analytics solution powered by advanced deep learning, offering real-time vehicle monitoring with high accuracy—even in challenging conditions like tunnels, poor weather, or dense urban settings. Integrating features from AI-ROAD3D and AI-INCIDENT, it can classify vehicles, estimate speed and colour, and detect risky behaviours such as wrong-way driving or pedestrians in restricted zones. It also monitors traffic flow, congestion, and origin-destination patterns. Already adopted across Italian municipalities, airports, and beyond, AI-TRAFFIC enhances road safety and traffic management through intelligent automation. | Local | Italy | 2.024 | Enforcement | Smart Recognition processes | No | No | G2G | x | x | x | x | https://ecatalogue.firabarcelona.com/smartcityexpo2024/product/65103/detail?lang=en_GB | Perception | Computer vision | |||||||||||||||||||||||||||
| PSTW-2423 | AI4Life - AI-based smart intersection management system in Instanbul | https://www.urbantechnologyalliance.org/portfolio/urban-intersection-management/ | The AI4LIFE project targets urban challenges at intersections, which contribute to high greenhouse gas emissions, traffic congestion, and road fatalities, costing Europe billions annually. By developing an AI-based smart intersection management system, AI4LIFE aims to reduce traffic, emissions, accidents, and enhance urban quality of life. The city of Istanbul and Isbak (the municipal company of Istanbul) have deployed an AI-based smart intersection management system. This system is designed to reduce congestion by optimising traffic flow and reducing stop-and-go driving conditions, thereby cutting greenhouse gas emissions and reclaiming hours otherwise lost in traffic. | Local | Türkiye | 2.024 | Enforcement | Smart Recognition processes | No | No | G2G | x | x | x | x | https://ecatalogue.firabarcelona.com/smartcityexpo2024/product/65082/detail?lang=en_GB | Perception | Computer vision | |||||||||||||||||||||||||||
| PSTW-2429 | Video-based Intelligent solution for traffic monitoring in the Municipality of České Budějovice | https://ecatalogue.firabarcelona.com/smartcityexpo2024/product/64679/detail?lang=en_GB | České Budějovice, the largest city in Southern Bohemia, faced significant challenges in managing urban mobility. The city needed to address growing traffic congestion and improve overall transportation efficiency to sustain its economic and social activities. Sprinx, in partnership with distributor Gemtech and system integrators Abbas and Swarco Traffic CZ, implemented an advanced traffic analysis and monitoring system in České Budějovice using the analytics software, co.exist. The system utilises over 100 server-side Hanwha Vision cameras strategically placed throughout the city to monitor and analyse urban mobility. Key features of the solution include vehicle counting and classification, detection of stops within intersections, and identification of potential traffic jams. | Local | Czechia | 2.024 | Enforcement | Smart Recognition processes | No | No | G2G | x | x | x | https://sprinx.ai/case-studies/ | Perception | Computer vision | Planning and Scheduling | |||||||||||||||||||||||||||
| PSTW-2432 | Consult - AI for public engagement (part of the Humphrey toolkit) | https://ai.gov.uk/projects/consult/ | Consult is an AI-powered tool developed by the UK's Incubator for Artificial Intelligence (i.AI) in collaboration with the No10 Data Science team (10DS). It aims to streamline the analysis of public consultation responses by automatically identifying patterns and themes within large datasets. This automation allows policy makers to efficiently interpret public feedback, reducing the time and resources traditionally required for such analyses. By leveraging AI and data science techniques, Consult enhances the government's ability to develop informed policies based on comprehensive public input. i.AI has developed a brand new technique for topic modelling using Large Language Models (LLMs), that takes a two step approach: (1) Identify the themes in a set of responses that are descriptive, context aware and relevant to human analysts and (2) Map those themes back onto the responses. By breaking down the process into these two steps, the app gives the human analysts full control over the process. The outputs here give the analysts key insights into the views of the public. | National | United Kingdom | 2.024 | Public services and engagement | Engagement management | No | No | G2G | x | x | x | x | x | x | x | https://ai.gov.uk/projects/ | Learning | Machine learning | Generative AI | |||||||||||||||||||||||
| PSTW-2433 | Parlex - Forecasting Parliamentary Reactions (part of the Humphrey toolkit) | https://ai.gov.uk/projects/parlex-and-lex/ | Parlex allows users to forecast parliamentary reactions to proposed policies. By analysing years of parliamentary debate contributions from MPs and Peers, Parlex offers insights into how parliament might react to a new policy if it were debated tomorrow. This tool helps policy professionals gauge parliamentary sentiment towards specific issues, determining whether a policy will be well-received or face significant opposition. Using the Renters’ Rights Bill as an example, users are able to see which members of parliament have spoken about this topic in the past, and see a summary of their views, categorised by whether they are in favour or against the policy. This allows policy teams to understand the political climate and anticipate potential challenges or support for a policy before it is formally proposed and to build a parliamentary handling strategy. | National | United Kingdom | 2.024 | Analysis, monitoring and regulatory research | Innovating Public Policy | No | No | G2G | x | x | https://www.theguardian.com/technology/2025/jan/20/ai-tool-can-give-ministers-vibe-check-on-whether-mps-will-like-policies | Learning | Machine learning | Generative AI | ||||||||||||||||||||||||||||
| PSTW-2434 | Lex - Simplifying Legislative Research (part of the Humphrey toolkit) | https://ai.gov.uk/projects/parlex-and-lex/ | Lex is designed to aid in legislative research. Through the Lexplorer interface, users can ask questions in everyday language like, "Tell me about legislation on flying drones near airports," and receive a detailed analysis and summary of the relevant laws, citing precise sections of the legislation. This tool eliminates the need for users to have prior knowledge of where to look or the specific terms or keywords used in the relevant pieces of legislation. Lex is powered by nine tools that help it search, summarise and understand the interconnections between legislation, case law, and explanatory notes. We have indexed a vector database of over 1.5 million sections of legislation and 63,000 cases to power the search behind these tools. Further tools help it structure and improve its research process via an adversarial mechanism. Lex uses its legal expertise to inform which of these tools are best to help it provide a detailed analysis and summary of the relevant laws to answer a user query. | National | United Kingdom | 2.025 | Analysis, monitoring and regulatory research | Innovating Public Policy | No | No | G2G | x | x | https://ai.gov.uk/projects/parlex-and-lex/ | Learning | Machine learning | Generative AI | ||||||||||||||||||||||||||||
| PSTW-2435 | Minute - AI transcription service (part of the Humphrey toolkit) | https://ai.gov.uk/projects/minute/ | Minute is a secure AI transcription service developed by the UK's Incubator for Artificial Intelligence (i.AI). It produces customisable summaries tailored to the needs of public servants, enhancing efficiency in meeting documentation. | National | United Kingdom | 2.025 | Internal management | Internal support processes | No | No | G2G | x | x | x | https://ai.gov.uk/projects/ | Learning | Machine learning | Generative AI | |||||||||||||||||||||||||||
| PSTW-2436 | Caddy - AI powered tool for customer service functions (part of the Humphrey toolkit) | https://ai.gov.uk/projects/caddy/ | Caddy was born from a collaboration between i.AI and Citizens Advice Stockport, Oldham, Rochdale & Trafford (CASORT). This AI-powered assistant acts as a copilot for customer service agents, empowering them to provide high-quality, actionable advice quickly and securely. | National | United Kingdom | 2.024 | Public services and engagement | Service personalisation (various) | No | No | G2C | x | x | x | x | https://ai.gov.uk/projects/ | Learning | Machine learning | |||||||||||||||||||||||||||
| PSTW-2437 | Scout - AI-powered tool to improve government major project delivery | https://ai.gov.uk/projects/scout/ | Scout is an AI-powered tool developed by the UK’s Incubator for Artificial Intelligence (i.AI) to improve oversight of major government projects, which account for over £805 billion in whole-life spending. Currently, project reviews by the Infrastructure and Projects Authority (IPA) involve days of manual document analysis, risking inconsistency and knowledge silos. Scout streamlines this process by using AI to analyse review documents in under five minutes. It breaks down documents, generates summaries, and stores them in a vector database for fast retrieval. Scout includes two key modules: the Review module, which checks documents against IPA guidelines with source citations, and the Detect module, which finds patterns and potential issues across documents. All insights are grounded in official IPA review handbooks to ensure reliability. | National | United Kingdom | 2.024 | Internal management | Internal management processes | No | No | G2G | x | x | x | x | https://www.gov.uk/government/news/government-to-harness-the-power-of-ai-to-improve-public-project-delivery-under-new-framework | Learning | Machine learning | Generative AI | ||||||||||||||||||||||||||
| PSTW-2438 | Connect - AI to match capacity to demand in the Grid connections queue | https://ai.gov.uk/projects/connect/ | Connect is an AI-driven initiative by the UK's Incubator for Artificial Intelligence (i.AI) aimed at optimising the allocation of capacity in the national grid connections queue. By employing advanced matching algorithms, Connect seeks to align available grid capacity with demand more effectively, thereby reducing waitlists and encouraging investment in renewable energy projects. | National | United Kingdom | 2.024 | Internal management | Internal management processes | No | No | G2G | x | x | x | x | https://ai.gov.uk/projects/ | Learning | Machine learning | Optimisation | Planning and Scheduling | |||||||||||||||||||||||||
| PSTW-244 | Alarm Center Assistant for Risk Assessment | https://www.kratid.ee/kasutuslood-kratid | The emergency notification procedure process is very large-scale and complex, which is why rescue operators may make mistakes when giving a risk assessment and/or spend excessive time on it. When giving a threat assessment, the knowledge needs of at least three different agencies must be taken into account in order to send a resource, and at the same time, an emergency call must be processed within a minute. Gathering information under conditions of limited time resources is difficult for humans, and reducing errors is critical. The emergency center's threat assessment assistant is an artificial intelligence-based software development that, by transcribing an incoming call and taking into account previous actions, helps to provide the rescue operator with a typical case of the most likely event. | National | Estonia | EE | Emergency center | Central-Government | Public order and safety | Public order and safety n.e.c. | Implemented | 2.022 | Analysis, monitoring and regulatory research | Information analysis processes | No | No | Artificial Intelligence | G2G | x | x | x | https://www.kratid.ee/kasutuslood-kratid | Perception | Audio processing | Automated reasoning | 15/11/2023 | |||||||||||||||||||
| PSTW-2442 | VisitMadridGPT - Transforming tourism in Madrid | https://www.microsoft.com/en/customers/story/19546-madrid-destino-madrid-city-council-azure-open-ai-service | The City of Madrid has developed VisitMadridGPT, an AI-powered virtual assistant, using Microsoft Azure OpenAI Service. This innovative tool provides tourists with accurate, real-time information and personalised responses in over 95 languages, enhancing the overall visitor experience. Additionally, it allows city officials to analyze user interactions to better understand tourist needs. Notably, the assistant has achieved a low bounce rate, with users spending an average of four minutes and 18 seconds per session, indicating its effectiveness and user engagement. | Local | Spain | 2.024 | Public services and engagement | Service personalisation (various) | No | No | G2C | x | x | x | x | https://www.microsoft.com/en/customers/story/19546-madrid-destino-madrid-city-council-azure-open-ai-service | Learning | Machine learning | Generative AI | chatbot | |||||||||||||||||||||||||
| PSTW-2452 | AI-augmented system for predicting electricity consumption in Serbia | https://www.ekapija.com/en/news/4468129/eps-developed-an-ai-augmented-system-for-predicting-electricity-consumption | Electric Power Company of Serbia (EPS) has developed an AI-enhanced system for forecasting electricity consumption, leveraging machine learning techniques to predict demand with greater accuracy. This technology allows for optimised energy distribution and grid management by anticipating fluctuations in usage. The system integrates real-time data, helping to improve operational efficiency and resource allocation. It also supports the energy sector's efforts to enhance sustainability and reduce waste, ultimately contributing to smarter energy management across the grid. | National | Serbia | 2.023 | Analysis, monitoring and regulatory research | Prediction and planning | No | No | G2G | x | x | x | x | https://www.eupan.eu/wp-content/uploads/2024/12/HU_eNews-on-Examples-of-recently-launched-digital-public-service-innovations.pdf | Planning | Planning and Scheduling | |||||||||||||||||||||||||||
| PSTW-2459 | AMS Berufs Infomat - personalized career advice for job seekers | https://www.ams.at/arbeitsuchende/aus-und-weiterbildung/berufsinformationen/berufsinformation/berufsinfomat?open=berufsinfomat&ref=alexanderchukovski.com | The AMS Career Infomat answers questions about careers, training, and continuing education. It uses advanced AI technology, particularly ChatGPT, to formulate dynamic answers. | National | Austria | 2.024 | Public services and engagement | Service personalisation (various) | No | No | G2C | x | x | x | x | https://cdn-dynmedia-1.microsoft.com/is/content/microsoftcorp/microsoft/msc/documents/presentations/CSR/Governing-AI-Blueprint-for-Austria.pdf | Learning | Machine learning | Generative AI | ||||||||||||||||||||||||||
| PSTW-2462 | Generative-AI based chatbot for the Cypriot Government Portal | https://www.gov.cy/ | The "Digital Assistant" is the first Generative Artificial Intelligence application in the Cypriot public sector, and is operational on the government portal gov.cy. According to a statement by the Deputy Ministry of Research, Innovation, and Digital Policy, its goal is to facilitate quicker and more immediate communication between citizens and the state, providing information on issues of concern on a 24/7 basis. | National | Cyprus | 2.024 | Public services and engagement | Service personalisation (various) | No | No | G2C | x | x | x | x | https://fastforward.com.cy/tech/cyprus-launches-1st-ai-digital-assistant-govcy | Learning | Machine learning | Generative AI | ||||||||||||||||||||||||||
| PSTW-2469 | Streamlining Environmental Permitting Processes with Multi-Agent AI in Denmark | https://www.cbrain.com/case-study/ai-assisted-environmental-permitting | The digital transformation of the Danish environmental permitting process has improved efficiency, transparency, and compliance. By transitioning from a traditionally lengthy and manual process to a fully digital and AI-assisted system, the EPA has been able to process applications faster while maintaining regulatory integrity. The structured workflow has eliminated bottlenecks, ensuring that permits are reviewed and approved in a timely manner. The centralized platform has improved coordination among agencies and stakeholders, reducing uncertainty for project developers. Applicants now have real-time access to their application status, improving predictability in the permitting process. Additionally, the integration of AI has enhanced regulatory decision-making by providing caseworkers with access to historical data and analytical tools, improving both accuracy and efficiency. By leveraging digital tools and AI-driven insights, the Danish EPA has established a scalable and replicable model for modernizing environmental permitting. The new system not only accelerates approvals for renewable energy projects but also ensures that environmental regulations are enforced with greater consistency and reliability. The transformation of the permitting process serves as a model for other agencies seeking to optimise complex regulatory procedures while supporting national and international climate goals. The solution was designed with cBrain. | National | Denmark | 2.024 | Internal management | Internal primary processes | No | No | G2G | x | x | x | x | https://www.cbrain.com/company/about | Reasoning | Optimisation | Automated reasoning and Automated Decision Making (ADM) | ||||||||||||||||||||||||||
| PSTW-247 | Calculation of forest resources by remote sensing methods | https://www.kratid.ee/kasutuslood-kratid | Since 1999, during the annual statistical inventory of Estonian forests (SMI), field measurements have been made on 5,600 plots. Based on the data, statistical estimates of the forest resource are obtained, which are the basis for national reporting and the formulation of forest policy. The aim of the project is to develop a suitable methodology for the Estonian SMI to use multispectral space images and laser scanning data from aircraft to obtain forest resource estimates in the form of maps. In the course of the project, solutions are sought for the preparation of maps of the species composition, height and trunk volume of the stands using accurate measurement data of the trees growing on the plots as input to the models. The results are useful both for monitoring forests and for planning economic decisions at the stand level. | National | Estonia | EE | Environment Agency | Central-Government | Environmental Protection | Protection of biodiversity and landscape. | Implemented | 2.020 | Analysis, monitoring and regulatory research | Information analysis processes | No | No | Artificial Intelligence | G2G | x | x | https://www.kratid.ee/kasutuslood-kratid | Perception | Computer vision | Machine learning | 15/11/2023 | ||||||||||||||||||||
| PSTW-2471 | AI-driven citizen engagement platform for the City of Prague | https://rootcode.io/news/building-an-ai-driven-citizen-engagement-platform-for-prague | Rootcode, a global software engineering company, is collaborating with the City of Prague to develop an AI-driven citizen engagement platform. This initiative aims to streamline the reporting and resolution of citywide issues by enabling residents to report problems, which the platform then automatically categorises and routes to the appropriate municipal departments, eliminating the need for traditional email communications. The project is part of CommuniCity, a European Union-funded initiative focused on citizen-centric innovation, and is being developed in partnership with Prague's OICT organisation. This collaboration underscores Prague's commitment to digital innovation and AI adoption, enhancing public service efficiency and setting new standards in citizen engagement . | Local | Czechia | 2.025 | Public services and engagement | Service integration (various) | No | No | G2C | x | x | x | x | x | x | x | https://rootcode.io/news/building-an-ai-driven-citizen-engagement-platform-for-prague | Reasoning | Automated reasoning and Automated Decision Making (ADM) | ||||||||||||||||||||||||
| PSTW-2475 | ADLER: Local Language Models for Sensitive Data | https://www.bundesdruckerei.de/en/innovation-hub/project-ki-kc | ADLER (Ausführung datensicherer LLMs, evaluiert auf resilienten Geräten, “execution of data-secure LLMs, evaluated on resilient devices”) an on-edge document processing assistant, investigates how small language models can be operated locally on commercially available devices. This allows sensitive data to be processed directly on the work tool without having to upload it via networks. This strengthens data sovereignty and opens up new utilisation contexts, especially for confidential information such as VS-NfD data. | National | Germany | 2.023 | Internal management | Data Sharing Management | No | Yes | G2B | x | x | x | x | https://www.bundesdruckerei.de/en/innovation-hub/project-ki-kc | Learning | Machine learning | Generative AI | AI Services | |||||||||||||||||||||||||
| PSTW-2476 | MÖVE: Benchmarking of Language Models for Public Administration | https://www.bundesdruckerei.de/en/innovation-hub/project-ki-kc | MÖVE (Modelle für die öffentliche Verwaltung evaluieren, “evaluate models for public administration”) is a framework for evaluating language models with regard to their performance in administrative tasks, results in German and governance criteria such as social fairness, hallucinations (false or misleading results) and conformity with the AI regulation EU AI Act. The aim is to establish a sound basis for arriving at decisions on the use of language models in public administration. | National | Germany | 2.023 | Internal management | Internal support processes | No | Yes | G2G | x | x | x | x | https://www.bundesdruckerei.de/en/innovation-hub/project-ki-kc | Learning | Machine learning | Generative AI | AI Services | |||||||||||||||||||||||||
| PSTW-2477 | AI Language Assistant for the German Federal Administration: Efficient Information Processing | https://www.bundesdruckerei.de/en/innovation-hub/project-ki-kc | The language model project for AI-supported text analysis enables documents to be analysed quickly and comprehensively in order to extract relevant information and thus support decision-making. Automatic summaries, topic-related analyses and the identification of responsibilities increase the efficiency of administrative work. | National | Germany | 2.023 | Analysis, monitoring and regulatory research | Information analysis processes | No | Yes | G2B | x | x | x | x | https://www.bundesdruckerei.de/en/innovation-hub/project-ki-kc | Learning | AI Services | |||||||||||||||||||||||||||
| PSTW-2478 | PLAIN: a data analysis platform for the entire German federal administration | https://www.bundesdruckerei.de/en/innovation-hub/plain | PLAIN (Platform Analysis and Information System) enables the public administration to make decisive progress in the use of data for political action. In accordance with the Federal Government’s data and digital strategy, PLAIN is the cross-departmental infrastructure that lays the technological foundation for AI and data applications in the Federal Administration. The aim of PLAIN is to establish a standard platform for the entire federal administration to securely process and analyse large, heterogeneous data sets – without thematic restrictions. This platform provides the Federal Government’s ministries and subordinate federal authorities with a solution to increase their political analysis capabilities and implement many of their data-driven, demanding tasks and projects. | National | Germany | 2.024 | Analysis, monitoring and regulatory research | Information analysis processes | No | Yes | G2G | x | x | x | https://www.bundesdruckerei.de/en/innovation-hub/plain | Planning | Searching | AI Services | |||||||||||||||||||||||||||
| PSTW-248 | Water level monitoring in coastal seas and lakes using satellite altimetry | https://www.kratid.ee/kasutuslood-kratid | The project developed a prototype for operational flood monitoring using radar remote sensing data and water level remote sensing data to improve hydrological monitoring and marine forecasting services. Hydrological monitoring includes on-site measurements of water levels and flows at national hydrometric stations. Prototypes for remote water level monitoring enable the combined use of remote sensing data, forecasting models and artificial intelligence to provide better water level information to interested parties and the public. Integrating altimetry data into hydrological monitoring would help improve the spatial coverage of observations on the Great Lakes and improve the accuracy of sea level forecasting. | National | Estonia | EE | Environment Agency | Central-Government | Environmental Protection | Environmental protection n.e.c. | Implemented | 2.019 | Analysis, monitoring and regulatory research | Information analysis processes | No | No | Artificial Intelligence | G2G | x | x | x | https://www.kratid.ee/kasutuslood-kratid | Perception | Computer vision | Knowledge representation | 15/11/2023 | |||||||||||||||||||
| PSTW-2485 | Smart Street Lighting | https://loriot.io/use-cases/smart-lighting.html | LORIOT's smart street lighting solution, implemented in Hafnarfjörður, Iceland, utilises LoRaWAN®-enabled controllers and the inteliLIGHT® platform to modernise urban lighting infrastructure. This system allows for precise control over 6,000 streetlights, enabling adaptive lighting based on real-time conditions. The integration has led to a 35% reduction in energy consumption and a 42% decrease in maintenance costs, while also enhancing public safety and supporting sustainability goals. The solution provides a scalable foundation for future smart city applications. | Local | Iceland | 2.025 | Internal management | Internal support processes | No | No | G2G | x | x | x | x | https://loriot.io/usecases.html | Planning | Optimisation | |||||||||||||||||||||||||||
| PSTW-2487 | Water Network Monitoring | https://loriot.io/use-cases/water-monitoring.html | LORIOT's Water Network Monitoring use case, implemented by WaterScope Zrt. in Tápióság, Hungary, demonstrates the application of IoT technology to enhance water supply and quality in areas lacking traditional infrastructure. By deploying WaterScope S2N data acquisition and wireless transmission devices, the system continuously monitors pumping stations, measuring parameters such as pump performance, operating time, power consumption, water pressure, and water meter data. These devices utilise a LoRa network to transmit data to the LORIOT Network Management System, enabling real-time monitoring and alerting capabilities. The solution effectively operates without human intervention, even in remote locations, and provides actionable insights to optimise water distribution and reduce losses. This initiative contributes to sustainable water management practices and supports cost savings for water utilities | Regional | Hungary | 2.024 | Internal management | Internal support processes | No | No | G2G | x | x | x | x | https://loriot.io/usecases.html | Planning | Optimisation | |||||||||||||||||||||||||||
| PSTW-2488 | Data-driven Wildfire Prevention System for Forest | https://loriot.io/use-cases/wildfire-prevention-system.html | LORIOT’s Wildfire Prevention System, deployed in Salzburg, Austria, uses LoRaWAN® sensors to monitor environmental factors like weather and soil moisture across 350 square kilometers. Developed with the Forest Department of Salzburg, it calculates the Fire Weather Index to provide real-time fire risk data. This helps authorities make timely decisions on fire prevention, improving forest safety and supporting sustainable management. | Local | Austria | 2.023 | Internal management | Internal support processes | No | No | G2G | x | x | x | x | https://loriot.io/usecases.html | Planning | Optimisation | |||||||||||||||||||||||||||
| PSTW-2489 | German Ministry of Research, Technology, and Space provides a popular chatbot to make project funding regulations more accessible | https://www.deepset.ai/case-studies/bundesministerium-fur-forschung-technologie-und-raumfahrt-bmftr | The deepset AI Platform is an enterprise-grade solution designed to streamline the development and deployment of custom generative AI agents and applications. Built on the open-source Haystack framework, it offers a modular and composable architecture that enables organisations to rapidly prototype, test, and scale AI solutions without vendor lock-in. The platform has had application also at the Federal Government level. | National | Germany | 2.025 | Internal management | Internal support processes | No | Yes | G2G | x | x | x | https://www.deepset.ai/ | Learning | Machine learning | Generative AI | |||||||||||||||||||||||||||
| PSTW-249 | Marakratt - Personal learning path infrastructure | https://www.kratid.ee/kasutuslood-kratid | In the framework of the project, a proof-of-concept solution for students supporting individual study paths was created. During the project, the use of machine learning was tested in the creation of educational material recommendation models. Prototype-like models were also created to help automate the personalization of educational materials and activities used in learning, based on learners' interests, knowledge and abilities. | National | Estonia | EE | Board of Education and Youth | Central-Government | Education | R&D education. | Pilot | 2.020 | Public services and engagement | Service personalisation (various) | No | No | Artificial Intelligence | G2C | x | x | x | x | https://www.kratid.ee/kasutuslood-kratid | Reasoning | Automated reasoning | Knowledge representation | 15/11/2023 | ||||||||||||||||||
| PSTW-2499 | AI-Tour guide in the City of Tampere | https://www.bable-smartcities.eu/explore/use-cases/use-case/ai-tour-guide.html | The "AI Tour Guide" project in Tampere, Finland, introduces an innovative approach to enhancing the tourist experience through the use of smart glasses equipped with an AI-powered assistant. These glasses provide real-time, multilingual information and recommendations about local attractions, such as monuments, restaurants, and museums. Tourists can rent the smart glasses from various Points-of-Service (POS) located at key spots like the airport, train station, and the Visit Tampere office. The AI assistant, powered by Meta AI technology, ensures that visitors receive up-to-date and comprehensive information, making their exploration of Tampere more engaging and informative. Additionally, local businesses have the opportunity to update their information in the database, promoting their offerings directly to tourists and enhancing the overall visitor experience. | Local | Finland | 2.024 | Public services and engagement | Service personalisation (various) | No | No | G2C | x | x | x | x | https://www.bable-smartcities.eu/explore/use-cases.html | Perception | Computer vision | |||||||||||||||||||||||||||
| PSTW-25 | e-Residency - Chatbot for customer assistance | https://chatbotsmagazine.com/how-e-residency-of-estonia-uses-ai-to-help-users-get-answers-instantly-and-increase-customer-e07e052beb4f | Artificial Intelligence (AI) customer service assistant for the Republic of Estonia’s e-Residency organisation. Together, the organisation decided to tackle the challenge of increasing customer support response time without hiring additional people. The solution is simple , i.e. an Artificial Intelligence chatbot with a live-chat interface. | National | Estonia | EE | e-Residency organization | Central-Government | General public services | General services. | Implemented | 2.018 | Public services and engagement | Engagement management | No | No | Artificial Intelligence | G2B | x | x | x | x | https://medium.com/e-residency-blog/how-we-use-ai-to-help-users-get-answers-instantly-and-increase-customer-satisfaction-95d1a06caad | Communication | Natural language processing | Automated reasoning | chatbot | 06/10/2023 | |||||||||||||||||
| PSTW-250 | Salme - Speech recognition in courts | https://www.compriseh2020.eu/speech-recognition-in-estonian-courts/ | Speech recognition software enables the transcription of a written transcript of a hearing ('the transcript'), which is used to draw up the minutes of the hearing. COMPRISE H2020 project is experimenting a solution for this. Tilde – a leading European language technology company – in collaboration with the Estonian national Centre of Registers and Information Systems (RIK) has developed a solution for automated transcription of court hearings in all 9 national and regional courts of the country. The solution has brought significant improvements to the efficiency and speed of producing court session recordings and protocolling. Speech recognition models have been adapted for the rather rich domain content – more than 800 hours of transcribed audio files have been used for the development of the acoustic models and over 800 million words worth of textual data have been used for the custom language model development. As a result, the solution which provides for real-time, as well as offline speech recognition has high quality of speech recognition, where word error rates (WER) vary between 8 and 15%, and this is a very good result given the actual conditions at court hearings. This solution is built to run on the RIK’s infrastructure thus safeguarding the security and availability to authorized users only. | National | Estonia | EE | Courts of Estonia and Registers and Information Systems Center | Central-Government | Public order and safety | Law courts | Implemented | 2.019 | Internal management | Internal support processes | No | No | Artificial Intelligence | G2G | x | x | x | https://www.kratid.ee/kasutuslood-kratid | Perception | Audio processing | Machine learning | Natural language processing | speech recognition | 15/11/2023 | |||||||||||||||||
| PSTW-2502 | Regional AI Hub/Centres for Environmental Data and Sustainable Mobility | https://innovazione.gov.it/notizie/articoli/il-dipartimento-regioni-e-province-autonome-insieme-per-l-innovazione/ | AI Regional Hubs for Environmental Data and Sustainable Mobility, developed within a federated framework and presented by the Lombardy Region (lead partner) together with the Veneto Region, aim to create a “smart land” through advanced analytical models built on a federated data architecture. The objective is to optimise environmental and mobility policies by leveraging artificial intelligence on a transregional scale to foster innovation and sustainability. | Regional | Italy | 2.025 | Internal management | Internal support processes | No | Yes | G2G | x | x | x | x | x | https://innovazione.gov.it/notizie/articoli/il-dipartimento-regioni-e-province-autonome-insieme-per-l-innovazione/ | Planning | Optimisation | ||||||||||||||||||||||||||
| PSTW-2503 | Regional AI Hubs/Centres for the PA | https://innovazione.gov.it/notizie/articoli/il-dipartimento-regioni-e-province-autonome-insieme-per-l-innovazione/ | AI Regional Hubs for Public Administration, presented by the Apulia Region (lead partner) in collaboration with Abruzzo, Marche, Umbria, Aosta Valley, Campania, and the Autonomous Province of Bolzano, aim to enhance the quality of administrative action and public sector work. The initiative supports human decision-making in public policy and technical-administrative procedures through the use of artificial intelligence. | Regional | Italy | 2.025 | Internal management | Internal support processes | No | Yes | G2G | x | x | x | x | x | https://innovazione.gov.it/notizie/articoli/il-dipartimento-regioni-e-province-autonome-insieme-per-l-innovazione/ | Planning | Optimisation | ||||||||||||||||||||||||||
| PSTW-2518 | ChatAmsterdam - AI assistant for civil servants | https://www.amsterdam.nl/nieuws/nieuwsoverzicht/chatamsterdam/ | The City of Amsterdam has developed its own AI assistant, ChatAmsterdam, to support municipal employees with tasks such as drafting texts, summarising documents, and analysing complex information. Designed as a secure alternative to commercial AI tools like ChatGPT, ChatAmsterdam ensures that all data entered remains within the municipality and is not used to train external language models. This initiative aligns with Amsterdam's Agenda Digitale Stad, aiming to create a digital city that is human-centred, reliable, and future-proof. Following a six-month pilot involving over 800 civil servants and more than 34,000 assignments, the municipality is exploring ways to share its knowledge with other governmental bodies to foster a robust, shared digital infrastructure. | Local | Netherlands | 2.024 | Internal management | Internal support processes | No | Yes | G2G | x | x | x | https://www.accountant.nl/nieuws/2025/5/amsterdam-maakt-eigen-ai-assistent-voor-ambtenaren/ | Learning | Machine learning | Generative AI | Natural language processing | chatbot | |||||||||||||||||||||||||
| PSTW-252 | Analysis of customer calls at the Estonian Social Insurance Board | https://www.kratid.ee/kasutuslood-kratid | The Social Insurance Board in cooperation with Feelingstream conducted a pilot project, the aim of which was to analyze customer calls and online chats in detail and to find patterns in the reasons for customer appeals. As part of the pilot, the Feelingstream application transcribed the speeches of the Social Insurance Board from May to August 2020 (3 months) in Estonian and Russian. | National | Estonia | EE | Social Insurance Board | Central-Government | Social protection | Social protection n.e.c. | Pilot | 2.020 | Analysis, monitoring and regulatory research | Information analysis processes | No | No | Artificial Intelligence | G2G | x | x | https://www.kratid.ee/kasutuslood-kratid | Integration and Interaction | Robotics and Automation | Natural language processing | 15/11/2023 | ||||||||||||||||||||
| PSTW-2520 | LOQUI - participation by speech | https://kia-digitalisering.nl/projecten/loqui-participation-by-speech | People with a language deficit such as new Dutch citizens, status holders and low-literates, together with digital/illiterate people and blind/visually impaired people, have difficulty with the digitalisation of society. Also with the use of digital government services. The aim of this project is to develop AI-based speech technology 'LOQUI' (Latin for 'to speak'). In this way, digital tools can be developed, allowing the aforementioned vulnerable target groups to participate better in (digital) society. d-centralise wants to develop a speech control tool in Dutch, English and Arabic. This makes all digital government services controllable with speech. Language deficits can also be recognised immediately. | National | Netherlands | 2.021 | Public services and engagement | Service personalisation (various) | No | No | G2C | x | x | x | x | https://nlaic.com/en/news/these-12-ai-companies-received-sbir-funding-to-develop-human-centric-ai-solutions/ | Communication | Natural language processing | |||||||||||||||||||||||||||
| PSTW-2521 | VITE-A2 Video and Text AI Analysis for Political Debates | https://vicarvision.nl/projects/VITE-A2/ | The VITE-A2 project (Video and Text AI Analysis for Political Debates) by VicarVision aims to enhance public understanding of municipal council meetings in the Netherlands through AI-driven analysis. Funded by a Dutch SBIR (Small Business Innovation Research) initiative, the project explores the use of video and text AI technologies to summarise and present lengthy and complex political discussions in a more accessible format. By leveraging expertise in emotion analysis, pose, voice, and sentiment detection, VITE-A2 seeks to bridge the gap between government and citizens, fostering increased civic engagement. The project's outcomes include a paper prototype and plans for further development based on feasibility studies and stakeholder feedback. | National | Netherlands | 2.022 | Internal management | Internal support processes | No | No | G2G | x | x | https://vicarvision.nl/ | Learning | Machine learning | Natural language processing | ||||||||||||||||||||||||||||
| PSTW-2529 | Spain’s Social Security administration: Using AI to deliver benefits to citizens more efficiently with the ISSA Social Security Virtual Assistant | https://cloud.google.com/customers/seguridad-social | The Social Security’s AI virtual assistant provides citizens with immediate, 24/7 access to official information and guidance on frequently requested procedures, thus significantly reducing administrative workloads. The chatbot initially tackled 37 core services, encompassing access to benefits as well as routine processes. On its first month, the chatbot had over 2 million interactions. | National | Spain | 2.020 | Public services and engagement | Service personalisation (various) | No | No | G2C | x | x | x | x | https://www.esade.edu/ecpol/wp-content/uploads/2025/05/AAFF_EsadeEcPolxGoogle_AIbenefits__ENG_vfinal.pdf | Communication | Natural language processing | chatbot | ||||||||||||||||||||||||||
| PSTW-253 | Identification of flammable dwellings | https://www.kratid.ee/kasutuslood-kratid | A project under development in Estonia about an AI solution for detection of flammable residential buildings Estonia | National | Estonia | EE | Estonian Fire Department | Central-Government | Public order and safety | Fire-protection services | In development | 2.020 | Enforcement | Predictive enforcement processes | No | No | Artificial Intelligence | G2G | x | x | x | https://www.kratid.ee/kasutuslood-kratid | Planning | Planning and Scheduling | Automated reasoning | 15/11/2023 | |||||||||||||||||||
| PSTW-2530 | Streamlining the Kit Consulting financing programme with AI | https://www.esade.edu/ecpol/wp-content/uploads/2025/05/AAFF_EsadeEcPolxGoogle_AIbenefits__ENG_vfinal.pdf | The Kit Consulting program, led by Red.es, supports SMEs with specialised digital consulting services and integrates a pioneering AI platform to streamline the verification of submitted documents. The AI system detects plagiarism, duplicates, and assesses document quality, significantly reducing review times and improving efficiency. By cutting processing time per document from 5 hours to 1.5 hours (an 80% reduction) the system will handle around 45,000 documents and perform up to 1 billion comparisons to ensure originality. Using Deep Learning and Large Language Models (LLMs), the platform enhances traceability, security, and quality in the aid payment process. Digital advisors and grant recipients submit documentation electronically, with AI playing a key role in expediting reviews. | National | Spain | 2.025 | Internal management | Internal support processes | No | No | G2G | x | x | x | x | https://www.red.es/es/actualidad/noticias/kit-consulting-incorporacion-ia-justificacion-ayudas | Learning | Machine learning | Generative AI | Deep learning | |||||||||||||||||||||||||
| PSTW-2532 | AI to streamline rental subsidies procedures in the Region of Valencia | https://www.esade.edu/ecpol/wp-content/uploads/2025/05/AAFF_EsadeEcPolxGoogle_AIbenefits__ENG_vfinal.pdf | The Valencian Regional Government has developed an AI-based solution to reduce administrative processing time and burdens associated with rental subsidy programs. This system automatically verifies rental contracts and pay slips, avoiding redundant request for documentation, streamlining the application process and significantly cutting verification time. This allows administrative personnel to focus solely on complex cases that require manual review, increasing overall efficiency. | Regional | Spain | 2.025 | Adjudication | Taking decisions on benefits | No | No | G2G | x | x | x | x | https://www.esade.edu/ecpol/wp-content/uploads/2025/05/AAFF_EsadeEcPolxGoogle_AIbenefits__ENG_vfinal.pdf | Reasoning | Automated reasoning and Automated Decision Making (ADM) | |||||||||||||||||||||||||||
| PSTW-2533 | Recognition of university degrees with AI | https://www.esade.edu/ecpol/wp-content/uploads/2025/05/AAFF_EsadeEcPolxGoogle_AIbenefits__ENG_vfinal.pdf | The Ministry of Science, Innovation, and Universities is starting to use AI and other automation technologies to streamline the process of recognition of foreign university degrees. The process not only eliminates repetitive paperwork but also will significantly shorten waiting times from years to months. This application will also improve the implementation of public policies, facilitating the incorporation of foreign professionals into tight, high-value areas of the labor market. | National | Spain | 2.025 | Enforcement | Certification and validation processes | No | No | G2G | x | x | x | x | https://www.esade.edu/ecpol/wp-content/uploads/2025/05/AAFF_EsadeEcPolxGoogle_AIbenefits__ENG_vfinal.pdf | Reasoning | Automated reasoning and Automated Decision Making (ADM) | |||||||||||||||||||||||||||
| PSTW-2534 | AI for Fiscal Compliance | https://sede.agenciatributaria.gob.es/Sede/en_gb/notas-prensa/notas-prensa/2025/marzo/17/agencia-tributaria-impulsa-control-personas-declarados.html | The Spanish Tax Agency (AEAT) is applying AI tools to enhance the effectiveness and efficiency of tax and customs operations, placing, strategic emphasis on taxpayer support, information management, and preventive measures. The adoption of AI technologies will streamline tax compliance procedures, simplifying taxpayer responsibilities and improving the accuracy of submitted data. By proactively addressing common reporting errors, AI solutions will substantially reduce the frequency of audits and subsequent tax regularisations. The implementation follows a "human-in-the-loop", approach, ensuring continuous human oversight. Tax professionals will actively review, assess, and validate AI-based tools and outcomes to guarantee reliability and accountability. | National | Spain | 2.025 | Internal management | Internal support processes | No | No | G2G | x | x | x | x | x | https://www.esade.edu/ecpol/wp-content/uploads/2025/05/AAFF_EsadeEcPolxGoogle_AIbenefits__ENG_vfinal.pdf | Learning | Machine learning | ||||||||||||||||||||||||||
| PSTW-2535 | BRAVA (Bid Rigging Algorithm for Vigilance in Antitrust) | https://blog.cnmc.es/2024/04/11/premio-a-brava-cnmc-contra-el-fraude-en-contratacion-publica/ | The Comisión Nacional de los Mercados y la Competencia (CNMC) has developed BRAVA (Bid Rigging Algorithm for Vigilance in Antitrust), an AI-powered tool designed to detect collusion in public procurement processes. By analysing large datasets from public tenders, BRAVA classifies bids as either competitive or potentially collusive, enhancing the CNMC's ability to identify and address anti-competitive practices. This innovative approach has earned the CNMC recognition in the "AI for Fraud and Corruption Detection" category at the Socinfo Digital Awards. | National | Spain | 2.024 | Enforcement | Supporting inspection processes | No | No | G2G | x | x | x | x | x | https://www.esade.edu/ecpol/wp-content/uploads/2025/05/AAFF_EsadeEcPolxGoogle_AIbenefits__ENG_vfinal.pdf | Learning | Machine learning | ||||||||||||||||||||||||||
| PSTW-2536 | HipatIA - AI-driven forecasting tool for educational services | https://www.ayesa.com/en/projects/hipatia-ai-powered-predictive-information-and-data-analysis-processing-tool/ | The Andalusian Regional Government is using an AI-driven forecasting tool to improve the impact and speed of educational services. One of the applications is “Hipatia”, an AI solution that implements predictive analytics methodologies to analyse historical student data to accurately predict key educational indicators. Hipatia helps the Department of Education and Vocational Training to anticipate critical needs such as teacher allocation, classroom requirements and vocational training. Thus, schools can offer student personalised support (such as tutoring and guidance) and education authorities can optimize professors or classroom planning decisions in advance. | Regional | Spain | 2.019 | Analysis, monitoring and regulatory research | Prediction and planning | No | No | G2G | x | x | x | x | x | https://www.esade.edu/ecpol/wp-content/uploads/2025/05/AAFF_EsadeEcPolxGoogle_AIbenefits__ENG_vfinal.pdf | Planning | Planning and Scheduling | ||||||||||||||||||||||||||
| PSTW-2537 | Smart lighting with AI in Barcelona | https://kurrant.com/kurrantly-news/barcelona-to-reduce-traffic-congestion-by-20-with-ai-powered-smart-traffic-lights/ | Barcelona has announced a new initiative to deploy AI-driven smart traffic lights, aiming to cut traffic congestion by 20%. The project, part of the city’s 2025 Sustainable Mobility Plan, will use sensors and AI algorithms to adjust traffic light timings in real time based on traffic density. Developed in partnership with local startups the system aims to cut travel times during peak hours and reduce CO2 emissions. | Local | Spain | 2.025 | Analysis, monitoring and regulatory research | Prediction and planning | No | No | G2G | x | x | x | x | https://www.esade.edu/ecpol/wp-content/uploads/2025/05/AAFF_EsadeEcPolxGoogle_AIbenefits__ENG_vfinal.pdf | Planning | Optimisation | |||||||||||||||||||||||||||
| PSTW-2538 | ADIA - the AI Document Assistant for spanish Courts | https://www.administraciondejusticia.gob.es/-/adia-anonimizado-de-documentos | The ADIA (AI Document Assistant) is a tool from Spain’s Ministry of Justice designed to streamline document handling in judicial processes. It allows users, especially legal professionals, to anonymise and summarise documents quickly and securely. Accessible via the internal network and SARA, it removes sensitive personal data to ensure confidentiality and generates condensed versions that capture key information efficiently. This service operates nationwide, automatically processing uploads through a web interface integrated with existing judicial systems to support privacy and efficiency. | National | Spain | 2.023 | Internal management | Internal support processes | No | No | G2G | x | x | x | x | x | https://www.esade.edu/ecpol/wp-content/uploads/2025/05/AAFF_EsadeEcPolxGoogle_AIbenefits__ENG_vfinal.pdf | Communication | Natural language processing | ||||||||||||||||||||||||||
| PSTW-2539 | Canal Empresa - reducing administrative burden and providing regulatory information for businesses | https://canalempresa.gva.es/va/ | The Generalitat Valenciana has launched Canal Empresa, a digital platform designed to streamline and simplify interactions between businesses, self-employed professionals, and public administration. Serving as a centralised hub, it consolidates information and procedures from the Generalitat and its public sector entities, and includes a virtual assistant to facilitate immediate interaction and guidance for users. | Regional | Spain | 2.025 | Public services and engagement | Service personalisation (various) | No | Yes | G2B | x | x | x | x | https://www.esade.edu/ecpol/wp-content/uploads/2025/05/AAFF_EsadeEcPolxGoogle_AIbenefits__ENG_vfinal.pdf | Communication | Natural language processing | chatbot | ||||||||||||||||||||||||||
| PSTW-254 | Crop detection from Sentinel-1 and -2 time series using deep learning methods | https://www.kratid.ee/kasutuslood-kratid | Within the framework of the project, together with Estonian universities, a methodology for the identification of agricultural crops suitable for Estonian conditions was developed. The study combined data from the Sentinel 1 and 2 satellites on soil type, average daily air temperature and precipitation, and showed that it is possible to identify crop classes with over 90% accuracy: potatoes, field peas and beans, summer and winter canola and canola, maize, rye, winter wheat and -barley. It was not possible to identify berry and fruit tree plantations and carrot and beetroot plantations with sufficient accuracy. The developed methodology is planned to be introduced both in PRIA and for the benefit of the Estonian state more broadly - to produce objective and uniform quality agricultural statistics. | National | Estonia | EE | Ministry of Rural Affairs | Central-Government | Economic Affairs | Agriculture, forestry, fishing and hunting | Implemented | 2.020 | Analysis, monitoring and regulatory research | Prediction and planning | No | No | Artificial Intelligence | G2G | x | x | https://www.kratid.ee/kasutuslood-kratid | Perception | Computer vision | Machine learning | 15/11/2023 | ||||||||||||||||||||
| PSTW-2540 | PREDUCA - Student learning pathways personalisation | https://www.juntadeandalucia.es/sites/default/files/2023-03/BORRADOR_ESTRATEGIA_IA_2_0.pdf | Preduca is a system developed by the Andalusian Government to personalise student learning pathways and support data-driven planning in public education by predicting each student’s educational needs. Built on Hipatia (case PSTW-2536), and integrated into the regional school management system, it uses historical academic and behavioral data to identify behavior patterns and recommend tailored educational interventions. This enables educators to tailor lesson plans, materials, and classroom activities to the specific profile of each student: for instance, early support for at-risk students or personalized challenges for high-achievers. | Regional | Spain | 2.023 | Public services and engagement | Service personalisation (various) | No | No | G2C | x | x | x | https://www.esade.edu/ecpol/wp-content/uploads/2025/05/AAFF_EsadeEcPolxGoogle_AIbenefits__ENG_vfinal.pdf | Planning | Planning and Scheduling | recommender system | |||||||||||||||||||||||||||
| PSTW-2541 | ESKOLA ADIMENTSUA - Automation, robotics, and artificial intelligence in teaching | https://www.euskadi.eus/eskola-adimentsua/web01-a3hsare/es/ | This initiative for the 2024-25 academic year, promotes active learning and the incorporation of advanced digital technologies into the educational experience in a context in which, as the Consejería de Educación itself emphasizes, "automation, robotics, and artificial intelligence are producing profound changes in our society, redefining our ways of learning, working, and relating to one another." One component of Eskola Adimentsua is teacher training. The program offers educators mentoring and horizontal coordination mechanisms for incorporating computational thinking, programming, and the development of building blocks for building more advanced digital skills. Teachers will have this support throughout the entire process, which will help them gain the confidence and skills to incorporate this knowledge and tools into their classrooms. This investment not only improves digital skills but also makes educators drivers of innovation for the future. | National | Spain | 2.024 | Analysis, monitoring and regulatory research | Innovating Public Policy | No | No | G2C | x | x | x | https://www.esade.edu/ecpol/wp-content/uploads/2025/05/AAFF_EsadeEcPolxGoogle_AIbenefits__ENG_vfinal.pdf | Services | AI Services | ||||||||||||||||||||||||||||
| PSTW-2542 | AI to anticipate peaks in Hospital La Fe (Valencia) | http://www.lafe.san.gva.es/noticias/-/asset_publisher/D6Zy/content/la-fe-disena-y-desarrolla-una-solucion-de-inteligencia-artificial-para-anticipar-picos-de-presion-asistencial/maximized | The Hospital Universitari i Politècnic La Fe in Valencia has developed Spain’s first artificial intelligence (AI) tool designed to anticipate surges in patient demand in its Adult Emergency Department. This AI system combines anonymised historical data with real-time information to predict the likelihood of patient hospitalisation. By identifying key factors—such as patient age, triage priority, previous conditions, past admissions, and diagnostic test results—it helps hospital staff take preventive actions and manage resources more efficiently. | Local | Spain | 2.024 | Analysis, monitoring and regulatory research | Prediction and planning | No | No | G2G | x | x | x | x | https://www.esade.edu/ecpol/wp-content/uploads/2025/05/AAFF_EsadeEcPolxGoogle_AIbenefits__ENG_vfinal.pdf | Planning | Planning and Scheduling | Optimisation | ||||||||||||||||||||||||||
| PSTW-2545 | PALOMA - Madrid’s AI-powered virtual assistant | https://www.mascomunidad.org.ar/paloma-la-asistente-virtual-con-la-que-madrid-combate-la-soledad-entre-personas-mayores/ | “Paloma” is Madrid’s AI-powered virtual assistant developed by the Social Serives area aimed at proactively tackling unwanted loneliness among elderly residents. This assistant systematically contacts citizens aged over 75 who live alone, initiating personalised phone conversations to assess their well-being through a brief questionnaire in a procedure that fully respects privacy and protects underlying data, while firmly keeping a ‘human in the loop’ in all phases: by detecting issues early, it can connect vulnerable residents with the appropriate municipal support services. Currently part of the city’s broader strategy against loneliness, it streamlines the identification of at-risk individuals, allowing social workers to focus their efforts directly on residents needing intervention, thus improving quality of life and reducing social isolation. | Local | Spain | 2.024 | Public services and engagement | Service personalisation (various) | No | No | G2C | x | x | x | x | https://www.esade.edu/ecpol/wp-content/uploads/2025/05/AAFF_EsadeEcPolxGoogle_AIbenefits__ENG_vfinal.pdf | Communication | Natural language processing | chatbot | ||||||||||||||||||||||||||
| PSTW-2551 | Margot AI supporting the Agenzia Italiana del Farmaco - document search case | https://www.e-time.it/margot-ai/ | Margot is an AI-powered virtual assistant developed by e-time, built on a Retrieval-Augmented Generation (RAG) architecture, and deployed at the Agenzia Italiana del Farmaco (AIFA) across three use cases: (1) internal document search, enabling staff to retrieve precise information from AIFA's internal database; (2) FarmaciLine citizen assistance, supporting public-facing customer service through automated classification and response to incoming queries; and (3) a monitoring platform for operational oversight. Margot integrates with existing systems and channels to automate repetitive tasks, classify incoming messages, and search corporate documents for accurate answers. | National | Italy | 2.025 | Internal management | Internal support processes | No | No | G2G | x | x | x | x | https://www.e-time.it/e-time-al-forum-pa-2025/ | Learning | Machine learning | Generative AI | Natural language processing | |||||||||||||||||||||||||
| PSTW-2552 | Margot AI supporting the Agenzia Italiana del Farmaco - FarmaciLine assistance | https://www.e-time.it/margot-ai/ | Margot is an AI-powered virtual assistant developed by e-time to streamline customer service and internal support. In this use case, the tool is used within the FarmaciLine service which allows citizens to request information on medicines. The service responds to questions on Authorised Medicinal Products, based on what is reported in the Summary of Product Characteristics and in AIFA Resolutions. Built on a Retrieval-Augmented Generation (RAG) architecture, Margot AI seamlessly integrates with existing systems and channels to automate repetitive tasks, classify incoming messages, and search corporate documents for precise answers. | National | Italy | 2.025 | Public services and engagement | Service personalisation (various) | No | No | G2C | x | x | x | x | https://www.e-time.it/e-time-al-forum-pa-2025/ | Learning | Machine learning | Generative AI | Natural language processing | |||||||||||||||||||||||||
| PSTW-2553 | Margot AI supporting the Agenzia Italiana del Farmaco - Monitoring platform | https://www.e-time.it/margot-ai/ | Margot is an AI-powered virtual assistant developed by e-time to streamline customer service and internal support. This use case supports the Agency in retrieving the correct information from the monitoring registries. The AIFA monitoring registry list includes various types of systems used to track the use of medicines in clinical practice, including standard monitoring registries, therapeutic plans, simplified multi-drug registries, among others. Built on a Retrieval-Augmented Generation (RAG) architecture, Margot AI seamlessly integrates with existing systems and channels to automate repetitive tasks, classify incoming messages, and search corporate documents for precise answers. | National | Italy | 2.025 | Internal management | Internal support processes | No | No | G2G | x | x | x | x | https://www.e-time.it/e-time-al-forum-pa-2025/ | Learning | Machine learning | Generative AI | Natural language processing | |||||||||||||||||||||||||
| PSTW-2554 | AI-powered procurement platform | https://apolitical.co/solution-articles/en/how-albania-is-transforming-government-one-evirtual-assistant-at-a-time | By 2026, in partnership with the EU and World Bank, Albania will launch an AI-powered procurement platform. This platform will automate procurement processes using AI to draft terms of reference, estimate costs, and generate initial evaluation reports, thereby increasing transparency and reducing human errors. While AI will streamline and enhance efficiency, human oversight will remain central, with detailed audit trails for any changes made to generated outputs. This initiative will foster fair competition and ensure equal access for businesses within and beyond Albania. | National | Albania | 2.025 | Internal management | Internal support processes | No | No | G2G | x | x | x | x | x | https://apolitical.co/solution-articles/en/how-albania-is-transforming-government-one-evirtual-assistant-at-a-time | Learning | Machine learning | ||||||||||||||||||||||||||
| PSTW-2555 | AI for taxation project in Albania | https://apolitical.co/solution-articles/en/how-albania-is-transforming-government-one-evirtual-assistant-at-a-time | In the field of taxation, Albania is finalising, with the support of Microsoft, an AI model that will analyse real-time electronic invoices and custom declarations to detect anomalies and combat tax evasion and financial crime. This model will automate routine tasks, allowing staff to focus on more complex cases. | National | Albania | 2.025 | Internal management | Internal support processes | No | No | G2G | x | x | x | https://apolitical.co/solution-articles/en/how-albania-is-transforming-government-one-evirtual-assistant-at-a-time | Learning | Machine learning | ||||||||||||||||||||||||||||
| PSTW-257 | Automatic border control - Facial Recognition at border controls | https://www.kratid.ee/kasutuslood-kratid | At the beginning of 2021, the first automated border control or ABC gates started working at Tallinn Airport and at the Narva road border crossing. Automated border control gates based on biometrics speed up border crossing and provide the border guard with an additional tool to identify a person and verify the right to enter the country. Identification algorithms at ABC gates reduce the chance of someone crossing the border with the wrong document. In addition, initial testing has shown that through the ABC gates, a person can cross the border in an average of 15 seconds. | National | Estonia | EE | Police and Border Guard Board | Central-Government | Public order and safety | Police Services | Implemented | 2.021 | Enforcement | Smart Recognition processes | No | No | Artificial Intelligence | G2G | x | x | x | https://www.kratid.ee/kasutuslood-kratid | Perception | Computer vision | Machine learning | face recognition | 15/11/2023 | ||||||||||||||||||
| PSTW-2572 | Barking and Dagenham AI Search and Webchat - Streamlining access to council services and information through AI-powered search and chat | https://ai.gov.uk/knowledge-hub/use-cases/barking-and-dagenham-ai-search-and-webchat/ | The Barking & Dagenham AI Search and Webchat project uses AI-driven chat and search tools to handle common resident queries, starting with waste collection and expanding to other services like housing and council tax. It automates responses based on postcode data, resolving most questions without staff input. The initiative has reduced call volumes, improved satisfaction, and maintained accessibility by keeping traditional service channels and involving community feedback. The AI Search interface is handling 18,000 sessions per month. The first-time hit rate on search (i.e., finding the right information with the initial query) is high, with low levels of negative feedback. The AI Chatbot interface is currently serving 4,450 conversations per month, with a 93% success rate based on user feedback (thumbs up / down) at the end of each conversation. The combined impact of the tool across both interfaces has been a reduction in general enquiries and calls into the Council. | Local | United Kingdom | 2.022 | Public services and engagement | Service personalisation (various) | No | No | G2C | x | x | x | x | https://ai.gov.uk/knowledge-hub/use-cases/?organisation=&governmentBody=&userGroup=&typeOfTechnology=&impact= | Learning | Machine learning | Generative AI | chatbot | |||||||||||||||||||||||||
| PSTW-2573 | Aila: AI Lesson Assistant for UK teachers | https://ai.gov.uk/knowledge-hub/use-cases/aila-ai-lesson-assistant/ | Aila, developed by Oak National Academy (an arm’s length body of the Department for Education), is an AI-powered lesson assistant designed to help teachers create personalised, curriculum-aligned lesson plans swiftly and efficiently. It combines a large language model with retrieval-augmented generation to draw from Oak’s extensive, high-quality and quality-assured lesson repository, ensuring content accuracy and relevance. Teachers interact with Aila through a chat interface to generate lesson outlines, which can be refined iteratively. In its first two months, Aila supported 10,000 users in creating nearly 25,000 lesson plans, with 85% rating the quality as 'fairly high' or 'very high'. Nearly two-thirds of teachers said Aila reduced workload or freed up time for other priorities. Reported total time savings ranged from 1 to 15 hours, with an average of around 3 hours saved. Some teachers have also noted reduced stress and improved well-being. | National | United Kingdom | 2.024 | Internal management | Internal support processes | No | No | G2G | x | x | https://ai.gov.uk/knowledge-hub/use-cases/?organisation=&governmentBody=&userGroup=&typeOfTechnology=&impact= | Learning | Machine learning | Generative AI | chatbot | |||||||||||||||||||||||||||
| PSTW-2575 | GCS Assist - Accelerating content creation for government communicators | https://ai.gov.uk/knowledge-hub/use-cases/gcs-assist/ | Assist is a secure tool created in-house to support government communicators. It went live in April 2025, following the initial prototype launch in November 2023. The tool features pre-built, task-specific prompts to save users time. It enables communicators to brainstorm ideas, produce first draft communication products and review work in a fraction of the time it would otherwise take manually. Assist's focus on communication disciplines ensures that outputs align with Government Communications' best practice, guidance and frameworks. | National | United Kingdom | 2.025 | Internal management | Internal support processes | No | No | G2G | x | x | x | x | https://ai.gov.uk/knowledge-hub/use-cases/?organisation=&governmentBody=&userGroup=&typeOfTechnology=&impact= | Learning | Machine learning | Generative AI | ||||||||||||||||||||||||||
| PSTW-2576 | Assisting social care workers through transcription and note-taking with Magic Notes | https://ai.gov.uk/knowledge-hub/use-cases/magic-notes-wales/ | Magic Notes is an AI-powered tool developed by Beam to assist social workers in recording and summarising case notes during client meetings. The system transcribes conversations and generates structured summaries, significantly reducing the time spent on administrative tasks. Each practitioner involved in the pilot saved on average, 25 minutes per assessment write-up. This equated to savings of around 7.5 hours per week per practitioner on administrative tasks. Practitioners submitted their assessments up to 8 hours faster when using the technology, with all participants reporting substantial time savings. The product consistently achieved over 97% accuracy in transcripts and summaries, significantly outperforming other products and increasing user confidence. Practitioners reported that conversations were more natural and higher in quality when using the product, resulting in better overall assessments compared to traditional methods. Managers noted progress in reducing case backlogs and improving workload distribution, leading to a positive impact on social worker wellbeing. All participating practitioners endorsed the product and expressed interest in continued use. | Regional | United Kingdom | 2.025 | Internal management | Internal support processes | No | No | G2G | x | x | x | https://ai.gov.uk/knowledge-hub/use-cases/?organisation=&governmentBody=&userGroup=&typeOfTechnology=&impact= | Learning | Machine learning | Generative AI | |||||||||||||||||||||||||||
| PSTW-2579 | SAM: Service AI Assistant Module - Streamlining routine queries through AI-powered contact centre tools | https://ai.gov.uk/knowledge-hub/use-cases/sam-service-ai-assistant-module/ | The Service AI Assistant Module (SAM) is an AI-powered chatbot developed to improve customer service efficiency. It helps handle routine public inquiries—such as waste collection and council tax—by integrating with backend systems and reducing the load on call centers. The assistant supports 24/7 access to council services, improves response times. Early testing showed 93% accuracy in the chatbot's responses and 86-90% user satisfaction, based on thumbs-up/down feedback. | Local | United Kingdom | 2.025 | Public services and engagement | Service personalisation (various) | No | No | G2C | x | x | x | x | https://ai.gov.uk/knowledge-hub/use-cases/?organisation=&governmentBody=&userGroup=&typeOfTechnology=&impact= | Learning | Machine learning | Generative AI | chatbot | |||||||||||||||||||||||||
| PSTW-258 | Chatbot Vesta - Estonian National Library | https://www.kratid.ee/kasutuslood-kratid | Questions and information requests are submitted to the Estonian National Library every day. These questions often have repetitive patterns and repetitive topics that require too much human resources to answer. Every year, the Estonian National Library receives approximately 14 thousand e-mails with questions. As a result of the project, a prototype of an application based on artificial intelligence was completed, which was able to sort incoming questions by topic and answer first-level questions by itself with repeating patterns. | National | Estonia | EE | National Library | Central-Government | General public services | Executive and legislative organs, financial and fiscal affairs, external affairs. | Pilot | 2.019 | Public services and engagement | Service personalisation (various) | No | No | Artificial Intelligence | G2C | x | x | x | https://www.kratid.ee/kasutuslood-kratid | Communication | Natural language processing | Searching | chatbot | 15/11/2023 | ||||||||||||||||||
| PSTW-2582 | Warm Home Discount Energy Cost Predictor - Modelling energy costs to determine eligibility for Warm Home Discount scheme | https://ai.gov.uk/knowledge-hub/use-cases/warm-home-discount-energy-cost-predictor/ | The Warm Home Discount Energy Cost Predictor is an AI-driven tool designed to streamline eligibility assessments for the UK’s Warm Home Discount scheme. It uses a log-linear regression model to estimate household energy costs based on property characteristics—such as type, age, and floor area—helping to identify low-income and high-cost households more efficiently. By leveraging this predictive system, the Department for Energy Security & Net Zero can better target support to vulnerable families in need. In 2023/24, over 90% of the total 3 million rebates were issued automatically. The implementation of this solution has made the process fairer by eliminating the first-come, first-served system. As a result, vulnerable customers who may not have been aware of the support available are now proactively identified and included. | National | United Kingdom | 2.023 | Adjudication | Taking decisions on benefits | No | No | G2G | x | x | x | https://ai.gov.uk/knowledge-hub/use-cases/?organisation=&governmentBody=&userGroup=&typeOfTechnology=&impact= | Planning | Planning and Scheduling | ||||||||||||||||||||||||||||
| PSTW-2599 | ADRYX - Chatbot for real-time flight updates | https://www.avionews.it/resource/47035-aeroporto-di-roma-fiumicino-t1-dello-scalo-romano-con-la-nuova-campagna-di-comunicazione-adr-che-ha-come-protagonista-adryx-la-mascotte-del-leonardo-da-vinci.html | The AdR “AdRyX” chatbot (part of the “Digiport” platform) was launched in June 2024 at Rome Fiumicino Airport by Aeroporti di Roma to enhance airport services. The chatbot provides real-time flight updates via WhatsApp and Facebook Messenger, offers recommendations on shops and restaurants, and delivers instant responses in English and Italian to passengers’ queries—marking a key milestone in improving the digital traveler experience | Local | Italy | 2.024 | Public services and engagement | Service personalisation (various) | No | No | G2C | x | x | x | x | https://www.avionews.it/resource/47035-aeroporto-di-roma-fiumicino-t1-dello-scalo-romano-con-la-nuova-campagna-di-comunicazione-adr-che-ha-come-protagonista-adryx-la-mascotte-del-leonardo-da-vinci.html | Communication | Natural language processing | chatbot | ||||||||||||||||||||||||||
| PSTW-26 | Enhanced Care Management - Prediction model for hospitalisation/assistance | https://www.haigekassa.ee/sites/default/files/uuringud_aruanded/1.7.%20Report%20pf%20ECM%20Pilot%20Evaluation.pdf | In 2015, the Estonian Health Insurance Fund started cooperating with the World Bank to develop and pilot a risk-based management model that would help increase the integration of health services. With risk-based management, GPs can identify patients with multiple chronic diseases on their list for whom additional prevention, counseling and monitoring would be most beneficial to their health and quality of life. If these patients are neglected by the GP teams, this can lead to serious problems, including unnecessary deterioration in health, which not only causes health damage but also unnecessary costs to the healthcare system (avoidable hospitalizations, duplication of examinations, etc.).The created solution finds the best algorithm for predicting which patients with selected diagnoses are likely to be hospitalized. In the solution, the EHIF database of medical bills first finds certain conditions / diagnoses to be included in the algorithm. | National | Estonia | EE | Estonian Health Insurance Fund | Central-Government | Health | Public health services. | Pilot | 2.016 | Analysis, monitoring and regulatory research | Prediction and planning | No | No | Artificial Intelligence | G2G | x | x | x | x | https://e-estonia.com/proactive-services-estonia/ | Learning | Machine learning | Automated reasoning | 06/10/2023 | ||||||||||||||||||
| PSTW-2601 | Faneque Double Tunnel - improving traffic with Automatic Incident Detection (AID) system | https://sprinx.ai/case-studies/faneque-double-tunnel/ | The completion of the second phase of the new La Aldea highway in Gran Canaria marked a monumental milestone in enhancing the island’s infrastructure. This phase involved the construction of the Faneque double tunnel, designed to streamline traffic and significantly reduce travel time for both residents and tourists. Sprinx, in partnership with COMSA and thanks to its Spanish distributor CASMAR, helped addressing these challenges by implementing an advanced Automatic Incident Detection (AID) system based on artificial intelligence. The traffix.ai system, coupled with the dragon platform, is AI-driven traffic analysis system designed to ensure high performance, enhancing both safety and traffic flow. | Regional | Spain | 2.024 | Enforcement | Smart Recognition processes | No | No | G2G | x | x | x | https://sprinx.ai/case-studies/faneque-double-tunnel/ | Perception | Computer vision | Planning and Scheduling | |||||||||||||||||||||||||||
| PSTW-2607 | AI use in the City of Kastav | https://interoperable-europe.ec.europa.eu/collection/public-sector-tech-watch/news/damir-medved-pstw | The City of Kastav, known for supporting education, environmental protection, and cultural events like the Kastav Summer Festival, partnered with EDIH ADRIA TBI to digitise and partially automate its co-financing tender process. A prototype AI model using a large language model (LLM) was developed to handle digital submission of tender documents, auto-fill application forms, and generate evaluation proposals. The AI can extract data, summarise project proposals, score them based on set criteria, and export results to Excel. This system enables faster, more transparent ranking of submissions, helping commission members efficiently review and prioritise proposals. | Local | Croatia | 2.025 | Internal management | Internal support processes | No | No | G2G | x | x | https://interoperable-europe.ec.europa.eu/collection/public-sector-tech-watch/news/damir-medved-pstw | Learning | Machine learning | Generative AI | ||||||||||||||||||||||||||||
| PSTW-261 | Kratt for analyzing customer conversations - Finding the root causes of customer inquiries | https://www.kratid.ee/kasutuslood-kratid | Feelingstream has created an application based on Artificial Intelligence, which is based on the analysis of customer contacts in several different languages, including Estonian and Russian. The Unemployment Insurance Fund and Feelingstream worked together to create a pilot, the aim of which was to find the root causes of customer inquiries and thereby reduce the number of calls. As part of the pilot, the Feelingstream application Unemployment Insurance Fund transcribed calls from April to August 2019 (5 months). The main reason for calling with the chosen type of support was related to the receipt of grants. From a human point of view, it is very clear why issues related to the receipt of money arise and the volume of calls is therefore significantly higher at the beginning of the month. Following the pilot project, work was carried out to improve e-environments and there were other findings that continued to work to improve the customer experience. | National | Estonia | EE | Estonian Unemployment Insurance Fund | Central-Government | Social protection | Unemployment. | Implemented | 2.019 | Internal management | Internal support processes | No | No | Artificial Intelligence | G2G | x | x | x | https://www.kratid.ee/kasutuslood-kratid | Communication | Natural language processing | Machine learning | Audio processing | 15/11/2023 | ||||||||||||||||||
| PSTW-2612 | Robic: Inclusive AI for Special Learning | https://interoperable-europe.ec.europa.eu/collection/public-sector-tech-watch/2025-best-cases-award | This pilot project explores the feasibility and educational impact of an AI-supported social robotics solution in a special education setting. Implemented at Colegio Gaudem in Madrid, the initiative aims to enhance the personal, cognitive, and emotional development of students with special educational needs through personalised, structured interactions using Inrobic Clinic and Inrobic Virtual. Between November 2024 and March 2025, 300 sessions were conducted involving 28 students, mostly in group formats. High satisfaction scores were reported by educators and families, with notable improvements in communication, motor skills, and engagement across subjects like math and language. Students responded positively, treating the robot as a peer and showing increased motivation. Teachers integrated the solution smoothly into their practices, and families expressed strong interest in its continuation. Early findings support the value and effectiveness of AI-assisted robotics in promoting inclusive and adaptive education. | Local | Spain | 2.024 | Public services and engagement | Service personalisation (various) | No | No | G2C | x | x | x | Self-reporting tool | Learning | Machine learning | ||||||||||||||||||||||||||||
| PSTW-2614 | Local.iA: promoting public and responsible AI | https://www.diba.cat/ca/web/local-ia/inici | Local.iA is an ecosystem of resources, materials, and initiatives that provides local authorities—free of charge—with training paths, guides, and communication materials to deploy AI and data governance in an organised manner. In addition, it promotes AI-based proof-of-concept pilots to address local government needs, in collaboration with municipalities. Some of these pilots are already in production, while others are in the analysis phase. All pilots are documented and shared openly. | Local | Spain | 2.025 | Internal management | Internal support processes | No | No | G2C | x | x | x | x | Self-reporting tool | Learning | Machine learning | |||||||||||||||||||||||||||
| PSTW-2615 | Document Review in Service Requests powered by Gen AI | https://interoperable-europe.ec.europa.eu/collection/public-sector-tech-watch/2025-best-cases-award | INPS provides services where users are required to submit various types of documents to support their requests, which must undergo a thorough review to verify their validity. This process involves the manual review of millions of documents annually by operators, all within a constrained timeframe. This involves a wide variety of documents (invoices, contracts, travel tickets, payment receipts, etc), making the process highly time-consuming and error prone. The goal of the project was to streamline and enhance the verification process through AI-powered automation, reducing manual workload, ensuring consistency in checks, and improving response times for citizens. To address these challenges, an innovative solution has been developed, integrating on-premise Generative Artificial Intelligence technologies designed to support operators in document analysis activities. Key features of the solution include: • Automatic classification of documents based on both type and content; • Data extraction and verification, with automated comparison between the information in the documents, the tender requirements, and the associated metadata; • Smart visualization of AI-extracted fields, with automatic highlighting directly within the document for easy reference; • Decision support, offering a detailed summary of the extracted data, flagging any discrepancies, and assisting with manual validation. This solution significantly streamlines the verification process, reducing manual effort and increasing both the speed and consistency of checks, delivering concrete benefits to both staff and citizens. Moreover, the system’s ability to adapt and learn from new data ensures continuous performance improvement, supporting progressively more effective procedure management. The solution aims to deliver benefits for both operators and citizens. Overall, the implementation of Generative AI has proven to be a transformative step in modernizing the document verification process, setting a strong foundation for future innovation and scalability. The next objective is primarily to adopt this solution for the other services within the INPS system. | National | Italy | 2.025 | Internal management | Internal support processes | No | No | G2G | x | x | x | x | Self-reporting tool | Learning | Machine learning | Generative AI | ||||||||||||||||||||||||||
| PSTW-2616 | Text Simplification for Citizens with GenAI | https://oecd-opsi.org/innovations/text-simplification-for-citizens-with-genai/ | Clear and accessible communication is essential to ensure that citizens can effectively navigate public services. INPS—Italy’s National Institute of Social Security and the largest welfare institution in Europe—serves approximately 45 million citizens through nearly 500 digital services related to pensions and welfare. The clarity of these service descriptions plays a critical role in guaranteeing equitable access and a positive user experience. To address the challenges of bureaucratic language, INPS has launched a structured simplification program aimed at making content understandable to users with a middle school level of education. Over 700 texts have been manually simplified so far, resulting in an increase in the average Gulpease readability score from 57 to 64—a substantial improvement in accessibility. However, this manual process is labor-intensive, requiring specialised linguistic and legal expertise, and is not easily scalable. The need for plain language in public administration has long been acknowledged in Italy. A 2002 directive still in force emphasizes that “all texts produced by administrations must be designed and written to be understood by those who receive them.” Yet institutional communication remains overly formal and complex, hindering citizens’ ability to fully access and understand critical services. While simplification improves transparency and public trust, it must also preserve the legal precision required for official documentation. To overcome these limitations, INPS has integrated Large Language Models (LLMs) into its simplification workflow, developing a semi-automated system—operating in a human-in-the-loop model—that is both scalable and efficient. This solution can process high volumes of content while ensuring readability, semantic accuracy, and legal compliance. A dedicated evaluation framework was introduced to measure key aspects of the output, including readability, fluency, and content preservation. User testing further validated the approach, confirming the quality of AI-generated content in comparison to both the original and manually simplified texts. The AI-based system delivers expert-level results in a fraction of the time and cost required by manual processes. It enhances INPS’s operational efficiency, standardizes quality across service pages, and ensures that content remains accessible and legally sound. Human oversight guarantees accuracy and relevance, while integrated metrics provide transparency and guide ongoing optimization. A large-scale user study involving A/B testing with 1,620 participants confirmed the model’s effectiveness. AI-generated texts were preferred in over 70% of cases when compared to the original versions and outperformed them across all measured dimensions: fluency (+14.1%), readability (+13.5%), clarity (+11.1%), and engagement (+12.3%). The AI semplified versions outperformed also the corresponding human simplified texts across all the qualitative metrics. Citizens are the ultimate beneficiaries of this transformation. By simplifying complex institutional language, INPS reduces barriers to access for individuals with limited language skills, lower educational attainment, or reading difficulties. More inclusive communication strengthens transparency, encourages greater civic engagement, and builds trust between citizens and institutions. Beyond INPS, this AI-driven approach has strong potential for adoption in other sectors where complex language limits accessibility—such as healthcare, legal services, taxation, and social welfare. Its ability to adapt to diverse regulatory and linguistic contexts makes it a powerful tool for modernising public communication across government systems. In summary, the integration of LLMs into INPS’s content simplification strategy demonstrates how generative AI can enhance accessibility, efficiency, and trust in public services—delivering clear, comprehensible, and citizen-centered communication at scale. | National | Italy | 2.025 | Internal management | Internal support processes | No | No | G2C | x | x | x | x | Self-reporting tool | Learning | Machine learning | Generative AI | ||||||||||||||||||||||||||
| PSTW-2622 | KIRA - AI research assistant | https://digital.hamburg.de/digitale-stadt/innotechh-644652 | As part of Hamburg’s digital strategy, the KIRA Research Assistant addresses the challenge of managing vast amounts of legal and social services legislation. This AI-driven knowledge tool (chatbot) retrieves relevant documentation and provides accurate answers, reducing research time, supporting consistent service quality, and easing pressure on public administration staff. Developed with support from the InnoTecHH Fonds, KIRA has demonstrated strong performance, with an 87% top-k accuracy rate, excellent usability (SUS score 9.75/10), and high satisfaction among staff. Pilot results confirm significant efficiency gains, enabling faster, reliable processing of social benefits requests and directly improving service delivery for both Hamburg’s administration and its citizens. | Regional | Germany | 2.025 | Public services and engagement | Service personalisation (various) | No | No | G2C | x | x | x | x | Self-reporting tool | Learning | Machine learning | Generative AI | chatbot | |||||||||||||||||||||||||
| PSTW-2625 | Vienna AI with generative search (de: WienKI mit generative Suche) | https://digitales.wien.gv.at/wien-im-finale-des-red-hat-innovation-awards-jetzt-abstimmen/ | The City of Vienna has proactively embraced artificial intelligence to modernise public administration and deliver tangible benefits to citizens and employees. Recognising the disruptive potential of generative AI, Vienna developed WienKI, a holistic AI platform designed to improve efficiency, safeguard data sovereignty, and foster responsible innovation. WienKI brings together secure, user-friendly tools such as multilingual assistants, knowledge databases with anonymisation functions, and image generation, supported by a strong governance framework and continuous staff training. More than 2,500 employees are already actively using the system, with over 100,000 chat interactions, 85,000 image generations, and 14,000 curated knowledge documents to date. Built on a modular, open-source architecture, WienKI ensures compliance with GDPR, the EU AI Act, and strict security standards, whilst remaining transparent, scalable, and reusable by other public institutions. It enhances internal efficiency, strengthens accessibility across 103 languages, and encourages a culture of responsible innovation throughout the administration. WienKI demonstrates how public administration can act as a pioneer in times of technological change—balancing innovation and responsibility to create sustainable value for both employees and citizens. | Local | Austria | 2.025 | Public services and engagement | Service personalisation (various) | No | No | G2C | x | x | x | x | Self-reporting tool | Learning | Machine learning | Generative AI | ||||||||||||||||||||||||||
| PSTW-263 | Effective tax collection - Identifying companies or person in need for inspection | https://www.kratid.ee/kasutuslood-kratid | The Tax and Customs Board (MTA) has begun to analyze whether Artificial Intelligence could be used for more efficient tax collection. In particular, the system could identify which companies are most likely to be envelope payers. The aim would be to establish a model that would make it easier to determine the probability of paying an envelope salary through information provided on tax returns (such as turnover) and help to better find suitable objects, ie companies to be inspected. | National | Estonia | EE | Tax and Customs Board | Central-Government | General public services | Executive and legislative organs, financial and fiscal affairs, external affairs. | Implemented | 2.019 | Enforcement | Supporting inspection processes | No | No | Artificial Intelligence | G2G | x | x | x | https://www.kratid.ee/kasutuslood-kratid | Planning | Planning and Scheduling | Automated reasoning | 16/11/2023 | |||||||||||||||||||
| PSTW-2631 | ChatAmsterdam - an internally developed generative AI chatbot tailored to the municipality's needs and values to support civil servants in their daily activities | https://www.amsterdamai.com/en/nieuws/amsterdam-launches-chatamsterdam-its-own-ai-assistant-for-civil-servants | ChatAmsterdam is an internally developed generative AI assistant designed to support civil servants in the Municipality of Amsterdam. Developed through a six-month research pilot involving over 800 employees, the application provides practical assistance with daily tasks while promoting AI literacy, ensuring digital security, and safeguarding sensitive municipal data. ChatAmsterdam operates within a secure, vendor-neutral environment, prioritising data ownership, privacy, transparency, and compliance with Dutch and European regulations. The platform enables integration with internal data sources, allowing staff to pose domain-specific questions and receive contextually relevant answers. By providing a safe alternative to commercial generative AI tools, ChatAmsterdam reduces shadow use of external platforms and facilitates responsible AI adoption. Its flexible architecture allows future expansion, including additional functionalities, AI-assisted workflows, and integration of new datasets, while ensuring alignment with organisational values and operational goals. The application reflects a user-centred design approach, incorporating continuous feedback, training, and co-creation with staff to maximise usability, trust, and impact. | Local | Netherlands | 2.025 | Public services and engagement | Service personalisation (various) | No | No | G2C | x | x | x | x | Self-reporting tool | Learning | Machine learning | Generative AI | chatbot | |||||||||||||||||||||||||
| PSTW-2632 | AI tool for depersonalising sensitive data at the State Consumer Rights Protection Authority (SCRPA) | https://interoperable-europe.ec.europa.eu/collection/public-sector-tech-watch/2025-best-cases-award | The personal data depersonalisation AI tool is an internally developed solution designed to enhance data privacy, security, and regulatory compliance. By automatically identifying, masking, encrypting, or removing Personally Identifiable Information (PII), the tool ensures that datasets used for development, testing, and analysis are fully anonymised, embedding a “privacy by design” culture across the organisation. This automation has reduced manual depersonalisation time from several hours to under 15 minutes, achieving a 95% efficiency gain, while maintaining 99.8% accuracy in PII detection. The solution is fully interoperable with existing internal systems, integrates seamlessly into data pipelines, and complies with GDPR, CCPA, and organisational policies. Its advanced Natural Language Processing (NLP) and Machine Learning (ML) capabilities allow context-aware recognition of PII in structured and unstructured data, outperforming traditional rule-based methods. The tool has delivered measurable impact, including an 85% reduction in data breaches involving unauthorised PII exposure, significant labour cost savings, and increased user confidence. By providing a reliable, scalable, and user-friendly solution, the AI tool strengthens operational efficiency, data integrity, and transparency, allowing secure data sharing with internal teams and external partners without compromising privacy. | Regional | Lithuania | 2.025 | Internal management | Internal support processes | No | No | G2C | x | x | x | x | Self-reporting tool | Learning | Machine learning | Natural language processing | ||||||||||||||||||||||||||
| PSTW-2633 | Virtual Market Assistant for the State Consumer Rights Protection Authority (SCRPA) | https://play.google.com/store/apps/details?id=com.vvtat.vvtat | The Virtual Market Assistant is an innovative mobile application designed to enhance consumer safety by providing instant access to information on officially listed hazardous products and enabling users to report new risks. By connecting to verified databases such as the EU Safety Gate (RAPEX) and integrating user-submitted reports, the app offers proactive protection and empowers citizens to participate directly in market surveillance. It allows barcode scanning for instant product safety checks and simplifies the submission of detailed hazard reports, including photos and descriptions, which are standardised for seamless use by regulatory authorities. Technologically, the app leverages familiar mobile, cloud, and database infrastructure, providing a scalable and user-friendly solution without requiring specialised equipment. It is designed with full interoperability in mind, adhering to the European Interoperability Framework at legal, organisational, semantic, and technical levels, ensuring seamless integration with national and transnational market surveillance systems. By increasing transparency, accountability, and public engagement, the Virtual Market Assistant strengthens trust between citizens and regulatory authorities, streamlines hazard reporting, and accelerates the removal of unsafe products from the market. | Regional | Lithuania | 2.025 | Public services and engagement | Data Sharing Management | No | No | G2C | x | x | x | x | Self-reporting tool | Learning | Machine learning | |||||||||||||||||||||||||||
| PSTW-2635 | AI agent for Prague 6: Simplifying communication between the office and citizens | https://www.citymind.tech/en/case-studies/prague6-oict | The Citymind chatbot was implemented by Prague 6 to improve citizen-office communication and streamline access to public services. Its primary function is to provide citizens with a quick, intuitive interface to find information—covering topics such as passport issuance, ID cards, and local police services—while freeing officials from answering routine inquiries. The project, funded under the Horizon Europe CommuniCity programme, combines co-creation with citizens and municipal staff to ensure a user-centred design, resulting in a high user satisfaction rating of 4.05 out of 5. Technologically, the solution is scalable, secure, and user-friendly, integrating seamlessly into municipal websites with minimal technical effort. Its structured data processing ensures semantic interoperability, translating complex administrative content into plain, human-like language. The chatbot also generates analytical reports on common queries, supporting internal service improvements and enhancing organisational efficiency. The innovation process involved participatory development, iterative testing, and a replicability guide to support adoption by other municipalities. Citymind is commercially managed, ensuring ongoing support and continuous development, while being aligned with European interoperability and accessibility principles. | Local | Czechia | 2.025 | Public services and engagement | Service personalisation (various) | No | No | G2C | x | x | x | x | Self-reporting tool | Learning | Machine learning | chatbot | ||||||||||||||||||||||||||
| PSTW-2636 | AI Literacy in Action: An Interactive and Reusable Prompting Workbook for Public Servants | https://g.co/gemini/share/08cbc5c9071f | The AI Prompting Workbook was developed to rapidly build AI literacy among public administration employees, addressing the limitations of passive training formats and fulfilling capacity-building requirements under the EU AI Act. The interactive, self-paced workbook allows users to engage directly with an internal AI model (“LinzGPT”), experimenting with prompts, executing them in real time, and receiving instant feedback across 50 practical exercises. Internal metrics—voluntary enrolment, course completion, and certificate issuance—demonstrate high uptake and effectiveness, while qualitative feedback from the “AI Pioneers” focus group confirms its practical relevance and engaging format. Technologically, the solution leverages a lightweight web application and structured content (JSON-based exercises), enabling semantic, organisational, technical, and legal interoperability. It is designed for easy scaling and reuse, both internally and as a public Google Gemini Canvas, allowing other administrations to customise or expand the workbook without programming knowledge. The implementation followed a user-centric, agile process, combining in-house prototyping, co-creation with internal focus groups, and rigorous IT validation, with no external procurement required. The dual-delivery model ensures secure internal deployment while maximising public value and societal impact, supporting AI capacity-building and fostering a broader culture of digital empowerment across Europe. | Local | Austria | 2.025 | Public services and engagement | Data Sharing Management | No | No | G2C | x | x | x | x | Self-reporting tool | Learning | Machine learning | |||||||||||||||||||||||||||
| PSTW-2642 | Impulsa Autónomo: Intelligent Platform to Personalise Grants and Subsidies for the Self-Employed in Galicia through AI | https://oficinadoautonomo.gal/es | The Xunta de Galicia developed an intelligent portal and widget to simplify access to grants and subsidies for self-employed professionals. By consolidating dispersed information into a single platform, the project reduces complexity and fragmentation in accessing funding opportunities. Using Retrieval-Augmented Generation (RAG)–based Generative AI, the system integrates official databases to provide personalised recommendations, outperforming static catalogues. It was designed for rapid deployment with iterative testing and direct user pilots, ensuring relevance and usability. Early results show search time reductions of more than 60% and over 100 hours of integrated specialised advisory services. BI dashboards track consultations, usage, and real-time satisfaction, while automated responses deliver cost savings for the administration. Transparency is reinforced through personalised publication of subsidies, automatic alerts, and two-way feedback channels that enhance citizen participation. Fully aligned with European interoperability principles and Spanish regulations, the platform strengthens government-to-citizen interaction, increases public participation, and provides a replicable model for digital public services. | Regional | Spain | 2.025 | Internal management | Internal management processes | No | No | G2B | x | x | x | x | Self-reporting tool | Learning | Machine learning | |||||||||||||||||||||||||||
| PSTW-266 | Sewage - Improving Sewage Pipe Network predicting sewer blockages | https://faia.fi/market-research/ | The AI solution predicts possible blockages in Helsinki Region Environmental Services Authority HSY’s sewage network, spanning over 3000 kilometers. With the intelligent solution, HSY is able to prevent one third of blockages on an annual basis as sewer cleaning can be targeted on blockage-prone drain ranges suggested by the AI solution. The solution is used in Helsinki Region Environmental Services Authority. The experience showed that the AI is able to predict blockages efficiently, and up to a third of the blockages could be avoided. | Regional | Finland | FI1B | Helsinki Region Environmental Services Authority HSY | Local Government | Housing and community amenities | Housing and community amenities n.e.c. | Implemented | 2.020 | Analysis, monitoring and regulatory research | Prediction and planning | No | No | Artificial Intelligence | G2B | x | x | x | https://faia.fi/market-research/ | Planning | Planning and Scheduling | Optimisation | 16/11/2023 | |||||||||||||||||||
| PSTW-267 | Optimize the processing of reports of adverse health events | https://www.etalab.gouv.fr/intelligence-artificielle-decouvrez-les-15-nouveaux-projets-selectionnes/ | Using the data from all the reports of adverse health events, the AI will make it possible to classify the reports, extract the relevant business concepts and detect anomalies in the reports. | National | France | FR | General Directorate of Health | Central-Government | Health | Health n.e.c. | Pilot | 2.019 | Analysis, monitoring and regulatory research | Information analysis processes | No | No | Artificial Intelligence | G2G | x | x | https://www.etalab.gouv.fr/intelligence-artificielle-decouvrez-les-15-nouveaux-projets-selectionnes | Learning | Machine learning | Natural language processing | 16/11/2023 | ||||||||||||||||||||
| PSTW-268 | Facilitate access to patient information - Semantic search in patient records | https://www.etalab.gouv.fr/intelligence-artificielle-decouvrez-les-15-nouveaux-projets-selectionnes/ | The AI will allow a semantic search in the computerized patient record to allow the healthcare staff to find and visualize the information on the patient. The prototype will facilitate the work of nursing staff and reduce the loss of time associated with finding information on the patient. | Local | France | FRI1 | Bordeaux University Hospital Center | Local Government | Health | Hospital services. | Pilot | 2.021 | Internal management | Internal primary processes | No | No | Artificial Intelligence | G2G | x | x | https://www.etalab.gouv.fr/intelligence-artificielle-decouvrez-les-15-nouveaux-projets-selectionnes | Reasoning | Knowledge representation | Searching | 16/11/2023 | ||||||||||||||||||||
| PSTW-269 | Ionizing radiation exposure monitoring information system (SISERI) | https://docs.siseri.irsn.fr/about-siseri | Using data from the ionizing radiation exposure monitoring information system (SISERI), AI will allow personalized monitoring of workers' exposure to ionizing radiation and easier detection of anomalies. | National | France | FR | Institute for Radiation Protection and Nuclear Safety | Central-Government | Health | R&D health. | Pilot | 2.019 | Analysis, monitoring and regulatory research | Information analysis processes | No | No | Artificial Intelligence | G2G | x | x | https://www.etalab.gouv.fr/intelligence-artificielle-decouvrez-les-15-nouveaux-projets-selectionnes | Planning | Planning and Scheduling | Optimisation | anomaly detection | 16/11/2023 | |||||||||||||||||||
| PSTW-270 | Acts - Develop Artificial Intelligence in dematerialized legality control | https://www.etalab.gouv.fr/intelligence-artificielle-decouvrez-les-15-nouveaux-projets-selectionnes/ | Using data from the @ctes (Acts) application, the AI will simplify the work of agents in the prefecture, by automatically sorting transmissible and non-transmissible acts and by detecting the information to be checked as a priority. | National | France | FR | General Directorate of Local Authorities | Central-Government | General public services | Executive and legislative organs, financial and fiscal affairs, external affairs. | Pilot | 2.019 | Internal management | Internal support processes | No | No | Artificial Intelligence | G2G | x | x | x | x | https://www.etalab.gouv.fr/intelligence-artificielle-decouvrez-les-15-nouveaux-projets-selectionnes | Planning | Planning and Scheduling | Automated reasoning | 16/11/2023 | ||||||||||||||||||
| PSTW-272 | Identify false customs declarations using text mining | https://www.etalab.gouv.fr/intelligence-artificielle-decouvrez-les-15-nouveaux-projets-selectionnes | From product descriptions in single administrative documents, AI will help detect imported products that are wrongly declared in a tax-advantaged product nomenclature and improve the fight against customs duty fraud. | National | France | FR | General Directorate of Customs and Indirect Duties | Central-Government | General public services | Executive and legislative organs, financial and fiscal affairs, external affairs. | Pilot | 2.019 | Enforcement | Supporting inspection processes | No | No | Artificial Intelligence | G2B | x | x | https://www.etalab.gouv.fr/intelligence-artificielle-decouvrez-les-15-nouveaux-projets-selectionnes | Planning | Planning and Scheduling | Automated reasoning | 16/11/2023 | ||||||||||||||||||||
| PSTW-273 | Improve the identification of the employing establishment in the population census | https://www.etalab.gouv.fr/intelligence-artificielle-decouvrez-les-15-nouveaux-projets-selectionnes | Based on the declaration of the employing establishment in the population census data and the SIRENE database of companies and their establishments, the AI will make it possible to develop a recommendation engine for the agents who correct the census data. The project will allow greater precision in home-work statistics provided by INSEE and a gain in efficiency in the data production chain. | National | France | FR | National Institute of Statistics and Economic Studies | Central-Government | General public services | Executive and legislative organs, financial and fiscal affairs, external affairs. | Pilot | 2.019 | Internal management | Internal support processes | No | No | Artificial Intelligence | G2G | x | x | https://www.etalab.gouv.fr/intelligence-artificielle-decouvrez-les-15-nouveaux-projets-selectionnes | Communication | Natural language processing | Searching | text analysis | 16/11/2023 | |||||||||||||||||||
| PSTW-274 | Develop a tool to help the establishment of craft businesses | https://www.etalab.gouv.fr/intelligence-artificielle-decouvrez-les-15-nouveaux-projets-selectionnes | Using data on craft businesses and data on the population, AI will make it possible to determine the chances of success of a craftsman in a territory and to better advise craftsmen in their choice of location. | Regional | France | FRI | New Aquitaine Chambers of Trades and Crafts | Regional Government | Economic Affairs | General economic, commercial and labour affair | Pilot | 2.019 | Analysis, monitoring and regulatory research | Information analysis processes | No | No | Artificial Intelligence | G2B | x | x | x | https://www.etalab.gouv.fr/intelligence-artificielle-decouvrez-les-15-nouveaux-projets-selectionnes | Planning | Planning and Scheduling | Optimisation | recommender system | 16/11/2023 | ||||||||||||||||||
| PSTW-277 | Group disputes together with AI for a joint decision | https://www.etalab.gouv.fr/intelligence-artificielle-decouvrez-les-15-nouveaux-projets-selectionnes/ | From all requests to administrative courts, AI will make it possible to group together disputes to automatically detect series and improve the efficiency of administrative justice. | National | France | FR | Council of State | Central-Government | Public order and safety | Law courts | Pilot | 2.019 | Analysis, monitoring and regulatory research | Information analysis processes | No | No | Artificial Intelligence | G2G | x | x | x | https://www.etalab.gouv.fr/intelligence-artificielle-decouvrez-les-15-nouveaux-projets-selectionnes | Planning | Searching | Knowledge representation | 16/11/2023 | |||||||||||||||||||
| PSTW-278 | AI for Detect mandatory information and unfair terms in contracts, quotes and invoices | https://www.etalab.gouv.fr/intelligence-artificielle-decouvrez-les-15-nouveaux-projets-selectionnes/ | From the reports and documents recovered by DGCCRF investigators during controls and the decisions, opinions and recommendations of the Unfair Terms Commission, AI will make it possible to detect the presence and content of mandatory information, to identify the themes of contract clauses and, where applicable, to identify unfair clauses in order to ensure better consumer protection and better competitive regulation of markets. | National | France | FR | Directorate-General for Competition, Consumer Affairs and Fraud Control | Central-Government | Economic Affairs | General economic, commercial and labour affair | Pilot | 2.019 | Analysis, monitoring and regulatory research | Information analysis processes | No | No | Artificial Intelligence | G2G | x | x | https://www.etalab.gouv.fr/intelligence-artificielle-decouvrez-les-15-nouveaux-projets-selectionnes | Communication | Natural language processing | Automated reasoning | text analysis | 16/11/2023 | |||||||||||||||||||
| PSTW-28 | ITI - Chatbot for Statistics Estonia | https://www.stat.ee/en | The virtual assistant called ITI, created in collaboration with the Estonian start-up AlphaBlues, knows the population of Estonia, the size of the pay gap, average wages and consumer price changes, and many other things. Iti also assists the data provider, whose typical questions are related to activities in the electronic data submission portal and filling in questionnaires. If Iti does not know the answer, it will redirect the query based on its content to either the customer support specialist of the data provider or the user of the statistics. Iti has obtained its knowledge from the questions sent through online chats over one year and gets wiser with every query. ITI helps to find information faster thus allowing the customer support of Statistics Estonia to focus on answering more complicated and detailed queries. | National | Estonia | EE | Estonian Statistical Office | Central-Government | General public services | General services. | Implemented | 2.020 | Public services and engagement | Service integration (various) | No | No | Artificial Intelligence | G2C | x | x | x | x | https://www.stat.ee/en/uudised/news-release-2019-042 | Communication | Natural language processing | Machine learning | chatbot | 06/10/2023 | |||||||||||||||||
| PSTW-280 | Identify divergences in case law - Detection of divergent interpretations of the law | https://www.etalab.gouv.fr/intelligence-artificielle-decouvrez-les-15-nouveaux-projets-selectionnes/ | Based on case law data from the Court of Cassation (Jurinet) and Courts of Appeal (JuriCA), AI will make it possible to reconcile decisions dealing with the same theme and to detect divergent interpretations of the law in order to guarantee an appropriate interpretation. | National | France | FR | Court of Cassation | Central-Government | Public order and safety | Law courts | Pilot | 2.019 | Enforcement | Supporting inspection processes | No | No | Artificial Intelligence | G2G | x | x | https://www.etalab.gouv.fr/intelligence-artificielle-decouvrez-les-15-nouveaux-projets-selectionnes | Reasoning | Knowledge representation | Natural language processing | 16/11/2023 | ||||||||||||||||||||
| PSTW-281 | Automating coastline correction work - Improve coastal mapping | https://www.etalab.gouv.fr/intelligence-artificielle-decouvrez-les-15-nouveaux-projets-selectionnes | Based on laser remote sensing (lidar) measurements taken on the coastline, AI will make it possible to improve the production of the coastline repository by automating the agents' correction work. | National | France | FR | Hydrographic and Oceanographic Service of the Navy | Central-Government | General public services | Executive and legislative organs, financial and fiscal affairs, external affairs. | Pilot | 2.019 | Analysis, monitoring and regulatory research | Information analysis processes | No | No | Artificial Intelligence | G2G | x | x | x | https://www.etalab.gouv.fr/intelligence-artificielle-decouvrez-les-15-nouveaux-projets-selectionnes | Perception | Computer vision | Planning and Scheduling | sensor network | 16/11/2023 | ||||||||||||||||||
| PSTW-282 | Safe Spotter - AI platform to detect and transmit data of an accident | https://www.faticoni.it/safespotter-ai-e-smart-city-per-il-comune-di-monserrato/ | Safespotter is an R&D project born for the Municipality of Monserrato whose general objective is to reduce the number of deaths and injuries in case of road accidents. The idea was born as part of the creation of an innovative and sustainable Smart City model towards which the Municipality of Monserrato aims. The strategic objective is to start a process of protecting citizens and the territory, strengthening the ability to govern road safety. Artificial Intelligence platform able to detect and transmit the data of an accident through an advanced system of cameras and sound sensors able to hear the noise produced by a traffic accident. These sensors, mounted on intelligent street lights, will activate a directional camera to detect Minimun Safe Data (MSD), or a minimum set of key data on the accident, such as images / videos, time, place, driving direction and the vehicle registration number. | Local | Italy | IT | Municipality of Monserrato | Local Government | Public order and safety | Police Services | Implemented | 2.020 | Enforcement | Smart Recognition processes | No | No | Artificial Intelligence | G2G | x | x | x | https://www.faticoni.it/safespotter-ai-e-smart-city-per-il-comune-di-monserrato/ | Perception | Computer vision | Automated reasoning | 16/11/2023 | |||||||||||||||||||
| PSTW-284 | Better guide environmental police checks | https://www.etalab.gouv.fr/intelligence-artificielle-decouvrez-les-6-projets-laureats-de-lappel-a-manifestation-dinteret-ia | French Biodiversity Agency (AFB): better guide environmental police controls thanks to AI; | National | France | FR | French Biodiversity Agency (AFB): | Central-Government | Environmental Protection | Protection of biodiversity and landscape. | Pilot | 2.019 | Analysis, monitoring and regulatory research | Monitoring policy implementation | No | No | Artificial Intelligence | G2G | x | x | x | https://www.etalab.gouv.fr/intelligence-artificielle-decouvrez-les-6-projets-laureats-de-lappel-a-manifestation-dinteret-ia | Planning | Planning and Scheduling | Optimisation | 16/11/2023 | |||||||||||||||||||
| PSTW-285 | ASN: better use of the data contained in follow-up letter of inspections | https://www.ensreg.eu/sites/default/files/attachments/update_of_the_action_plan_of_the_french_nuclear_safety_authority.pdf | ASN, in charge of the regulation of the French nuclear installations, requested operators on 5 May 2011 to undertake complementary safety assessments (CSA) of their installations following the accident that occurred in Japan on 11 March 2011. The objective of the solution was to Automatically detect, thanks to inspection follow-up letters, weak signals and statistical trends to support inspectors in their work. The challenges were to analyze the information contained in the 20,000 follow-up letters inspection and extract structured data and to develop a “ready-to-use” tool to help inspectors in their work | National | France | FR | Nuclear Safety Authority (ASN) | Central-Government | Defence | Military defence. | Implemented | 2.017 | Enforcement | Supporting inspection processes | No | No | Artificial Intelligence | G2G | x | x | x | x | x | x | https://www.etalab.gouv.fr/intelligence-artificielle-decouvrez-les-6-projets-laureats-de-lappel-a-manifestation-dinteret-ia | Communication | Natural language processing | Automated reasoning | text analysis | 16/11/2023 | |||||||||||||||
| PSTW-286 | Automatically detecting irregularities in occupancy soils | https://www.etalab.gouv.fr/intelligence-artificielle-decouvrez-les-6-projets-laureats-de-lappel-a-manifestation-dinteret-ia | Automatically detecting irregularities in occupancy soils (illegal constructions, illegal dumping, etc.) from aerial and satellite images | National | France | FR | Departmental Directorate of Territories and the Sea (DDTM) of L'Hérault: | Central-Government | Housing and community amenities | Housing and community amenities n.e.c. | Pilot | 2.019 | Enforcement | Predictive enforcement processes | No | No | Artificial Intelligence | G2G | x | x | x | https://www.etalab.gouv.fr/intelligence-artificielle-decouvrez-les-6-projets-laureats-de-lappel-a-manifestation-dinteret-ia | Perception | Computer vision | Planning and Scheduling | 16/11/2023 | |||||||||||||||||||
| PSTW-287 | Targeting establishment inspection - refine targeting of establishments for inspections | https://www.etalab.gouv.fr/intelligence-artificielle-decouvrez-les-6-projets-laureats-de-lappel-a-manifestation-dinteret-ia | refine the targeting of establishments to be inspected in the direct delivery sector to consumers (restaurants, catering trades, distributors) through consumer reviews on online review sites. | National | France | FR | General Directorate of Food (DGAL) of the Ministry of Agriculture and Food: | Central-Government | Economic Affairs | Other industries | Implemented | 2.017 | Enforcement | Supporting inspection processes | No | No | Artificial Intelligence | G2G | x | x | x | https://www.etalab.gouv.fr/intelligence-artificielle-decouvrez-les-6-projets-laureats-de-lappel-a-manifestation-dinteret-ia | Planning | Planning and Scheduling | Natural language processing | 16/11/2023 | |||||||||||||||||||
| PSTW-288 | Intelligence Emploi | https://www.modernisation.gouv.fr/actualites/investir-pour-transformer-decouvrez-les-17-laureats-du-premier-appel-projets-du-ftap | Install Artificial Intelligence within Pôle emploi as a lever to accelerate the return to sustainable employment. | National | France | FR | Ministry of Labor | Central-Government | Social protection | Unemployment. | Implemented | 2.018 | Public services and engagement | Service personalisation (various) | No | No | Artificial Intelligence | G2B | x | x | x | https://www.modernisation.gouv.fr/action-publique-2022/fonds-pour-la-transformation-de-laction-publique/investir-pour-transformer-decouvrez-les-17-laureats-du-premier-appel-a-projets-du-ftap | Planning | Planning and Scheduling | Searching | 16/11/2023 | |||||||||||||||||||
| PSTW-289 | AI for targeting fraud and valuing requests (CFVR) to improve the efficiency of tax audits | https://www.modernisation.gouv.fr/actualites/investir-pour-transformer-decouvrez-les-17-laureats-du-premier-appel-projets-du-ftap | Concretely, the use of the innumerable data gathered by the administrations, milled by algorithm, would make it possible to target the controls on the people and the companies most likely to be in default - involuntary or fraudulent. For example in the event of a sudden change in income, or inconsistency in the situations declared to the various administrations ... | National | France | FR | Ministry of Action and Public Accounts - DGFIP | Central-Government | General public services | Executive and legislative organs, financial and fiscal affairs, external affairs. | Pilot | 2.018 | Enforcement | Predictive enforcement processes | No | No | Artificial Intelligence | G2B | x | x | https://www.modernisation.gouv.fr/action-publique-2022/fonds-pour-la-transformation-de-laction-publique/investir-pour-transformer-decouvrez-les-17-laureats-du-premier-appel-a-projets-du-ftap | Planning | Planning and Scheduling | Automated reasoning | 16/11/2023 | ||||||||||||||||||||
| PSTW-29 | OTT - Predicting employment pathways | https://nortal.com/blog/ott-an-ai-powered-success-story-in-the-public-sector/ | The Estonian Unemployment Insurance Fund uses profiling to identify the position that suits a job seeker the most. Based on machine-learning software, the solution assists people by suggesting job positions according to their qualifications. The application (OTT) provides job seekers with better and more accurate suggestions on where they could work and offers customized recommendations on re-education and reskilling. OTT is a tool used by civil servants to improve the understanding of the clients’ needs. It is an AI system that employs more than 100 000 client records to estimate the probabilities of different employment pathways, systematizes clients to provide support where it is most needed, and distributes the workload between civil servants. Now, the system finds the probability of finding a new job and is regarded as much more useful. The AI has been created in collaboration with Citis, Nortal and Resta. | National | Estonia | EE | Estonian Unemployment Insurance Fund | Central-Government | Social protection | Unemployment. | Implemented | 2.020 | Public services and engagement | Service personalisation (various) | No | No | Artificial Intelligence | G2C | x | x | x | https://techmonitor.ai/ai/how-estonia-using-ai-tackle-unemployment | Reasoning | Automated reasoning | Machine learning | 06/10/2023 | |||||||||||||||||||
| PSTW-290 | Datascience | https://www.modernisation.gouv.fr/actualites/investir-pour-transformer-decouvrez-les-17-laureats-du-premier-appel-projets-du-ftap | Enlargement of the activity of the scientific laboratory (datalab) created in 2016 by the Ministry of the Interior in order to systematize the approaches of strategic analysis by data, and promote the emergence of Artificial Intelligence for the benefit of the all the missions of the Ministry of the Interior. | National | France | FR | Ministry of the Interior | Central-Government | General public services | R&D general public services. | Pilot | 2.018 | Public services and engagement | Data Sharing Management | No | No | Artificial Intelligence | G2C | x | x | x | x | https://www.modernisation.gouv.fr/action-publique-2022/fonds-pour-la-transformation-de-laction-publique/investir-pour-transformer-decouvrez-les-17-laureats-du-premier-appel-a-projets-du-ftap | Planning | Automated reasoning | Knowledge representation | 16/11/2023 | ||||||||||||||||||
| PSTW-291 | Health data hub - Creation of a big data infrastructure in health | https://www.modernisation.gouv.fr/actualites/investir-pour-transformer-decouvrez-les-17-laureats-du-premier-appel-projets-du-ftap | create a “big data” data infrastructure in health as well as bring together tools and skills to significantly improve the efficiency of our health system. The advantages of the project: the development of data-driven analysis for clinical research, decision support in terms of resource allocation and the development of predictive and efficient medicine | National | France | FR | Ministry of Solidarity and Health - DREES | Central-Government | Health | Health n.e.c. | Pilot | 2.018 | Public services and engagement | Data Sharing Management | No | No | Artificial Intelligence | G2G | x | x | x | x | x | https://www.modernisation.gouv.fr/action-publique-2022/fonds-pour-la-transformation-de-laction-publique/investir-pour-transformer-decouvrez-les-17-laureats-du-premier-appel-a-projets-du-ftap | Planning | Planning and Scheduling | Knowledge representation | decision support | 16/11/2023 | ||||||||||||||||
| PSTW-294 | Extraction of topographical objects - AI to extract topographical objects from aerial images | https://gouvernement.lu/en/dossiers.gouv_digitalisation%2Ben%2Bdossiers%2B2021%2BAI4Gov.html | This project involved using AI to extract topographical objects from aerial images, thereby making it possible to detect new buildings and roads with a view to identifying construction areas. Extracting these objects made it possible to reduce State officials’ workload and increase the quality and rapidity of updating the databases held by the Land Registry and Topography Administration. A further aim of the project was to allow the creation of new data and services, and object recognition. | National | Luxembourg | LU | Land Registry and Topography Administration | Central-Government | General public services | Executive and legislative organs, financial and fiscal affairs, external affairs. | Pilot | 2.019 | Analysis, monitoring and regulatory research | Information analysis processes | No | No | Artificial Intelligence | G2G | x | x | https://gouvernement.lu/en/dossiers.gouv_digitalisation%2Ben%2Bdossiers%2B2021%2BAI4Gov.html | Perception | Computer vision | Machine learning | object recognition | 16/11/2023 | |||||||||||||||||||
| PSTW-295 | Transcription of texts of articles by using optical character recognition | https://gouvernement.lu/en/dossiers.gouv_digitalisation%2Ben%2Bdossiers%2B2021%2BAI4Gov.html | The aim of the project proposed by the Luxembourg National Library (Bibliothèque nationale de Luxembourg - BnL) is to improve the transcription of the texts of articles by using optical character recognition (OCR). This enhancement was a prerequisite for the automated identification of "named entities" (people, places, organisations, and dates). These entities, detected using AI techniques, form the basis for a new interactive application that allows dynamic exploration of articles, thereby improving access to the archive of digitalised newspapers and journals. | National | Luxembourg | LU | Luxembourg National Library | Central-Government | General public services | Executive and legislative organs, financial and fiscal affairs, external affairs. | Pilot | 2.019 | Analysis, monitoring and regulatory research | Prediction and planning | No | No | Artificial Intelligence | G2G | x | x | https://gouvernement.lu/en/dossiers.gouv_digitalisation%2Ben%2Bdossiers%2B2021%2BAI4Gov.html | Perception | Computer vision | Machine learning | Natural language processing | 16/11/2023 | |||||||||||||||||||
| PSTW-296 | CLAVIS project - Automatic recognition of old handwritten documents | https://sip.gouvernement.lu/en/dossiers.gouv_digitalisation%2Ben%2Bdossiers%2B2021%2BAI4Gov.html | The CLAVIS project proposed by the Luxembourg National archives (Archives nationales de Luxembourg - ANLux) involves submitting digitised images of seventeenth- and eighteenth-century manuscript documents to Transkribus, a platform for AI-assisted recognition of handwriting, transcription, and searches in historic documents. Automated transcription helps to make these sources, hardly exploitable until now, legible and comprehensible again for upcoming generations of researchers. ANLux also expects the project to come up with new possibilities for the automated creation of inventories or indexes of people and places. | National | Luxembourg | LU | Luxembourg National archive | Central-Government | General public services | Executive and legislative organs, financial and fiscal affairs, external affairs. | Pilot | 2.019 | Internal management | Internal support processes | No | No | Artificial Intelligence | G2G | x | x | https://gouvernement.lu/en/dossiers.gouv_digitalisation%2Ben%2Bdossiers%2B2021%2BAI4Gov.html | Perception | Computer vision | Machine learning | Natural language processing | natural language understanding | 16/11/2023 | ||||||||||||||||||
| PSTW-297 | 3D scan underground infrastructure - Prevention damage of critical infrastructure | https://slimstebinnenstad.nl/categorie-projecten/ | The 3D scan of the precise location of the main sewer in combination with an app that visualizes the location of the sewer above ground prevents damage to this critical infrastructure during construction work. | Local | Netherlands | NL | Municipality of Arnhem | Local Government | Housing and community amenities | Water supply. | In development | 2.016 | Analysis, monitoring and regulatory research | Prediction and planning | No | No | Artificial Intelligence | G2B | x | x | Hoekstra, M., Chideock, C., & Veenstra, A.F. van (2021). Quik Scan AI in de Publieke Dienstverlening II - Longlist Initiatieven. TNO: Den Haag. | Planning | Planning and Scheduling | Computer vision | 16/11/2023 | ||||||||||||||||||||
| PSTW-298 | 8TING - Analysis of drivers to keep people in class | https://slimstebinnenstad.nl/categorie-projecten/ https://www.8ting.nl/Cases/Data-analyse-bijstandsbestand/ | With 8TING, the use of pyschology and web technology in the Municipality of Enschede appeals to internal drivers by monitoring and adjusting on more than 80 factors. Based on profile, behaviour and context, it is made clear who needs what attention. With this insight, (automatic) programs are planned to measure, pats on the back and people are kept in class. | Local | Netherlands | NL | 8Ting, business office Work & Income of the municipality of Enschede | Local Government | Education | Secondary education. | In development | 2.021 | Analysis, monitoring and regulatory research | Information analysis processes | No | No | Artificial Intelligence | G2C | x | x | x | Hoekstra, M., Chideock, C., & Veenstra, A.F. van (2021). Quik Scan AI in de Publieke Dienstverlening II - Longlist Initiatieven. TNO: Den Haag. | Planning | Planning and Scheduling | Automated reasoning | 16/11/2023 | |||||||||||||||||||
| PSTW-299 | Aerial Inspection Drones | https://www.rvo.nl/subsidie-en-financieringswijzer/sbir/sbir-oproep-artifici%C3%ABle-intelligentie-voor-de-publieke-diensten/publieke-samenvattingen | Aurea Imaging wants to develop image analysis technology for drones/Unmanned Aerial Vehicles (UAVs) to use them in the agricultural sector in detecting anomalies. These abnormalities may indicate harmful organisms. In a testing ground of the Dutch Food and Consumer Product Safety Authority (NVWA), we investigate the feasibility of this technology. | National | Netherlands | NL | Dutch Food and Consumer Product Safety Authority (NVWA) | Central-Government | Economic Affairs | Agriculture, forestry, fishing and hunting | Pilot | 2.021 | Analysis, monitoring and regulatory research | Information analysis processes | No | No | Artificial Intelligence | G2B | x | x | x | Hoekstra, M., Chideock, C., & Veenstra, A.F. van (2021). Quik Scan AI in de Publieke Dienstverlening II - Longlist Initiatieven. TNO: Den Haag. | Integration and Interaction | Robotics and Automation | Computer vision | unmanned vehicle | 16/11/2023 | ||||||||||||||||||
| PSTW-30 | Texta Toolkit - Identifying documents published without authorisation | https://www.keeletehnoloogia.ee/en | The Ministry of Education and Research performed a document management audit using the Texta Toolkit, which was aimed at identifying the documents that had been published without authorisation (e.g. internal documents, personal data, etc.). During the audit, more than 1,200,000 documents were analysed, converted into machine-readable form and had the personal data removed. In collaboration with the Centre of Registers and Information Systems, the Ministry of Justice removed, using Texta, personal data from nearly 80,000 court decisions involving information about punishments deleted from the Criminal Records Database and republished the decisions in the Court Information System. Texta Toolkit grew out of industrial research in the Software Technology and Applications Competence Center (STACC) and its development has been supported from the Estonian Language Technology programme. | National | Estonia | EE | Ministry of Education and Research | Central-Government | General public services | General services. | Implemented | 2.020 | Enforcement | Predictive enforcement processes | No | No | Artificial Intelligence | G2G | x | x | x | https://www.texta.ee/home | Communication | Natural language processing | Machine learning | Automated reasoning | text analysis | 06/10/2023 | |||||||||||||||||
| PSTW-300 | Agent system | https://werkenbijprorail.nl/nieuws/artificial-intelligence-ingezet-bij-prorail/ | The agent is an autonomous computer program that functions completely independently with associated actions and goals. The officer gives avies to train traffic controllers in case of delay to avoid further delays in train traffic. | National | Netherlands | NL | ProRail | Central-Government | Economic Affairs | Transport | Pilot | 2.018 | Analysis, monitoring and regulatory research | Information analysis processes | No | No | Artificial Intelligence | G2G | x | x | Hoekstra, M., Chideock, C., & Veenstra, A.F. van (2021). Quik Scan AI in de Publieke Dienstverlening II - Longlist Initiatieven. TNO: Den Haag. | Learning | Machine learning | Robotics and Automation | 16/11/2023 | ||||||||||||||||||||
| PSTW-301 | AI for public space notifications - Image recognition to analyse reports | https://www.smartcitydordrecht.nl/gemeentelijke-projecten/dordrecht-koploper-in-onderzoek-gebruik-artificial-intelligence-ai-bij-meldingen-openbare-ruimte https://www.nativeconsulting.nl/tdocumenten/docdetail.aspx?pkey1=447&title=datagedreven-werken-in-de-praktijk-dordrecht-roeselare-be-en-eindhoven | In Dordrecht, residents can report defects and inconveniences in public space to the Wijklijn. These reports vary from loose pavement tiles, broken street lights to reporting dangerous situations. After the report arrives at the municipality, we look at how the situation can be solved. Dordrecht has investigated whether it will be possible in the future to use Artificial Intelligence (AI) to make reporting easier and the process more efficient.With photo a report of defects in the public space; image recognition helps to analyze the report. | Local | Netherlands | NL | Municipality of Dordrecht | Local Government | General public services | Executive and legislative organs, financial and fiscal affairs, external affairs. | Pilot | 2.018 | Enforcement | Smart Recognition processes | No | No | Artificial Intelligence | G2C | x | x | x | x | x | Hoekstra, M., Chideock, C., & Veenstra, A.F. van (2021). Quik Scan AI in de Publieke Dienstverlening II - Longlist Initiatieven. TNO: Den Haag. | Perception | Computer vision | Machine learning | 16/11/2023 | |||||||||||||||||
| PSTW-302 | AI Chatbot Robin - Answer questions about business transfers | https://www.rvo.nl/onderwerpen/agrarisch-ondernemen/uw-registratie-bij-ons/bedrijfsoverdracht | Chatbot Robin is the sequel to the Pilot Watson. Chatbot Robin went live in April 2019. Chatbot Robin is a virtual agent that can answer questions about agricultural business transfers. | National | Netherlands | NL | Netherlands Enterprise Agency | Central-Government | General public services | Executive and legislative organs, financial and fiscal affairs, external affairs. | Implemented | 2.019 | Public services and engagement | Service personalisation (various) | No | No | Artificial Intelligence | G2C | x | x | Hoekstra, M., Chideock, C., & Veenstra, A.F. van (2021). Quik Scan AI in de Publieke Dienstverlening II - Longlist Initiatieven. TNO: Den Haag. | Communication | Natural language processing | Searching | AI Services | chatbot | 16/11/2023 | ||||||||||||||||||
| PSTW-303 | AICrimePrediction (AICP) - Prediction of the risk of crime and terrorism | https://www.rvo.nl/subsidie-en-financieringswijzer/sbir/sbir-oproep-artifici%C3%ABle-intelligentie-voor-de-publieke-diensten/publieke-samenvattingen | AICrimePrediction (AICP) is a feasibility study of the Amsterdam police and Ciphix. It investigates whether the historical data of the control room (type, time, location), combined with the real-time reports by means of AI, can predict the risk of crime and terrorism with great accuracy. | Local | Netherlands | NL32 | Amsterdam Police | Local Government | Public order and safety | Police Services | Pilot | 2.019 | Enforcement | Predictive enforcement processes | No | No | Artificial Intelligence | G2G | x | x | Hoekstra, M., Chideock, C., & Veenstra, A.F. van (2021). Quik Scan AI in de Publieke Dienstverlening II - Longlist Initiatieven. TNO: Den Haag. | Planning | Planning and Scheduling | Automated reasoning | 16/11/2023 | ||||||||||||||||||||
| PSTW-304 | AI machine learning supervised - Delivering learning reports | https://www.rvo.nl/subsidie-en-financieringswijzer/sbir/sbir-oproep-artifici%C3%ABle-intelligentie-voor-de-publieke-diensten/publieke-samenvattingen | Duo is currently holding a small-scale internal pilot called 'AI machine learning supervised', with the aim of delivering a learning report for DUO | National | Netherlands | NL | Education Implementation Service | Central-Government | Education | R&D education. | Pilot | 2.021 | Internal management | Internal primary processes | No | No | Artificial Intelligence | G2C | x | x | x | Hoekstra, M., Chideock, C., & Veenstra, A.F. van (2021). Quik Scan AI in de Publieke Dienstverlening II - Longlist Initiatieven. TNO: Den Haag. | Learning | Machine learning | Automated reasoning | 16/11/2023 | |||||||||||||||||||
| PSTW-305 | AI for detection of diseases in plants and trees | https://www.nvwa.nl/documenten/consument/eten-drinken-roken/vlees-en-vleesproducten/publicaties/advies-van-buro-over-toepassing-sensortechnologie-en-artificial-intelligence-ai-in-slachthuizen-ten-behoeve-van-dierenwelzijn | The NVWA has a pilot run that uses AI to detect diseases in plants and trees. | National | Netherlands | NL | NVWA | Central-Government | Environmental Protection | Protection of biodiversity and landscape. | Pilot | 2.021 | Enforcement | Smart Recognition processes | No | No | Artificial Intelligence | G2G | x | x | Hoekstra, M., Chideock, C., & Veenstra, A.F. van (2021). Quik Scan AI in de Publieke Dienstverlening II - Longlist Initiatieven. TNO: Den Haag. | Perception | Computer vision | Planning and Scheduling | 16/11/2023 | ||||||||||||||||||||
| PSTW-306 | AI for detecting Asian Hornbill | The NVWA has a pilot running that uses AI to detect the Asian Hornbill. If the NVWA receives a notification about a possible nest in a certain area. The NVWA will then fly a drone with thermal imaging camera over that area. The NVWA is also developing an image recognition app for the Asian horn. The app determines whether it is a European or Asian horn. | National | Netherlands | NL | NVWA | Central-Government | Economic Affairs | Agriculture, forestry, fishing and hunting | Pilot | 2.021 | Enforcement | Smart Recognition processes | No | No | Artificial Intelligence | G2G | x | x | x | Hoekstra, M., Chideock, C., & Veenstra, A.F. van (2021). Quik Scan AI in de Publieke Dienstverlening II - Longlist Initiatieven. TNO: Den Haag. | Perception | Computer vision | Planning and Scheduling | 16/11/2023 | ||||||||||||||||||||
| PSTW-307 | AI for fisheries inspections - Detecting illegal barrels | https://www.wur.nl/en/newsarticle/drones-and-ai-to-support-fisheries-inspectors.htm | Aurea Imaging wants to develop image analysis technology for drones/Unmanned Aerial Vehicles (UAVs) to use them in the agricultural sector to detect deviations. These deviations may indicate harmful organisms. In a testing ground of the Dutch Food and Consumer Product Safety Authority (NVWA) we are investigating the feasibility of this technology. The detection of these anomalies using AI has 3 purposes: A more efficient use of resources for inspection (inspection, lab, deployment of equipment), Improving inspection methods of the Netherlands Food and Consumer Product Safety Authority, Achieve higher food safety through better controls. | National | Netherlands | NL | NVWA | Central-Government | Environmental Protection | Environmental protection n.e.c. | Pilot | 2.021 | Enforcement | Supporting inspection processes | No | No | Artificial Intelligence | G2G | x | x | x | Hoekstra, M., Chideock, C., & Veenstra, A.F. van (2021). Quik Scan AI in de Publieke Dienstverlening II - Longlist Initiatieven. TNO: Den Haag. | Perception | Computer vision | Machine learning | 16/11/2023 | |||||||||||||||||||
| PSTW-311 | Asphalt scan - Detection of damage to roads | https://www.baminfra.nl/nieuws/samen-winnen-met-artificial-intelligence | With the help of 'the Asphalt Scan', damage to the road and reduced brightness of signage is recognized. The Asphalt Scan uses satellites and scanning vehicles to collect data. Algorithms then identify the problems on the road. | Regional | Netherlands | NL | Province of North Holland, Municipality of Amersfoort, Bam infra, Province of Gelderland and other provinces | Local Government | Economic Affairs | Transport | In development | 2.019 | Enforcement | Predictive enforcement processes | No | No | Artificial Intelligence | G2C | x | x | Hoekstra, M., Chideock, C., & Veenstra, A.F. van (2021). Quik Scan AI in de Publieke Dienstverlening II - Longlist Initiatieven. TNO: Den Haag. | Planning | Planning and Scheduling | Computer vision | 16/11/2023 | ||||||||||||||||||||
| PSTW-314 | Blue Operational Prevention Service | https://www.rvo.nl/subsidie-en-financieringswijzer/sbir/sbir-oproep-artifici%C3%ABle-intelligentie-voor-de-publieke-diensten/publieke-samenvattingen | The aim of this project is to prevent flooding. The optimal deployment is determined by minimizing real-time information about the risks with smart algorithms based on the available resources. This gives a user a tailor-made action perspective. | National | Netherlands | NL | Netherlands Enterprise Agency (RVO) | Central-Government | Public order and safety | Public order and safety n.e.c. | Pilot | 2.019 | Analysis, monitoring and regulatory research | Prediction and planning | No | No | Artificial Intelligence | G2G | x | x | Hoekstra, M., Chideock, C., & Veenstra, A.F. van (2021). Quik Scan AI in de Publieke Dienstverlening II - Longlist Initiatieven. TNO: Den Haag. | Planning | Planning and Scheduling | Automated reasoning | 16/11/2023 | ||||||||||||||||||||
| PSTW-315 | Tree Monitor - Detecting illegal logging | https://www.neo.nl/nieuws/bomenmonitor-helpt-illegale-kap-op-te-sporen/ | Since December 2017, the province of Gelderland has an additional tool for detecting illegal logging: the tree monitor. Satellite images from different years are compared with each other, if trees have disappeared somewhere, the map indicates this. | Regional | Netherlands | NL | Province of Gelderland, NEO, Wageningen Environmental Research | Regional Government | Environmental Protection | Environmental protection n.e.c. | Implemented | 2.017 | Enforcement | Supporting inspection processes | No | No | Artificial Intelligence | G2G | x | x | x | Hoekstra, M., Chideock, C., & Veenstra, A.F. van (2021). Quik Scan AI in de Publieke Dienstverlening II - Longlist Initiatieven. TNO: Den Haag. | Perception | Computer vision | Machine learning | anomaly detection | 16/11/2023 | ||||||||||||||||||
| PSTW-316 | Brid.ge - Smart City Enschede | https://www.youtube.com/watch?v=4Pf_dK-OtFs, https://techforfuture.nl/smart-city-enschede-onderzoekers-combineren-realtime-informatie-over-parkeren-weer-en-vervoer/ | With the available information, the visitor can drive directly to the right parking lot or still opt for public transport. | Local | Netherlands | NL | Municipality of Enschede, Saxion, Winkelhart Enschede, University of Twente, Both Social, eLabbs, Marotura, Present Media, Squal Media, Think Public, University of Twente and Winkelhart Enschede | Local Government | General public services | General public services n.e.c. | Pilot | 2.018 | Public services and engagement | Service integration (various) | No | No | Artificial Intelligence | G2C | x | x | x | x | x | Hoekstra, M., Chideock, C., & Veenstra, A.F. van (2021). Quik Scan AI in de Publieke Dienstverlening II - Longlist Initiatieven. TNO: Den Haag. | Reasoning | Automated reasoning | Searching | 16/11/2023 | |||||||||||||||||
| PSTW-317 | Business Intelligence and Analytics (BI&A) - Indication of tax fraud risks based on previous declarations | https://decorrespondent.nl/1766/Vergeet-de-politiestaat-Welkom-in-de-belastingstaat/90525160-5a2c27c2 | Dutch Tax Authority works with self-learning models that increasingly more refined indicate where risks are based on previous inspected declarations and feedback of the results. An example is Dynamic Monitoring. This project links outstanding receivables to sources for redress (wages, cars, real estate, etc.) and generates a list of claims with (new) redress options. | National | Netherlands | NL | Dutch Tax Authority | Central-Government | General public services | Executive and legislative organs, financial and fiscal affairs, external affairs. | Implemented | 2.014 | Analysis, monitoring and regulatory research | Monitoring policy implementation | No | No | Artificial Intelligence | G2G | x | x | Hoekstra, M., Chideock, C., & Veenstra, A.F. van (2021). Quik Scan AI in de Publieke Dienstverlening II - Longlist Initiatieven. TNO: Den Haag. | Reasoning | Automated reasoning | Machine learning | 16/11/2023 | ||||||||||||||||||||
| PSTW-318 | Case Law Engine | https://www.lexiq.nl/clients | The Public Prosecution Service (OM, Openbare Ministerie) is a Dutch governmental institution that investigated the applications of AI in their daily working procedures. The OM needed a tool to reduce research time and also to improve the quality of case preparation. The private company LexIQ developed a “Jurisprudentierobot” for the OM, a tool that supports prosecutors and researchers in their daily work to search, analyse and make use of insights in criminal cases. the software saves time and gives users an indication of the possible outcome in court. Additionally, it also helps them discover hidden information. The use of machine learning algorithms and our features such as data visualisations and intuitive search functionalities, helped OM approach the overload of information in a new and better way. | National | Netherlands | NL | Public Prosecution Service | Central-Government | Public order and safety | Law courts | Implemented | 2.019 | Analysis, monitoring and regulatory research | Information analysis processes | No | No | Artificial Intelligence | G2G | x | x | x | x | Hoekstra, M., Chideock, C., & Veenstra, A.F. van (2021). Quik Scan AI in de Publieke Dienstverlening II - Longlist Initiatieven. TNO: Den Haag. | Reasoning | Knowledge representation | Searching | 16/11/2023 | ||||||||||||||||||
| PSTW-32 | Traffic load - Machine vision for collecting information on traffic load | https://automatingsociety.algorithmwatch.org/report2020/estonia/ | The Tallinn transport Dep. started developing a machine vision application in autumn 2018 in collaboration with Sifr OU. The main objective of this application is to identify the traffic load within Tallinn, i.e. how many cars drive in and out of the city in a day in order to make city transport planning related decisions based on such data (e.g. parking issues, road construction, etc.). Three cameras were selected on intersections in Tallinn to train the application to count the vehicles passing by the cameras. The training of the application was a crucial process in developing the solution since there was no ready-made solution available that suited the circumstances of Tallinn. The result is an application that uses machine vision to count buses, cars, lorries and motorcycles and in the future hopefully also pedestrians, cyclists and like with a 70% accuracy on the traffic load in a certain area when previously there no such information available at all. | Local | Estonia | EE | Public Transport and Traffic Management Transport Board in Tallinn | Local Government | Economic Affairs | Transport | Implemented | 2.018 | Enforcement | Smart Recognition processes | No | No | Artificial Intelligence | G2G | x | x | x | https://www.kratid.ee/tlt-kasutuslugu | Perception | Computer vision | Machine learning | 06/10/2023 | |||||||||||||||||||
| PSTW-320 | CrossWalk in Smart City Rijswijk | https://www.mentalfloss.com/article/502776/app-gives-older-people-more-time-cross-street | The municipality of Rijswijk uses a smart pedestrian app for people who have difficulty walking. They are given more time to cross by extending the time of green traffic light. | Local | Netherlands | NL | Municipality of Rijswijk, Dynniq | Local Government | Health | Health n.e.c. | In development | 2.021 | Enforcement | Smart Recognition processes | No | No | Artificial Intelligence | G2C | x | x | Hoekstra, M., Chideock, C., & Veenstra, A.F. van (2021). Quik Scan AI in de Publieke Dienstverlening II - Longlist Initiatieven. TNO: Den Haag. | Perception | Computer vision | Machine learning | 20/11/2023 | ||||||||||||||||||||
| PSTW-321 | Improve data quality with AI - Machine learning to improve the data quality of registrations | The services of the municipality of The Hague run on data registrations. The quality of the registrations can have consequences for the quality of the service. In this pilot, AI (machine learning) was used with the aim of analyzing, monitoring and continuously improving the data quality of the registrations. Phinion's Qbot product has been used. Qbot discovers patterns and deviations within and between registrations via machine learning. | Local | Netherlands | NL | Municipality of The Hague and Phinion Data Engineering. | Local Government | General public services | R&D general public services. | Implemented | 2.020 | Internal management | Internal primary processes | No | No | Artificial Intelligence | G2G | x | x | Hoekstra, M., Chideock, C., & Veenstra, A.F. van (2021). Quik Scan AI in de Publieke Dienstverlening II - Longlist Initiatieven. TNO: Den Haag. | Learning | Machine learning | Knowledge representation | 20/11/2023 | |||||||||||||||||||||
| PSTW-322 | The Refinery: AI in investigation support | https://zoek.officielebekendmakingen.nl/blg-849198.pdf | A facility that makes it possible to quickly access, give meaning to large amounts of police data, to analyse and visualize in conjunction with each other. | Local | Netherlands | NL | Dutch Police | Local Government | Public order and safety | Police Services | In development | 2.018 | Analysis, monitoring and regulatory research | Information analysis processes | No | No | Artificial Intelligence | G2G | x | x | Hoekstra, M., Chideock, C., & Veenstra, A.F. van (2021). Quik Scan AI in de Publieke Dienstverlening II - Longlist Initiatieven. TNO: Den Haag. | Planning | Planning and Scheduling | Machine learning | 20/11/2023 | ||||||||||||||||||||
| PSTW-324 | Detection of aggression, panic and abnormal behaviour with smart cameras | https://www.rvo.nl/subsidie-en-financieringswijzer/sbir/sbir-oproep-artifici%C3%ABle-intelligentie-voor-de-publieke-diensten/publieke-samenvattingen | In this project, the private company ViNotion develops AI technology that analyzes the behavior of individuals and recognizes panic, aggression and deviant behavior early. This allows early signalling in large public areas such as stations, airports, city centres and entertainment centres, so that security and assistance can be switched on much faster. The faster and more efficient deployment of personnel reduces the impact of incidents on the public and the environment. | National | Netherlands | NL | Netherlands Enterprise Agency (RVO) | Central-Government | Public order and safety | Public order and safety n.e.c. | Pilot | 2.019 | Enforcement | Smart Recognition processes | No | No | Artificial Intelligence | G2G | x | x | x | Hoekstra, M., Chideock, C., & Veenstra, A.F. van (2021). Quik Scan AI in de Publieke Dienstverlening II - Longlist Initiatieven. TNO: Den Haag. | Perception | Computer vision | Machine learning | 20/11/2023 | |||||||||||||||||||
| PSTW-325 | Firework nuisance detection system - AI to determine if bangs are firework | https://www.ad.nl/amersfoort/amersfoort-zet-experiment-met-vuurwerkdetectie-voort~a4e1dbbd/ | If multiple sensors catch a bang, the system determines whether these are (illegal) fireworks. If so, municipal enforcers will receive a notification on their smartphones. This data makes it clear, for example, which routes nuisance offenders run, at what times they are lit and where. | Local | Netherlands | NL | Municipality of Amersfoort | Local Government | Public order and safety | Police Services | In development | 2.017 | Enforcement | Smart Recognition processes | No | No | Artificial Intelligence | G2G | x | x | x | Hoekstra, M., Chideock, C., & Veenstra, A.F. van (2021). Quik Scan AI in de Publieke Dienstverlening II - Longlist Initiatieven. TNO: Den Haag. | Perception | Audio processing | Machine learning | 20/11/2023 | |||||||||||||||||||
| PSTW-326 | Diagnosis Plan and Control Tool - Assessing the risk of home fraud | https://www.toetsingscommissievp.nl/binaries/toetsingscommissievp/documenten/publicaties/2020/01/02/boxmeer-vu-2016/Boxmeer+VU+2016.pdf | This allows the municipality to assess the risk of fraud so that it can make a choice whether or not to go on a home visit to verify data. A risk indicator in this system is, for example, the form in which one lives (such as with family, subletting) and whether or not with inmates. These circumstances are then related to the amount of housing costs and any debts. This digital tool allows a municipality to use its human power more selectively during home visits. | Local | Netherlands | NL | Municipalities (Boxmeer) | Local Government | Social protection | Social protection n.e.c. | In development | 2.011 | Enforcement | Supporting inspection processes | No | No | Artificial Intelligence | G2C | x | x | x | Hoekstra, M., Chideock, C., & Veenstra, A.F. van (2021). Quik Scan AI in de Publieke Dienstverlening II - Longlist Initiatieven. TNO: Den Haag. | Planning | Planning and Scheduling | Automated reasoning | 20/11/2023 | |||||||||||||||||||
| PSTW-327 | Digital assistant for answering Parliamentary questions | https://datascienceinitiative.eu/wp-content/uploads/2020/05/DSI-AIBinnenDeOverheid.pdf | The digital assistant supports policy staff in answering parliamentary questions by searching public sources | National | Netherlands | NL | Ministry of Social Affairs and Employment | Central-Government | General public services | Executive and legislative organs, financial and fiscal affairs, external affairs. | Implemented | 2.020 | Internal management | Internal primary processes | No | No | Artificial Intelligence | G2G | x | x | x | x | x | x | x | Hoekstra, M., Chideock, C., & Veenstra, A.F. van (2021). Quik Scan AI in de Publieke Dienstverlening II - Longlist Initiatieven. TNO: Den Haag. | Communication | Natural language processing | Searching | Q&A | 20/11/2023 | ||||||||||||||
| PSTW-328 | Digital identification and verification | https://www.digitaleoverheid.nl/actielijn/onderzoek-naar-gebruik-automatische-gezichtsherkenning-en-andere-vormen-van-biometrische-identificatie/ | Research into the use of automatic facial recognition and other forms of biometric identification. | National | Netherlands | NL | Ministry of Justice and Security, Ministry of the Interior and Kingdom Relations | Central-Government | General public services | General services. | In development | 2.019 | Enforcement | Smart Recognition processes | No | No | Artificial Intelligence | G2G | x | x | x | x | Hoekstra, M., Chideock, C., & Veenstra, A.F. van (2021). Quik Scan AI in de Publieke Dienstverlening II - Longlist Initiatieven. TNO: Den Haag. | Perception | Computer vision | Machine learning | facial recognition | 20/11/2023 | |||||||||||||||||
| PSTW-329 | E-Discovery - automatic classifcation of incoming and outgoing emails | https://www.nationaalarchief.nl/archiveren/nieuws/e-discovery-machine-learning-en-e-mail | In 2016, the Nationaal Archief started a study into the possibilities of E-discovery within information management. As part of this research, in collaboration with the ICT Implementation Organisation (ICTU), a prototype has been developed that automatically classifies incoming and outgoing e-mails. | National | Netherlands | NL | National Archives and ICTU | Central-Government | General public services | Executive and legislative organs, financial and fiscal affairs, external affairs. | Pilot | 2.017 | 2018 | Internal management | Internal support processes | No | No | Artificial Intelligence | G2G | x | x | x | Hoekstra, M., Chideock, C., & Veenstra, A.F. van (2021). Quik Scan AI in de Publieke Dienstverlening II - Longlist Initiatieven. TNO: Den Haag. | Reasoning | Automated reasoning | Machine learning | text classification | 20/11/2023 | |||||||||||||||||
| PSTW-330 | Excess Material Exchange (EME) | https://www.prorail.nl/nieuws/online-handelsplatform-voor-restmaterialen, https://excessmaterialsexchange.com/en_us/ | Various organizations are exploring the possibilities of exchanging residual materials among themselves. With the help of AI, supply and demand are linked together and a trading platform is created to close the residual flows circle of the organizations. EME then uses Artificial Intelligence (AI) to quickly read and interpret all that data. AI ensures that matches are made quickly and on a large scale between buyers and suppliers of materials. The intelligence lies in the fact that the AI program also brings together parties. | National | Netherlands | NL | ProRail, Schiphol and other organisations | Central-Government | Economic Affairs | Transport | Implemented | 2.018 | Public services and engagement | Tracking of goods and assets along the supply chain | No | No | Artificial Intelligence | G2G | x | x | Hoekstra, M., Chideock, C., & Veenstra, A.F. van (2021). Quik Scan AI in de Publieke Dienstverlening II - Longlist Initiatieven. TNO: Den Haag. | Learning | Machine learning | Optimisation | 20/11/2023 | ||||||||||||||||||||
| PSTW-332 | Forensic Image Recognition (FIRE) - Recognition of containers that have illegal cargo | https://securitydelta.nl/media/com_hsd/report/299/document/DSI-AIBinnenDeOverheid.pdf | The Netherlands Forensic Institute (NFI) is best known for the most visible part of forensic research. The men and women in white suits. “But our field of work goes much further than that,” says Lisanne van Dijk. In principle, we have three core tasks. Firstly, investigating cases for the police and the prosecution, we also do the research and development to support case investigation. Finally, we are responsible for knowledge exchange and education on these topics.’ The NFI also provides data support to other parts of the government. ‘The classical statistics that belong to our field are well suited to that. Also in combination with AI. “Explainable AI” is especially important, so AI explaining exactly which data is used and how, for example, it is weighed in an algorithm. One of the AI projects at NFI is the automatic recognition of images. The FIRE (Forensic Image Recognition) system is designed to relieve detection staff. ‘You can of course imagine everything in image recognition, but before we can use this everywhere we start with a few framed fields. For example, the recognition of sea containers: can we learn AI to recognise containers that have potentially illegal cargo? For the recognition of this image, huge amounts of data carriers and data are analysed. “If this succeeds, we might be able to bring people’s work back to a few hours with the help of AI,” says Van Dijk enthusiastically. But it’s not that far. ‘We need to first look at how we can compile, store and use datasets. There is, of course, a legal challenge. It is very good that we are bound by rules, but it would be interesting if we could find a solution that all security services can use together. | National | Netherlands | NL | Netherlands Forensic Institute (NFI) | Central-Government | Public order and safety | Police Services | Pilot | 2.020 | Enforcement | Smart Recognition processes | No | No | Artificial Intelligence | G2B | x | x | x | Hoekstra, M., Chideock, C., & Veenstra, A.F. van (2021). Quik Scan AI in de Publieke Dienstverlening II - Longlist Initiatieven. TNO: Den Haag. | Perception | Computer vision | Machine learning | image processing | 20/11/2023 | ||||||||||||||||||
| PSTW-333 | Geniq - reports wait times | https://www.pinkroccade-healthcare.nl/nieuws/robuust-maken-mijnquarant-en-uitbreidingen-op-geniq-ggz/ | Calculates, analyzes, and reports wait times, so that an institution always has up-to-date insights. | Local | Netherlands | NL | Mental health institutions | Local Government | Social protection | Social protection n.e.c. | Implemented | 2.017 | Analysis, monitoring and regulatory research | Information analysis processes | No | No | Artificial Intelligence | G2C | x | x | x | Hoekstra, M., Chideock, C., & Veenstra, A.F. van (2021). Quik Scan AI in de Publieke Dienstverlening II - Longlist Initiatieven. TNO: Den Haag. | Learning | Machine learning | Planning and Scheduling | 20/11/2023 | |||||||||||||||||||
| PSTW-334 | GEO reference of documents - Gaining more insight into data on nitrogen emissions and soil pollution | https://www.bolesian.ai/case-gelderland/ | Bolesian has developed an application for the province of Gelderland with which large amounts of unstructured information and data can be analyzed. The focus is on gaining more insight into data on nitrogen emissions and soil pollution. | Regional | Netherlands | NL | Province of Gelderland, Bolesian.ai | Regional Government | Environmental Protection | Pollution abatement. | Pilot | 2.021 | Analysis, monitoring and regulatory research | Information analysis processes | No | No | Artificial Intelligence | G2G | x | x | Hoekstra, M., Chideock, C., & Veenstra, A.F. van (2021). Quik Scan AI in de Publieke Dienstverlening II - Longlist Initiatieven. TNO: Den Haag. | Reasoning | Automated reasoning | Machine learning | 20/11/2023 | ||||||||||||||||||||
| PSTW-335 | Graasdierpremie - Use of drones in counting animals | https://isis-data.science.uva.nl/jvgemert/conservationDronesECCV14w/ | Nature conservation by automatically monitoring animal distribution and animal abundance. Typically, such conservation tasks are performed manually on foot or after an aerial recording from a manned aircraft. Such manual approaches are expensive, slow and labor intensive. | National | Netherlands | NL | Netherlands Food and Consumer Product Safety Authority (NVWA) | Central-Government | Economic Affairs | Agriculture, forestry, fishing and hunting | Pilot | 2.014 | Enforcement | Supporting inspection processes | No | No | Artificial Intelligence | G2B | x | x | x | Hoekstra, M., Chideock, C., & Veenstra, A.F. van (2021). Quik Scan AI in de Publieke Dienstverlening II - Longlist Initiatieven. TNO: Den Haag. | Integration and Interaction | Robotics and Automation | Computer vision | 20/11/2023 | |||||||||||||||||||
| PSTW-337 | Hansken - Recognizing images of narcotics in digital seizure | https://www.hansken.nl/latest/news/2021/03/21/smart-algorithm-faster-search | The NFI has a project under way using AI to recognise narcotics seized from images. | National | Netherlands | NL | Netherlands Forensic Institute | Central-Government | Health | Health n.e.c. | Implemented | 2.021 | Enforcement | Predictive enforcement processes | No | No | Artificial Intelligence | G2G | x | x | x | Hoekstra, M., Chideock, C., & Veenstra, A.F. van (2021). Quik Scan AI in de Publieke Dienstverlening II - Longlist Initiatieven. TNO: Den Haag. | Perception | Computer vision | Machine learning | image processing | 20/11/2023 | ||||||||||||||||||
| PSTW-339 | Identifying people at risk of falling into large debts | https://nos.nl/artikel/2366864-fraude-opsporen-of-gevaar-van-discriminatie-gemeenten-gebruiken-slimme-algoritmes.html | People at risk of defaulting into large debts automatically surface | Local | Netherlands | NL32 | Municipality of Amsterdam | Local Government | Social protection | Social protection n.e.c. | In development | 2.021 | Enforcement | Supporting inspection processes | No | No | Artificial Intelligence | G2C | x | x | x | Hoekstra, M., Chideock, C., & Veenstra, A.F. van (2021). Quik Scan AI in de Publieke Dienstverlening II - Longlist Initiatieven. TNO: Den Haag. | Planning | Planning and Scheduling | Automated reasoning | 20/11/2023 | |||||||||||||||||||
| PSTW-340 | Infobox criminal and unexplained assets (iCOV) | https://www.securitymanagement.nl/big-data-fraude/ https://icov.nl/organisatie/ | System provides insight into the assets of individuals and companies based on risk factors. An example is analyzing suspicious transactions in Rotterdam-Zuid. | National | Netherlands | NL | Public Prosecutor's Office, the National Police, the Tax Authorities, Customs, the FIOD and the Financial Intelligence Unit, the Social Affairs and Employment Inspectorate (Investigation Directorate), the Intelligence and Investigation Service of the Environment and Transport Inspectorate (ILT-IOD), the Intelligence and Investigation Service of the Dutch Food and Consumer Product Safety Authority (NVWA-IOD), the Media Commissioner | Central-Government | Public order and safety | Police Services | In development | 2.014 | Enforcement | Supporting inspection processes | No | No | Artificial Intelligence | G2G | x | x | x | Hoekstra, M., Chideock, C., & Veenstra, A.F. van (2021). Quik Scan AI in de Publieke Dienstverlening II - Longlist Initiatieven. TNO: Den Haag. | Planning | Planning and Scheduling | Automated reasoning | data analytics | 20/11/2023 | ||||||||||||||||||
| PSTW-341 | Inspection bridges with drones | https://securitydelta.nl/media/com_hsd/report/299/document/DSI-AIBinnenDeOverheid.pdf | Instead of human capacity, drones are used to inspect bridges and viaducts. | National | Netherlands | NL | Ministry of Instrastructures and market parties | Central-Government | Economic Affairs | Transport | Pilot | 2.020 | Enforcement | Supporting inspection processes | No | No | Artificial Intelligence | G2C | x | x | Hoekstra, M., Chideock, C., & Veenstra, A.F. van (2021). Quik Scan AI in de Publieke Dienstverlening II - Longlist Initiatieven. TNO: Den Haag. | Integration and Interaction | Robotics and Automation | Computer vision | 20/11/2023 | ||||||||||||||||||||
| PSTW-342 | Intelligent traffic control systems (I-VRI's) - Better traffic flow | https://www.talking-traffic.com/nl/partner-worden-bij-talking-traffic/clusters-en-expertise/intelligente-vri-s | The province of Gelderland has replaced the existing traffic lights with intelligent traffic control systems (iVRIs) at 8 intersections in Arnhem and Velp. These new installations ensure better flow. The iVRI's use mobile data from road users. For example, buses and emergency services can be given priority when passing through an intersection. In addition, the road user receives up-to-date information about the fastest route through the city and advice on speed. This information allows road users to tailor their traffic behaviour to the current situation. This results in a better flow. | Local | Netherlands | NL | Province of Gelderland | Local Government | Economic Affairs | Transport | In development | 2.016 | Analysis, monitoring and regulatory research | Prediction and planning | No | No | Artificial Intelligence | G2G | x | x | Hoekstra, M., Chideock, C., & Veenstra, A.F. van (2021). Quik Scan AI in de Publieke Dienstverlening II - Longlist Initiatieven. TNO: Den Haag. | Planning | Planning and Scheduling | Machine learning | 20/11/2023 | ||||||||||||||||||||
| PSTW-343 | Use of scan cars for underground containers - Determining type of waste | https://www.eionet.europa.eu/etcs/etc-wmge/products/etc-wmge-reports/digital-waste-management/@@download/file/Digital%20waste%20management.pdf | By means of scan cars that drive around The Hague, photos can be taken of underground containers (ORAC's). Thanks to AI, it is determined what type of waste there is. | Local | Netherlands | NL | Municipality of The Hague | Local Government | Housing and community amenities | Housing and community amenities n.e.c. | In development | 2.020 | Enforcement | Smart Recognition processes | No | No | Artificial Intelligence | G2B | x | x | Hoekstra, M., Chideock, C., & Veenstra, A.F. van (2021). Quik Scan AI in de Publieke Dienstverlening II - Longlist Initiatieven. TNO: Den Haag. | Perception | Computer vision | Automated reasoning | 20/11/2023 | ||||||||||||||||||||
| PSTW-344 | iRN_iColumbo | https://docplayer.nl/4918688-Projectplan-verduurzaming-irn-icolumbo.html | A service within the Internet Research & Investigation Network (iRN) of the police where the Internet can be methodically and automatically searched for suspicious material. | National | Netherlands | NL | Dutch Police | Central-Government | Public order and safety | Police Services | In development | 2.011 | Enforcement | Predictive enforcement processes | No | No | Artificial Intelligence | G2G | x | x | Hoekstra, M., Chideock, C., & Veenstra, A.F. van (2021). Quik Scan AI in de Publieke Dienstverlening II - Longlist Initiatieven. TNO: Den Haag. | Learning | Machine learning | Searching | 20/11/2023 | ||||||||||||||||||||
| PSTW-345 | Artificial Intelligence Knowledge System for the judiciary searches for similar lawsuits | https://rm.coe.int/challenges-and-opportunities-of-ai-in-the-judicial-system-reflections-/16808e4d88 | Knowledge system searches for similar lawsuits using entered text and gives the user the top 10 most similar lawsuits. | Regional | Netherlands | NL | District Court of East Brabant | Regional Government | Public order and safety | Law courts | Pilot | 2.018 | Internal management | Internal support processes | No | No | Artificial Intelligence | G2B | x | x | x | x | x | Hoekstra, M., Chideock, C., & Veenstra, A.F. van (2021). Quik Scan AI in de Publieke Dienstverlening II - Longlist Initiatieven. TNO: Den Haag. | Reasoning | Knowledge representation | Natural language processing | text classification | 20/11/2023 | ||||||||||||||||
| PSTW-346 | LAA - Address quality in Personal Records Database (BRP) | https://www.ictu.nl/projecten/landelijke-aanpak-adreskwaliteit | Data analysis used to achieve pattern recognition and to search for incorrect addressing based on this. The aim is to put the BRP in order and ultimately contribute to the fight against fraud. | National | Netherlands | NL | Ministry of Interior | Central-Government | General public services | Executive and legislative organs, financial and fiscal affairs, external affairs. | In development | 2.018 | Enforcement | Predictive enforcement processes | No | No | Artificial Intelligence | G2G | x | x | Hoekstra, M., Chideock, C., & Veenstra, A.F. van (2021). Quik Scan AI in de Publieke Dienstverlening II - Longlist Initiatieven. TNO: Den Haag. | Planning | Planning and Scheduling | Automated reasoning | pattern recognition | 20/11/2023 | |||||||||||||||||||
| PSTW-347 | Using smart algorithms to map whether building or demolishing certain homes improves liveability | https://nos.nl/artikel/2366864-fraude-opsporen-of-gevaar-van-discriminatie-gemeenten-gebruiken-slimme-algoritmes.html | The Municipality of Breda uses smart algorithms to investigate whether building or demolishing certain types of homes improves the quality of life. | Local | Netherlands | NL | Municipality of Breda | Local Government | Housing and community amenities | Housing development. | In development | 2.021 | Analysis, monitoring and regulatory research | Prediction and planning | No | No | Artificial Intelligence | G2G | x | x | x | x | x | Hoekstra, M., Chideock, C., & Veenstra, A.F. van (2021). Quik Scan AI in de Publieke Dienstverlening II - Longlist Initiatieven. TNO: Den Haag. | Planning | Planning and Scheduling | Automated reasoning | 20/11/2023 | |||||||||||||||||
| PSTW-349 | Detecting 'unknown' companies with environmental risk | https://www.digitaleoverheid.nl/nieuws/data-project-eindhoven-maakt-onvindbare-bedrijven-vindbaar/ | Mapping unknown companies that pose a potential environmental risk by making smart use of data. | Local | Netherlands | NL | Municipality of Eindhoven | Local Government | Economic Affairs | General economic, commercial and labour affair | Implemented | 2.017 | Enforcement | Predictive enforcement processes | No | No | Artificial Intelligence | G2G | x | x | x | Hoekstra, M., Chideock, C., & Veenstra, A.F. van (2021). Quik Scan AI in de Publieke Dienstverlening II - Longlist Initiatieven. TNO: Den Haag. | Planning | Planning and Scheduling | Automated reasoning | 20/11/2023 | |||||||||||||||||||
| PSTW-350 | Detecting welfare fraud - Prediction of the likelihood of unlawful behavior on the House Market | https://www.nissewaard.nl/werk-en-inkomen/werk-en-inkomen_to/voorspelmodel-bijstandsfraude.htm | The Municipality of Nissewaard uses AI to detect welfare fraud. The algorithm maps patterns in data that indicate an increased risk of wrongdoing. Based on these patterns, the algorithm predicts the likelihood of unlawful behavior for each client. | Local | Netherlands | NL | Totta Datalab, municipality of Nissewaard, municipality of Brielle | Local Government | Social protection | Social protection n.e.c. | In development | 2.017 | Enforcement | Predictive enforcement processes | No | No | Artificial Intelligence | G2G | x | x | Hoekstra, M., Chideock, C., & Veenstra, A.F. van (2021). Quik Scan AI in de Publieke Dienstverlening II - Longlist Initiatieven. TNO: Den Haag. | Planning | Planning and Scheduling | Automated reasoning | 20/11/2023 | ||||||||||||||||||||
| PSTW-351 | Detecting welfare fraud in the municipality of Deventer and Goirle (SyRI system) | https://nos.nl/artikel/2366864-fraude-opsporen-of-gevaar-van-discriminatie-gemeenten-gebruiken-slimme-algoritmes.html | Generating risk profiles of welfare recipients. On the basis of the risk score, it is determined whether a dossier is additionally investigated. (SyRI system) | Local | Netherlands | NL | Municipality of Deventer, Municipality of Goirle | Local Government | Social protection | Social protection n.e.c. | Pilot | 2.021 | Enforcement | Predictive enforcement processes | No | No | Artificial Intelligence | G2G | x | x | Hoekstra, M., Chideock, C., & Veenstra, A.F. van (2021). Quik Scan AI in de Publieke Dienstverlening II - Longlist Initiatieven. TNO: Den Haag. | Planning | Planning and Scheduling | Machine learning | 20/11/2023 | ||||||||||||||||||||
| PSTW-352 | Detection of crime and subversion in the Municipality of Leudal (SyRI system) | https://nos.nl/artikel/2366864-fraude-opsporen-of-gevaar-van-discriminatie-gemeenten-gebruiken-slimme-algoritmes.html | The municipality of Leudal uses algorithms (SyRI system) to detect crime and subversion: in buildings where the paperwork smacks of suspicious cases. | Local | Netherlands | NL | Municipality of Leudal | Local Government | Public order and safety | Public order and safety n.e.c. | In development | 2.021 | Enforcement | Predictive enforcement processes | No | No | Artificial Intelligence | G2G | x | x | Hoekstra, M., Chideock, C., & Veenstra, A.F. van (2021). Quik Scan AI in de Publieke Dienstverlening II - Longlist Initiatieven. TNO: Den Haag. | Planning | Planning and Scheduling | Machine learning | 20/11/2023 | ||||||||||||||||||||
| PSTW-353 | Detection of crime and subversion in the municipality of Dronten (SyRI system) | https://nos.nl/artikel/2366864-fraude-opsporen-of-gevaar-van-discriminatie-gemeenten-gebruiken-slimme-algoritmes.html | Dronten Municipality has an experiment under way to investigate how algorithms (SyRI system) can be used to detect subversive crime | Local | Netherlands | NL | Municipality of Dronten | Local Government | Public order and safety | Public order and safety n.e.c. | Pilot | 2.021 | Enforcement | Predictive enforcement processes | No | No | Artificial Intelligence | G2G | x | x | Hoekstra, M., Chideock, C., & Veenstra, A.F. van (2021). Quik Scan AI in de Publieke Dienstverlening II - Longlist Initiatieven. TNO: Den Haag. | Planning | Planning and Scheduling | Machine learning | 20/11/2023 | ||||||||||||||||||||
| PSTW-354 | Detection of crime and subversion in the municipality of Maastricht (SyRI system) | https://nos.nl/artikel/2366864-fraude-opsporen-of-gevaar-van-discriminatie-gemeenten-gebruiken-slimme-algoritmes.html | The municipality of Maastricht uses algorithms (SyRI system) to detect crime and subversion: in buildings where the paperwork smacks of suspicious cases. | Local | Netherlands | NL | Municipality of Maastricht | Local Government | Public order and safety | Public order and safety n.e.c. | In development | 2.021 | Enforcement | Predictive enforcement processes | No | No | Artificial Intelligence | G2G | x | x | Hoekstra, M., Chideock, C., & Veenstra, A.F. van (2021). Quik Scan AI in de Publieke Dienstverlening II - Longlist Initiatieven. TNO: Den Haag. | Planning | Planning and Scheduling | Machine learning | 20/11/2023 | ||||||||||||||||||||
| PSTW-355 | Detection of crime and subversion in the municipality of Nederweert (SyRI system) | https://nos.nl/artikel/2366864-fraude-opsporen-of-gevaar-van-discriminatie-gemeenten-gebruiken-slimme-algoritmes.html | The municipality of Nederweert uses algorithms (SyRI system) to detect crime and subversion: in buildings where the paperwork smacks of suspicious cases. | Local | Netherlands | NL | Municipality of Nederweert | Local Government | Public order and safety | Public order and safety n.e.c. | In development | 2.021 | Enforcement | Predictive enforcement processes | No | No | Artificial Intelligence | G2G | x | x | x | x | x | Hoekstra, M., Chideock, C., & Veenstra, A.F. van (2021). Quik Scan AI in de Publieke Dienstverlening II - Longlist Initiatieven. TNO: Den Haag. | Planning | Planning and Scheduling | Machine learning | 20/11/2023 | |||||||||||||||||
| PSTW-356 | Parking control in various Dutch municipalities - Parking control by means of scan cars | https://algoritmeregister.amsterdam.nl/parkeercontrole/ | Parking control by means of scan cars. The scan cars are equipped with cameras and drive past parking spaces in the city. The cameras capture car license plates and use an image recognition algorithm to identify license plates. | Local | Netherlands | NL | Municipality of Amsterdam (Parking, Team Analysis & Advice), the Hague, Rotterdam and Utrecht | Local Government | Public order and safety | Police Services | In development | 2.021 | Enforcement | Smart Recognition processes | No | No | Artificial Intelligence | G2C | x | x | Hoekstra, M., Chideock, C., & Veenstra, A.F. van (2021). Quik Scan AI in de Publieke Dienstverlening II - Longlist Initiatieven. TNO: Den Haag. | Perception | Computer vision | Connected and Automated vehicles | 20/11/2023 | ||||||||||||||||||||
| PSTW-357 | Passer-by count | https://www.intemo.com/passantenstromen-in-beeld/ | The municipality of Nijmegen uses sensors to visual monitor the hustle and bustle of the city and the economic development of the centre. | Local | Netherlands | NL | Intemo, Municipality of Nijmegen | Local Government | Economic Affairs | Economic affairs n.e.c | In development | 2.021 | Enforcement | Smart Recognition processes | No | No | Artificial Intelligence | G2G | x | x | x | Hoekstra, M., Chideock, C., & Veenstra, A.F. van (2021). Quik Scan AI in de Publieke Dienstverlening II - Longlist Initiatieven. TNO: Den Haag. | Perception | Computer vision | Machine learning | 20/11/2023 | |||||||||||||||||||
| PSTW-358 | Analyzing data to help people on welfare get back to work for Social Assistance in The Hague | https://securitydelta.nl/media/com_hsd/report/299/document/DSI-AIBinnenDeOverheid.pdf | Analyzing data to help people on welfare get back to work. The system finds people at an early stage so that they can be helped immediately on their way. | Local | Netherlands | NL | Municipality of The Hague | Local Government | Social protection | Unemployment. | Pilot | 2.020 | Analysis, monitoring and regulatory research | Information analysis processes | No | No | Artificial Intelligence | G2C | x | x | x | Hoekstra, M., Chideock, C., & Veenstra, A.F. van (2021). Quik Scan AI in de Publieke Dienstverlening II - Longlist Initiatieven. TNO: Den Haag. | Planning | Planning and Scheduling | Machine learning | 20/11/2023 | |||||||||||||||||||
| PSTW-359 | AviaTor - Pilot detection child abuse | https://aviatorproject.com/ https://www.ziuz.com/nl/nieuws/aviator-project-de-volgende-fase/ | AviaTor, which stands for Augmented Visual Intelligence and Targeted Online Research,was developed from a research project into a working prototype in just 12 months. By using expert insight gained from extensive interviews with the Dutch and Belgian police, it was possible to establish how to best process NCMEC referrals. The AviaTor Project is funded by the European Union's Internal Security Fund – Police. ZiuZ develops a solution AviaTor, which stands for Augmented Visual Intelligence and Targeted Online Research, is an efficient tool that helps you prioritise all aspects of CSAM (Child Sexual Abuse Material) reports, so that you can focus on identifying perpetrators and saving victims. By combining visual intelligence to help prioritize reports with online sources for additional information, AviaTor reduces the time spent by law enforcement agencies processing CSAM reports. This makes the processing not only quicker, but also more efficient and complete. | National | Netherlands | NL | National Police, Ziuz | Central-Government | Public order and safety | Police Services | Implemented | 2.021 | 2023 | Enforcement | Supporting inspection processes | No | No | Artificial Intelligence | G2G | x | x | x | Hoekstra, M., Chideock, C., & Veenstra, A.F. van (2021). Quik Scan AI in de Publieke Dienstverlening II - Longlist Initiatieven. TNO: Den Haag. | Learning | Machine learning | Searching | Planning and Scheduling | 20/11/2023 | |||||||||||||||||
| PSTW-360 | Pilot Youth Policy Rotterdam - Influencing factors socio-emotional development of young people | https://www.tno.nl/nl/aandachtsgebieden/strategische-analyses-beleid/expertisegroepen/strategy-policy/het-policy-lab-datagedreven-beleidsontwikkeling/ | By linking datasets and using a combination of statistical methods and machine learning, we explore which factors determine the socio-emotional development of young people. | Local | Netherlands | NL | Municipality of Rotterdam, TNO and BZK | Local Government | Social protection | Social protection n.e.c. | Pilot | 2.019 | Analysis, monitoring and regulatory research | Prediction and planning | No | No | Artificial Intelligence | G2C | x | x | x | x | x | Hoekstra, M., Chideock, C., & Veenstra, A.F. van (2021). Quik Scan AI in de Publieke Dienstverlening II - Longlist Initiatieven. TNO: Den Haag. | Planning | Planning and Scheduling | Machine learning | 20/11/2023 | |||||||||||||||||
| PSTW-363 | Rain radar Rijnmond - Prediction of rain to prevent flooding and damage | http://urbanbigdata.nl/big-data/voorbeelden/21/big-data-in-rotterdam https://www.rotterdam.nl/wonen-leven/regenradar/ | The Rijnmond rain radar measures and predicts precipitation in the region very locally. This helps prevent flooding and damage. | Local | Netherlands | NL | Municipality of Rotterdam, TUDelft | Local Government | Defence | Civil defence. | Pilot | 2.021 | Analysis, monitoring and regulatory research | Prediction and planning | No | No | Artificial Intelligence | G2C | x | x | x | x | Hoekstra, M., Chideock, C., & Veenstra, A.F. van (2021). Quik Scan AI in de Publieke Dienstverlening II - Longlist Initiatieven. TNO: Den Haag. | Planning | Planning and Scheduling | Automated reasoning | 20/11/2023 | ||||||||||||||||||
| PSTW-364 | Remote sensing for monitoring nature reserves on the Frisian Wadden Islands | https://www.mdpi.com/2072-4292/10/7/1085/htm | The aim of this project was to test the feasibility of models that monitor vegetation with annual frequency based on satellite data. These models are optimized by means of machine learning techniques. | Local | Netherlands | NL | Province of Friesland, Ilionix | Local Government | Environmental Protection | Environmental protection n.e.c. | Pilot | 2.018 | Analysis, monitoring and regulatory research | Information analysis processes | No | No | Artificial Intelligence | G2G | x | x | x | Hoekstra, M., Chideock, C., & Veenstra, A.F. van (2021). Quik Scan AI in de Publieke Dienstverlening II - Longlist Initiatieven. TNO: Den Haag. | Perception | Computer vision | Machine learning | 20/11/2023 | |||||||||||||||||||
| PSTW-365 | Rijkswaterstaat vital assets - Predictive maintenance on bridges | https://unece.org/sites/default/files/2022-06/ECE-TRANS-SC3-WP3-2022-inf_10e.pdf | Using data to predict when maintenance should be carried out on bridges. | National | Netherlands | NL | Ministry of Infrastructure and Water Management | Central-Government | Economic Affairs | Transport | In development | 2.020 | Analysis, monitoring and regulatory research | Prediction and planning | No | No | Artificial Intelligence | G2G | x | x | Hoekstra, M., Chideock, C., & Veenstra, A.F. van (2021). Quik Scan AI in de Publieke Dienstverlening II - Longlist Initiatieven. TNO: Den Haag. | Learning | Machine learning | Planning and Scheduling | 20/11/2023 | ||||||||||||||||||||
| PSTW-367 | Sia - Online notification system of the municipality of Amsterdam | https://algoritmeregister.amsterdam.nl/meldingen-openbare-ruimte/ | SIA is an online notification system of the municipality of Amsterdam. Reports can be made in the following situations: If something needs to be made or cleaned up on the street or in a park, in case of a dangerous traffic situation or nuisance of persons and restaurants. | Local | Netherlands | NL | Municipality of Amsterdam | Local Government | Environmental Protection | Waste management. | Implemented | 2.020 | Public services and engagement | Service personalisation (various) | No | No | Artificial Intelligence | G2C | x | x | x | x | Hoekstra, M., Chideock, C., & Veenstra, A.F. van (2021). Quik Scan AI in de Publieke Dienstverlening II - Longlist Initiatieven. TNO: Den Haag. | Communication | Natural language processing | Automated reasoning | 20/11/2023 | ||||||||||||||||||
| PSTW-368 | Smart Cameras - Analyzing road situations | https://www.verkeersnet.nl/smart-mobility/22251/rijkswaterstaat-test-slimme-cameras-om-spitsstroken-automatisch-te-kunnen-openen/ | Smart cameras that can 'read' the situation on the road, making opening and closing rush-hour lanes faster, easier and safer. | National | Netherlands | NL | Rijkswaterstaat, Innovation Centre and ViNotion | Central-Government | Economic Affairs | Transport | Pilot | 2.017 | Enforcement | Smart Recognition processes | No | No | Artificial Intelligence | G2G | x | x | x | Hoekstra, M., Chideock, C., & Veenstra, A.F. van (2021). Quik Scan AI in de Publieke Dienstverlening II - Longlist Initiatieven. TNO: Den Haag. | Perception | Computer vision | Machine learning | 20/11/2023 | |||||||||||||||||||
| PSTW-369 | Smart enforcement cameras - Enforcement of drivers driving through red road crosses | https://www.rijkswaterstaat.nl/nieuws/2019/05/proef-handhaving-negeren-rood-kruis-met-slimme-camera.aspx | In order to detect road users who ignore red crosses, and to reduce the number of violations, the Public Prosecutor's Office and Rijkswaterstaat have started a trial with enforcement using smart cameras along the A28 motorway near Amersfoort. | National | Netherlands | NL | Public Prosecutor's Office and Rijkswaterstaat | Central-Government | Public order and safety | Police Services | Implemented | 2.019 | Enforcement | Smart Recognition processes | No | No | Artificial Intelligence | G2G | x | x | x | Hoekstra, M., Chideock, C., & Veenstra, A.F. van (2021). Quik Scan AI in de Publieke Dienstverlening II - Longlist Initiatieven. TNO: Den Haag. | Perception | Computer vision | Machine learning | 20/11/2023 | |||||||||||||||||||
| PSTW-370 | Smart decision aid - Determining if a case is a scam or not | https://www.politie.nl/nieuws/2019/september/26/sneller-duidelijkheid-bij-aangifte-internetoplichting.html | The National Internet Reporting Centre receives 42,000 reports of buying and selling fraud every year. In about 10,000 cases, after studying a police officer, it turns out that this is not a criminal offence. The 'smart decision aid' helps determine whether this is a scam and links this directly back to the declarant. The decision aid also offers an action perspective if it turns out that they have not been scammed. | National | Netherlands | NL | National Police Lab Artificial Intelligence | Central-Government | Public order and safety | Police Services | In development | 2.019 | Enforcement | Supporting inspection processes | No | No | Artificial Intelligence | G2G | x | x | Hoekstra, M., Chideock, C., & Veenstra, A.F. van (2021). Quik Scan AI in de Publieke Dienstverlening II - Longlist Initiatieven. TNO: Den Haag. | Reasoning | Automated reasoning | Knowledge representation | 20/11/2023 | ||||||||||||||||||||
| PSTW-371 | Smart lampposts for combating burglaries - Detection of suspicious movements and audio | https://nos.nl/nieuwsuur/artikel/2355542-hoe-algoritmes-de-stad-besturen.html https://www.youtube.com/watch?v=gJDA4t6lIgY&feature=youtu.be | The Municipality of Rotterdam has installed smart lampposts in the Lombardijen district to combat burglaries. Sensors record suspicious movements and microphones hear if a window is being tapped. | Local | Netherlands | NL | Municipality of Rotterdam | Local Government | Public order and safety | Police Services | Pilot | 2.020 | Enforcement | Smart Recognition processes | No | No | Artificial Intelligence | G2G | x | x | x | Hoekstra, M., Chideock, C., & Veenstra, A.F. van (2021). Quik Scan AI in de Publieke Dienstverlening II - Longlist Initiatieven. TNO: Den Haag. | Perception | Audio processing | Machine learning | 20/11/2023 | |||||||||||||||||||
| PSTW-372 | Smart sensor waste containers | https://www.rijnmond.nl/nieuws/183535/Afvalcontainers-vergeten-te-melden-dat-ze-vol-zitten | Sensors are installed in waste containers to measure how full the bins are. The 'filling degree meter' transmits the position every hour. This information is used to look at when the container can best be emptied. Drivers can see on a tablet which route to take next. The system prevents waste from accumulating next to an overcrowded container, while at the same time saving the garbage men from rides to empty bins. | Local | Netherlands | NL | Municipality of Rotterdam | Local Government | Economic Affairs | Transport | Pilot | 2.021 | Internal management | Internal primary processes | No | No | Artificial Intelligence | G2G | x | x | x | x | Hoekstra, M., Chideock, C., & Veenstra, A.F. van (2021). Quik Scan AI in de Publieke Dienstverlening II - Longlist Initiatieven. TNO: Den Haag. | Perception | Computer vision | Planning and Scheduling | 20/11/2023 | ||||||||||||||||||
| PSTW-375 | Enforcement of social policy laws with AI | https://zoek.officielebekendmakingen.nl/blg-814167.pdf | AI to monitor the enforcement of the social security laws checking for fraud. | National | Netherlands | NL | UWV, SVB, the Tax And Customs Administration, DUO, Justid, CJIB and RDW | Central-Government | General public services | Executive and legislative organs, financial and fiscal affairs, external affairs. | Pilot | 2.017 | Analysis, monitoring and regulatory research | Prediction and planning | No | No | Artificial Intelligence | G2G | x | x | x | Hoekstra, M., Chideock, C., & Veenstra, A.F. van (2021). Quik Scan AI in de Publieke Dienstverlening II - Longlist Initiatieven. TNO: Den Haag. | Planning | Planning and Scheduling | Automated reasoning | 20/11/2023 | |||||||||||||||||||
| PSTW-376 | Speaker Tracking in Time and Space | https://www.rvo.nl/subsidie-en-financieringswijzer/sbir/sbir-oproep-artifici%C3%ABle-intelligentie-voor-de-publieke-diensten/publieke-samenvattingen | Spraaklab develops AI technology that can mostly disassemble and label the speech of the different speakers. This is useful for the police, for example, when analyzing audio recordings. This allows the police to work more efficiently and with higher quality, while different conversations than those of the subject do not need to be listened to as often. This ensures the privacy of citizens better. | National | Netherlands | NL | Dutch Police, with Speech lab B.V. | Central-Government | Public order and safety | Police Services | Pilot | 2.021 | Enforcement | Smart Recognition processes | No | No | Artificial Intelligence | G2G | x | x | x | Hoekstra, M., Chideock, C., & Veenstra, A.F. van (2021). Quik Scan AI in de Publieke Dienstverlening II - Longlist Initiatieven. TNO: Den Haag. | Perception | Audio processing | Machine learning | 20/11/2023 | |||||||||||||||||||
| PSTW-377 | Road safety model The Hague - Providing a risk score for all road sections and intersections | https://www.digitaleoverheid.nl/overzicht-van-alle-onderwerpen/nieuwe-technologieen-data-en-ethiek/het-led/toolbox/aan-de-slag-datagedreven-werken-in-de-praktijk/ | The model determines a risk score for all road sections and intersections in The Hague by means of machine learning and historical accidents. Recorded accidents are compared to a large dataset that describes the traffic situation at each intersection and road section by means of 250 characteristics. The model helps traffic experts identify unsafe traffic situations. | Local | Netherlands | NL | Municipality of The Hague | Local Government | Public order and safety | Public order and safety n.e.c. | In development | 2.020 | Analysis, monitoring and regulatory research | Prediction and planning | No | No | Artificial Intelligence | G2G | x | x | x | Hoekstra, M., Chideock, C., & Veenstra, A.F. van (2021). Quik Scan AI in de Publieke Dienstverlening II - Longlist Initiatieven. TNO: Den Haag. | Planning | Planning and Scheduling | Machine learning | 20/11/2023 | |||||||||||||||||||
| PSTW-378 | Road safety model Rotterdam - Predictive model for road accidents | https://www.kennisnetwerkspv.nl/Meetinstrumenten/Overige-meetinstrumenten/Verkeersveiligheidsmodel-machine-learning | In the Road Safety Model, data on historical accidents is linked to data about the road, traffic and the environment within the sphere of influence of the (accident) location. By using machine learning, a model with a predictive character is created. | Local | Netherlands | NL | Municipality of Rotterdam, Welance.io, | Local Government | Public order and safety | Public order and safety n.e.c. | In development | 2.020 | Analysis, monitoring and regulatory research | Prediction and planning | No | No | Artificial Intelligence | G2G | x | x | x | Hoekstra, M., Chideock, C., & Veenstra, A.F. van (2021). Quik Scan AI in de Publieke Dienstverlening II - Longlist Initiatieven. TNO: Den Haag. | Planning | Planning and Scheduling | Machine learning | 20/11/2023 | |||||||||||||||||||
| PSTW-38 | OuluBot - Virtual assistant for business | https://www.ouka.fi/oulu/oulubot/english | The City of Oulu has started a project co-financed by Business Finland, which aims to build a chatbot service, OuluBot. The goal for OuluBot is to become a virtual assistant in all everyday issues, whether they concern tourism, companies or city services. The answer or guidance to an electronic service should be provided regardless of time, place, medium and language. Technically, chatbot retrieves information e.g. relevant City of Oulu websites, chat history, guidance information, databases, and other information sources. OuluBot is available 24/7 service. independent of working hours. If the user is looking for information that OuluBot would not be able to answer, then during office hours the discussion could be directed to the City of Oulu chat service (Oulu10 general counseling customer service). | Local | Finland | FI | Municipality of Oulu | Local Government | General public services | Executive and legislative organs, financial and fiscal affairs, external affairs. | Implemented | 2.020 | Public services and engagement | Service personalisation (various) | No | No | Artificial Intelligence | G2C | x | x | x | x | https://www.ouka.fi/oulu/oulubot/ | Communication | Natural language processing | Searching | chatbot | 17/10/2023 | |||||||||||||||||
| PSTW-380 | Reference Index Recherche Onderzoeken en Subjecten - Detection of unusual transactions | https://wetten.overheid.nl/BWBR0041193/2018-07-25 | Unusual transactions are compared by means of a partly automated process with the Referral Index Recherche Onderzoeken en Subjecten (VROS), a file managed by the National Police. Positive matches led to a suspicion of the unusual transactions in question. It is clear in these cases that the transaction in question is linked to an investigation. | National | Netherlands | NL | Financial Intelligence Unit Netherlands (FIU-Netherlands) | Central-Government | Public order and safety | Police Services | In development | 2.018 | Enforcement | Supporting inspection processes | No | No | Artificial Intelligence | G2G | x | x | Hoekstra, M., Chideock, C., & Veenstra, A.F. van (2021). Quik Scan AI in de Publieke Dienstverlening II - Longlist Initiatieven. TNO: Den Haag. | Planning | Planning and Scheduling | Automated reasoning | 20/11/2023 | ||||||||||||||||||||
| PSTW-382 | Predict which residents have a higher risk of care or debt problems in Twenterand (SyRI) | https://nos.nl/artikel/2366864-fraude-opsporen-of-gevaar-van-discriminatie-gemeenten-gebruiken-slimme-algoritmes.html | At least 25 municipalities use predictive systems and algorithms to, for example, detect welfare fraud, predict where potentially subversive crime takes place and to be able to help citizens with debts in time. Risk profiling is under a magnifying glass. In the childcare allowance affair, dual nationality appeared to be taken into account when drawing up risk profiles. Last year, the judge also dismissed the SyRI profiling system, partly because it was insufficiently transparent and therefore there was a risk of discrimination. | Local | Netherlands | NL | Municipality of Twenterand | Local Government | Social protection | Social protection n.e.c. | In development | 2.021 | Analysis, monitoring and regulatory research | Prediction and planning | No | No | Artificial Intelligence | G2G | x | x | Hoekstra, M., Chideock, C., & Veenstra, A.F. van (2021). Quik Scan AI in de Publieke Dienstverlening II - Longlist Initiatieven. TNO: Den Haag. | Planning | Planning and Scheduling | Automated reasoning | 20/11/2023 | ||||||||||||||||||||
| PSTW-383 | Early school leavers in the municipality of Amersfoort - Estimation of students at risk | https://nos.nl/artikel/2286848-overheid-gebruikt-op-grote-schaal-voorspellende-algoritmes-risico-op-discriminatie.html | The municipality of Amersfoort and Dordrecht use an algorithm to estimate which students are at risk of becoming early school leavers. | Local | Netherlands | NL | Municipality of Amersfoort and Dordrecht | Local Government | Education | Education n.e.c. | In development | 2.019 | Analysis, monitoring and regulatory research | Information analysis processes | No | No | Artificial Intelligence | G2G | x | x | x | Hoekstra, M., Chideock, C., & Veenstra, A.F. van (2021). Quik Scan AI in de Publieke Dienstverlening II - Longlist Initiatieven. TNO: Den Haag. | Planning | Planning and Scheduling | Automated reasoning | 20/11/2023 | |||||||||||||||||||
| PSTW-384 | Wabo assistant - Automated environmental permits | Wabo Service Counter (online service): https://www.omgevingsloket.nl/ Wabo policy and process: https://rwsenvironment.eu/subjects/general-provisions-0/ | The Environmental Law General Provisions Act (Wabo) regulates the environmental permit. The municipality of The Hague needs a more efficient intake of the Wabo permits. The municipality wants to automate some of the tasks and make them more efficient through AI. The type of AI used is NLP. | Local | Netherlands | NL | Municipality of The Hague | Local Government | Environmental Protection | Environmental protection n.e.c. | Pilot | 2.020 | Public services and engagement | Service integration (various) | No | No | Artificial Intelligence | G2C | x | x | x | Hoekstra, M., Chideock, C., & Veenstra, A.F. van (2021). Quik Scan AI in de Publieke Dienstverlening II - Longlist Initiatieven. TNO: Den Haag. | Communication | Natural language processing | Automated reasoning | text analysis | 20/11/2023 | ||||||||||||||||||
| PSTW-385 | Water fields - purification system for rainwater | https://www.technologyrecord.com/Article/city-of-breda-optimises-water-use-with-the-internet-of-things-45082 | The water fields are a purification system for rainwater. Rainwater from the district is collected, buffered and purified by a number of natural filters. Data on the operation of the system and on the amount of rainwater are used to optimize the operation and predict the supply of rainwater. | Local | Netherlands | NL | Municipality of Breda and I-SAGO | Local Government | Environmental Protection | Waste water management. | In development | 2.015 | Analysis, monitoring and regulatory research | Monitoring policy implementation | No | No | Artificial Intelligence | G2G | x | x | x | Hoekstra, M., Chideock, C., & Veenstra, A.F. van (2021). Quik Scan AI in de Publieke Dienstverlening II - Longlist Initiatieven. TNO: Den Haag. | Planning | Planning and Scheduling | Automated reasoning | 20/11/2023 | |||||||||||||||||||
| PSTW-387 | WIL Leak Current - Discover abuse and improper use of benefits | https://nos.nl/artikel/2286848-overheid-gebruikt-op-grote-schaal-voorspellende-algoritmes-risico-op-discriminatie.html | WIL Lekstroom is a collaboration between the municipality of Houten, Ijsselstein, Lopik, Nieuwegein and Vijfheerenland and uses algorithms to discover abuse and improper use of benefits. | Local | Netherlands | NL | Municipality of Houten, Ijsselstein, Lopik, Nieuwegein and Vijfheerenland | Local Government | Social protection | Social protection n.e.c. | In development | 2.019 | Adjudication | Taking decisions on benefits | No | No | Artificial Intelligence | G2G | x | x | x | x | x | x | Hoekstra, M., Chideock, C., & Veenstra, A.F. van (2021). Quik Scan AI in de Publieke Dienstverlening II - Longlist Initiatieven. TNO: Den Haag. | Planning | Planning and Scheduling | Machine learning | 20/11/2023 | ||||||||||||||||
| PSTW-389 | W(e). Service.Heerlen (WESH) | https://www.brightlands.com/brightlands-smart-services-campus/subsidieprogramma-wesh | App for citizens, aimed at promoting citizen participation in the maintenance of the public environment. The app allows citizens to take on maintenance jobs. Once they have successfully completed this job, they will receive a financial reward that can be used by local SMEs. | Local | Netherlands | NL | Municipality of Heerlen, CBS, VNG, CoTown, Heerlen Mijn Stad, Brightlands | Local Government | General public services | General services. | Pilot | 2.018 | Public services and engagement | Engagement management | No | No | Artificial Intelligence | G2C | x | x | Hoekstra, M., Chideock, C., & Veenstra, A.F. van (2021). Quik Scan AI in de Publieke Dienstverlening II - Longlist Initiatieven. TNO: Den Haag. | Planning | Planning and Scheduling | Machine learning | 20/11/2023 | ||||||||||||||||||||
| PSTW-390 | Poverty prevention - Identification of poverty and debt early | https://www.brightlands.com/brightlands-smart-services-campus/brightlands-techruption-use-case | Digital solution to identify poverty and debt early and preventively by drawing conclusions from the data of different agencies without violating the privacy of the citizen (e..b g. multi-party computation). | Local | Netherlands | NL | Brightlands Techruption, CBS, municipality of Heerlen, CZ, Maastricht University, TNO | Local Government | Social protection | Social protection n.e.c. | Pilot | 2.018 | Analysis, monitoring and regulatory research | Information analysis processes | No | No | Artificial Intelligence | G2G | x | x | x | Hoekstra, M., Chideock, C., & Veenstra, A.F. van (2021). Quik Scan AI in de Publieke Dienstverlening II - Longlist Initiatieven. TNO: Den Haag. | Planning | Planning and Scheduling | Automated reasoning | 20/11/2023 | |||||||||||||||||||
| PSTW-391 | INZNAK Project - Intelligent road signs for adaptive vehicle traffic control | https://ieeexplore.ieee.org/document/8883382 | In response to the desire to improve road safety and vehicle traffic, the INZNAK project was proposed. This project aims to improve road traffic by developing and building a network of autonomous road signs. The use of intelligent road signs in road traffic will prevent the most common collisions on highways, resulting from speed not being adapted to weather conditions, the condition of the surface and damming? vehicles in the event of a need to brake suddenly. During the project, 3 types of signs will be developed: standing, hanging and mobile. Each sign will have a display that will present hints for drivers along with a suggested speed. Hints will be displayed in the form of text and image messages, which will warn or inform about current traffic disruptions. Thanks to the use of a string of signs placed along the road, drivers will be warned much faster about possible dangers on the road. This is due to the fact that each of the signs will communicate with the others, making it easier to manage traffic. The signs will communicate in LoraWan and LTE technology. LoraWan technology will enable the characters to communicate with each other. And LTE technology will be used to send and receive messages from the traffic control center. The use of two-level communication allows the solution to become independent from possible failures of the telecommunications infrastructure. To ensure the flow of up-to-date information to autonomous signs, it is necessary to equip them with a number of sensors, which will analyze the traffic in the vicinity of the sign on an ongoing basis. The experimental installations of intelligent signs will be equipped with sensors analyzing road traffic, such as: Doppler radar, lidar, acoustic probe, RGB camera, Bluetooth receiver. Due to the fact that changing weather conditions, such as: storms, blizzards, fog, black ice, are also a big risk on the road. A weather station will be installed in each sign, analyzing the current weather conditions around the sign. As a result, the resolution of weather measurements will be very high. The proposed approach to traffic analysis is based on the principles of multimodality, thanks to which it is possible to supplement each of the individual methods with a different one in a place where it better serves its purpose. Such a case can be observed e.g. at night, where standard vision cameras mainly capture car lights. The use of a lidar device in such conditions allows for proper detection of most vehicles. In the next chapter, individual modalities used in the conducted research will be presented. | Local | Poland | PL | Gdansk | Local Government | Economic Affairs | Transport | Pilot | 2.019 | Analysis, monitoring and regulatory research | Monitoring policy implementation | No | No | Artificial Intelligence | G2C | x | x | x | x | https://www.gov.pl/web/cyfryzacja/mapa-innowacji | Learning | Machine learning | Computer vision | 20/11/2023 | ||||||||||||||||||
| PSTW-392 | Virtual Clerk - Assistance with search for information | https://www.gov.pl/web/cyfryzacja/mapa-innowacji | "Virtual Clerk" is a system used to optimize the processes of servicing hundreds of thousands of beneficiaries. A modern and innovative tool that uses Artificial Intelligence, allowing you to intuitively search for information on the operation of the office and the procedures carried out by it. An important benefit offered by WU is the ease and speed in reaching the information sought and the availability of the service 24 hours a day, 7 days a week. | Local | Poland | PL | Municipality of Chorzow | Local Government | General public services | General public services n.e.c. | Implemented | 2.020 | Public services and engagement | Service personalisation (various) | No | No | Artificial Intelligence | G2C | x | x | https://www.gov.pl/web/cyfryzacja/mapa-innowacji | Communication | Natural language processing | Searching | 20/11/2023 | ||||||||||||||||||||
| PSTW-393 | Intelligent Management Systems | https://www.gov.pl/web/cyfryzacja/mapa-innowacji | The project consisted in the implementation of intelligent management systems in the buildings of the County Office, e.g. access control, external roller shutters, monitoring, management of water and electricity consumption, PIAPY, IT network, intelligent conference room, fire protection system. | Local | Poland | PL | Municipality of Płońsk | Local Government | General public services | General public services n.e.c. | Implemented | 2.020 | Internal management | Internal support processes | No | No | Artificial Intelligence | G2G | x | x | https://www.gov.pl/web/cyfryzacja/mapa-innowacji | Learning | Machine learning | Planning and Scheduling | 20/11/2023 | ||||||||||||||||||||
| PSTW-395 | Monitoring of a Water Treatment Station | https://www.gov.pl/web/cyfryzacja/mapa-innowacji | Monitoring of the Water Treatment Plant in Kartuzy includes: measurements of the flow rate, pressure in the network, control and regulation of the intake operation. Control of the amount of water sent to the water supply network. Balance of the volume of water distributed in the network, e.g. water losses | Local | Poland | PL | Municipality of Kartuzy | Local Government | Housing and community amenities | Water supply. | Implemented | 2.020 | Internal management | Internal support processes | No | No | Artificial Intelligence | G2G | x | x | https://www.gov.pl/web/cyfryzacja/mapa-innowacji | Learning | Machine learning | Optimisation | 20/11/2023 | ||||||||||||||||||||
| PSTW-396 | Intelligent water and sewage network management system | https://www.gov.pl/web/cyfryzacja/mapa-innowacji | The project involves the construction of an analytical system including hydraulic calculations, devices for the ongoing monitoring of network parameters and information about recipients. It is in line with the global trend of building smart grids, the aim of which is to optimize the operation of the network and its maintenance costs through the use of dynamic (on-line) information about the network load and optimization of used resources. | Local | Poland | PL | Municipality of Zywiec | Local Government | Housing and community amenities | Water supply. | In development | 2.020 | Internal management | Internal primary processes | No | No | Artificial Intelligence | G2G | x | x | https://www.gov.pl/web/cyfryzacja/mapa-innowacji | Learning | Machine learning | Optimisation | 20/11/2023 | ||||||||||||||||||||
| PSTW-397 | Lupine Intelligent lighting system | https://www.gov.pl/web/cyfryzacja/mapa-innowacji | Introduction of central control in street lighting based on motion sensors and sensors that analyze weather conditions. Currently, each lamp is individually controlled and monitored. This allows you to achieve significant savings and set different times for switching the lighting on and off. In addition, lamps near pedestrian crossings turn on earlier and then turn off in relation to the others, which increases the lighting and thus safety at pedestrian crossings. Full preview and the ability to monitor lighting parameters also allows to reduce the response time to failures. This, in turn, ensures minimal interruptions in lighting operation. The possibility of monitoring the parameters of the luminaires also enables earlier planning of maintenance works and minimizing their costs. | Local | Poland | PL | Municipality of Lupine | Local Government | Housing and community amenities | Street lighting. | Implemented | 2.020 | Internal management | Internal primary processes | No | No | Artificial Intelligence | G2G | x | x | x | x | https://www.gov.pl/web/cyfryzacja/mapa-innowacji | Learning | Machine learning | Optimisation | 20/11/2023 | ||||||||||||||||||
| PSTW-398 | Development of the Electronic Flood Warning System | https://www.gov.pl/web/cyfryzacja/mapa-innowacji | The project consists in the expansion of the Electronic Flood Warning System in the Biała Tarnowska River catchment area. The purpose of the system is to generate flood risk forecasts. The system is to determine when, where and with what intensity a flood risk is possible. One of the essential elements of the system is the introduction of Artificial Intelligence and machine learning mechanisms. Algorithms will be developed to analyze the relationship between the intensity of historical and on-line precipitation and the change in the water level (flood wave) on the river or the occurrence of the so-called flash flood. | Local | Poland | PL | Municipality of Tarnow | Local Government | Public order and safety | Public order and safety n.e.c. | In development | 2.020 | Analysis, monitoring and regulatory research | Prediction and planning | No | No | Artificial Intelligence | G2C | x | x | https://www.gov.pl/web/cyfryzacja/mapa-innowacji | Planning | Planning and Scheduling | Machine learning | 20/11/2023 | ||||||||||||||||||||
| PSTW-399 | Poland Integrated Public Transport Management System (ITS) – Gliwice, Poznań, Wrocław | https://www.gov.pl/web/cyfryzacja/mapa-innowacji | An AI-powered Integrated Transport System (ITS) deployed across Polish cities including Gliwice and Poznań. The system optimises urban mobility through green light priority for public transport and emergency vehicles, real-time road information for drivers via variable message signs and a mobile app, video analytics at intersections for automatic incident detection, intelligent parking space identification, electric bus flow optimisation, a meteorological monitoring system, and pre-selection vehicle weighing at city entry points. | Local | Poland | PL | Municipalities of Gliwice & Poznan | Local Government | Public order and safety | Police Services | Implemented | 2.020 | Internal management | Internal primary processes | No | No | Artificial Intelligence | G2C | x | x | https://www.gov.pl/web/cyfryzacja/mapa-innowacji | Reasoning | Automated reasoning | Computer vision | 20/11/2023 | ||||||||||||||||||||
| PSTW-400 | Cracow Virtual Clerk | https://www.gov.pl/web/cyfryzacja/mapa-innowacji | A pioneering solution has been launched on the new POP website - a virtual clerk. It is an innovative tool that uses Artificial Intelligence, allowing you to intuitively search for information in the field of entrepreneur service, including setting up your own business. An important advantage offered by a virtual officer is the ease and speed in reaching the information sought and the availability of the service 24 hours a day, seven days a week. | Local | Poland | PL | Municipality of Cracow | Local Government | General public services | General public services n.e.c. | Pilot | 2.020 | Public services and engagement | Service personalisation (various) | No | No | Artificial Intelligence | G2C | x | x | x | https://www.gov.pl/web/cyfryzacja/mapa-innowacji | Communication | Natural language processing | Machine learning | Searching | chatbot | 20/11/2023 | |||||||||||||||||
| PSTW-401 | AI-based timetables | https://www.gov.pl/web/cyfryzacja/mapa-innowacji | Provision of software for creating timetables, which takes into account historical data obtained from vehicles on the completed timetable. The software enables the projection of historical data from the completed trips on the timetable and the determination of the optimal travel time on a given section on the basis of statistical analysis, ensuring maximum punctuality. | Local | Poland | PL | Municipality of Poznan | Local Government | Economic Affairs | Transport | Implemented | 2.020 | Internal management | Internal primary processes | No | No | Artificial Intelligence | G2G | x | x | https://www.gov.pl/web/cyfryzacja/mapa-innowacji | Planning | Planning and Scheduling | Optimisation | 20/11/2023 | ||||||||||||||||||||
| PSTW-402 | Poznan: Improving the flow of electric bus traffic | https://www.gov.pl/web/cyfryzacja/mapa-innowacji | In connection with the planned introduction in the fourth quarter of 2019 of electric buses on the route No. 174, traffic lights on the route of this line are equipped with signal receivers from buses, and traffic light programs are adjusted to prioritize buses. The aim is to obtain the maximum smoothness of bus traffic in order to ensure the longest possible vehicle charging time in the end loop. | Local | Poland | PL | Municipality of Poznan | Local Government | Economic Affairs | Transport | Pilot | 2.020 | Internal management | Internal primary processes | No | No | Artificial Intelligence | G2G | x | x | https://www.gov.pl/web/cyfryzacja/mapa-innowacji | Reasoning | Automated reasoning | Connected and Automated vehicles | 20/11/2023 | ||||||||||||||||||||
| PSTW-403 | Ioom Intelligent lighting system | https://www.gov.pl/web/cyfryzacja/mapa-innowacji | Introduction of central control in street lighting based on motion sensors and sensors that analyze weather conditions. Currently, each lamp is individually controlled and monitored. This allows you to achieve significant savings and set different times for switching the lighting on and off. In addition, lamps near pedestrian crossings turn on earlier and then turn off in relation to the others, which increases the lighting and thus safety at pedestrian crossings. Full preview and the ability to monitor lighting parameters also allows to reduce the response time to failures. This, in turn, ensures minimal interruptions in lighting operation. The possibility of monitoring the parameters of the luminaires also enables earlier planning of maintenance works and minimizing their costs. | Local | Poland | PL | Digitization of KPRM | Central-Government | Housing and community amenities | Street lighting. | Implemented | 2.020 | Analysis, monitoring and regulatory research | Prediction and planning | No | No | Artificial Intelligence | G2C | x | x | https://www.gov.pl/web/cyfryzacja/mapa-innowacji | Reasoning | Automated reasoning | Optimisation | 20/11/2023 | ||||||||||||||||||||
| PSTW-404 | Smart lighting in urban space | https://www.gov.pl/web/cyfryzacja/mapa-innowacji | The lighting installed in the WUWA 2 estate uses a remote control system and LED technology, thus helping to reduce the costs of electricity consumption. It senses changes in traffic and adjusts the lighting intensity, which improves the safety of all residents. Permanent power supply for street lighting circuits allows the use of lighting infrastructure to offer residents additional functionalities, such as charging electric vehicles or providing the Internet. | Local | Poland | PL | Municipality of Wroclaw | Local Government | Housing and community amenities | Street lighting. | Implemented | 2.020 | Public services and engagement | Service personalisation (various) | No | No | Artificial Intelligence | G2C | x | x | https://www.gov.pl/web/cyfryzacja/mapa-innowacji | Reasoning | Automated reasoning | Planning and Scheduling | 20/11/2023 | ||||||||||||||||||||
| PSTW-405 | Wroclaw Intelligent lighting system | https://www.gov.pl/web/cyfryzacja/mapa-innowacji | A research project aimed at developing a combination of the basic function of lighting poles with new functions aimed at residents. As part of the available infrastructure, devices for counting pedestrians, cyclists and vehicles (along with the specification of the vehicle type) were installed. The lighting was replaced with LED with the function of adjusting the light intensity to external conditions. | Local | Poland | PL | Municipality of Wroclaw | Local Government | Housing and community amenities | Street lighting. | Implemented | 2.020 | Public services and engagement | Service integration (various) | No | No | Artificial Intelligence | G2C | x | x | https://www.gov.pl/web/cyfryzacja/mapa-innowacji | Reasoning | Automated reasoning | Optimisation | 20/11/2023 | ||||||||||||||||||||
| PSTW-406 | Wroclaw Intelligent parking system | https://www.gov.pl/web/cyfryzacja/mapa-innowacji | A research project aimed at developing a prototype system collecting data from various sources, such as sensors and cameras, on the basis of which it is possible to provide the resident with information about the chances of finding a free parking space in the area he is heading to. The solution is aimed mainly at recognizing how many free and occupied parking spaces are left in a given street space. As part of the project, a mobile application will be created that will determine the travel time to the car park and the availability of parking spaces. | Local | Poland | PL | Municipality of Wroclaw | Local Government | Housing and community amenities | Housing and community amenities n.e.c. | Implemented | 2.020 | Public services and engagement | Service integration (various) | No | No | Artificial Intelligence | G2C | x | x | https://www.gov.pl/web/cyfryzacja/mapa-innowacji | Planning | Planning and Scheduling | Computer vision | 20/11/2023 | ||||||||||||||||||||
| PSTW-407 | Resident's Virtual Advisor | https://www.gov.pl/web/cyfryzacja/mapa-innowacji | The Virtual Resident Advisor is an innovative software used by thousands of customers, including administration, to optimize customer service processes. Its main task is to improve the search for necessary information on the pages of the Public Information Bulletin in Wrocław. The Virtual Resident Advisor is a chat-based dialogue system that simulates a conversation with a real person, leading the user on the BIP side to the right answer. The offered solution belongs to the group of the so-called intelligence customer interaction solutions and uses the integration of sound and video with Artificial Intelligence mechanisms. The Virtual Resident Advisor is available at www.bip.um.wroc.pl | Local | Poland | PL | Municipality of Wroclaw | Local Government | General public services | Executive and legislative organs, financial and fiscal affairs, external affairs. | Implemented | 2.020 | Public services and engagement | Service personalisation (various) | No | No | Artificial Intelligence | G2C | x | x | x | https://www.gov.pl/web/cyfryzacja/mapa-innowacji | Communication | Natural language processing | Audio processing | chatbot | 20/11/2023 | ||||||||||||||||||
| PSTW-408 | Katowice Intelligent Monitoring and Analysis System (KISMiA) | https://www.gov.pl/web/cyfryzacja/mapa-innowacji | Katowice Intelligent Monitoring and Analysis System (KISMiA) is built with the use of three components: Video materials management system (VMS), Video Analytics Component and Operational Support Component. The video management system is used to manage and administer the video data supplied to the system. The Video Analytics component, based on the IBM Intelligent Video Analytics (IVA) platform, continuously analyzes video streams and generates information describing the images from each camera. The Operational Support Component (IBM) is designed to oversee and coordinate operations, and provide the right people with the right information to help them make the right decisions and track their results. The main component of the KISMiA system is the IOC platform. It is a gathering point for all elements of the system and enables coordination of activities of supported services with other integrated systems (IVA, VMS). Currently, there are 260 cameras in the KISMiA system. | Local | Poland | PL | Municipality of Katowice | Local Government | Public order and safety | Public order and safety n.e.c. | Implemented | 2.020 | Enforcement | Smart Recognition processes | No | No | Artificial Intelligence | G2G | x | x | x | https://www.gov.pl/web/cyfryzacja/mapa-innowacji | Perception | Computer vision | Machine learning | 20/11/2023 | |||||||||||||||||||
| PSTW-41 | French Fraud - Fraud detection value declarations | https://www.aiforhumanity.fr/pdfs/MissionVillani_Report_ENG-VF.pdf | A supervised deep mining algorithm is used by French customs in order to detect fraud with value declarations and to analyze cases of identiy fraud or import trafficiking. | National | France | FR | French Customs | Central-Government | Public order and safety | Police Services | Implemented | 2.018 | Enforcement | Supporting inspection processes | No | No | Artificial Intelligence | G2G | x | x | x | x | French AI Strategy - https://www.aiforhumanity.fr/pdfs/MissionVillani_Report_ENG-VF.pdf | Learning | Machine learning | Automated reasoning | Knowledge representation | 17/10/2023 | |||||||||||||||||
| PSTW-410 | Chojnice Virtual clerk | https://www.gov.pl/web/cyfryzacja/mapa-innowacji | As part of the project "Chojnice Poviat - attractive, innovative, investment-friendly - construction of the Biznes Chojnice portal and image campaign of the Chojnice Poviat", among others, on the bizneschojnice.eu website, the "virtual assistant" (chat-bot) service was launched. The "virtual assistant" is a system used to optimize the processes of servicing hundreds of thousands of beneficiaries. It informs interested parties about general matters related to the municipality (tourism, business tip). | Local | Poland | PL | Municipality of Chojnice | Local Government | General public services | General public services n.e.c. | Pilot | 2.020 | Public services and engagement | Service personalisation (various) | No | No | Artificial Intelligence | G2C | x | x | x | https://www.gov.pl/web/cyfryzacja/mapa-innowacji | Communication | Natural language processing | Optimisation | chatbot | 20/11/2023 | ||||||||||||||||||
| PSTW-411 | Introduction of autonomous electric vehicles for urban transport | https://www.gov.pl/web/cyfryzacja/mapa-innowacji | On the route connecting individual local / long-distance / railway / air stations, MPK autonomous, driverless electric public transport vehicles will be introduced, transporting passengers between transfer nodes | Local | Poland | PL | Municipality of Rzeszow | Local Government | Economic Affairs | Transport | Pilot | 2.020 | Public services and engagement | Service integration (various) | No | No | Artificial Intelligence | G2C | x | x | https://www.gov.pl/web/cyfryzacja/mapa-innowacji | Integration and Interaction | Robotics and Automation | Machine learning | Connected and Automated vehicles | 20/11/2023 | |||||||||||||||||||
| PSTW-412 | Chatbot SAM - Virtual Community Assistant | https://www.gov.pl/web/cyfryzacja/mapa-innowacji | Chatbot SAM is a solution that is being introduced to the Kielce Technology Park. It enables communication between tenants and guests with KPT employees. SAM runs mainly on the platforms that users know best, such as Facebook Messenger and Facebook. Using Messenger, the virtual assistant is able to precisely locate its user, helping it find an event, office, or specific company, and even lead and navigate inside and outside the building. Using it, tenants have ongoing contact with guardians, and it is easier for them to find business partners. Artificial Intelligence is being used here to present the offer and stimulate the activity of the KTP community. | Local | Poland | PL | Kielce Technology Park | Local Government | General public services | Foreign economic aid. | Implemented | 2.021 | Public services and engagement | Service personalisation (various) | No | No | Artificial Intelligence | G2C | x | x | x | https://www.gov.pl/web/cyfryzacja/mapa-innowacji | Communication | Natural language processing | Automated reasoning | chatbot | 20/11/2023 | ||||||||||||||||||
| PSTW-413 | Kąty Wrocławskie Virtual clerk | https://www.bskw.pl/ | This project aims to implement advanced public e-services in the municipality and commune administration, with the aim of improving and rationalizing work and communication between the office and the citizen. The eK@ty Wrocławskie mobile application is an assistant to an inhabitant of the Kąty Wrocławskie commune. | Local | Poland | PL | Municipality of Kąty Wrocławskie | Local Government | General public services | Executive and legislative organs, financial and fiscal affairs, external affairs. | Implemented | 2.021 | Public services and engagement | Engagement management | No | No | Artificial Intelligence | G2C | x | x | https://www.gov.pl/web/cyfryzacja/mapa-innowacji | Communication | Natural language processing | Searching | chatbot | 20/11/2023 | |||||||||||||||||||
| PSTW-414 | BOSCO - Distribution of financial aid | https://digitalfuturesociety.com/report/algorithms-in-the-public-sector-four-case-studies-of-adms-in-spain/ | In November 2017, the office of the Secretary of State for Energy released some software, known as BOSCO, to companies providing electricity. The aim of BOSCO was to determine whether people were entitled to financial aid to help; them with their electricity bills. The reasoning behind the ADM was twofold. Firstly, that it would make the process much easier for aid applicants (although, this didn’t seem to be the case judging by the large number of complaints the system received) and secondly, that it would also make the process easier and more efficient for the public utility companies. After receiving many reports that the software was not functioning properly, Civio, a Madrid-based non-profit investigative newsroom and citizen lobby, discovered that BOSCO was systematically denying aid to eligible applicants. Civio asked the government for the BOSCO source code to identify why those errors were happening. | National | Spain | ES | Secretary of State for Energy | Central-Government | Social protection | Social protection n.e.c. | Implemented | 2.017 | 2020 | Adjudication | Taking decisions on benefits | No | No | Artificial Intelligence | G2G | x | x | x | x | x | x | https://automatingsociety.algorithmwatch.org/report2020/spain/ | Reasoning | Automated reasoning | Machine learning | 20/11/2023 | |||||||||||||||
| PSTW-415 | Pred Crime Pilot Rivas-Vaciamadrid | https://www.eurocop.com/sistemas-de-eurocop/analisis-y-prediccion-del-delito/ | In 2016, the local police of Rivas-Vaciamadrid, a town of 86,000 people in the Madrid region, ran a pilot of the Pred-Crime software, developed by Spanish company EuroCop (Europa Press, 2015). Pred-Crime analyzes historical data to predict where and when it’s more likely that different types of common misdemeanors and offenses, like traffic violations and robberies, will be committed. Reportedly, the plan was to fully implement this software during 2016, but after testing it for nine months the municipality decided not to go on using it. EuroCop says on its website that it has dozens of municipalities from all over Spain among its customers, but it doesn’t specify whether those local authorities are using its predictive software or any of the other non-predictive tools the company also markets. In another case of predictive policing, the Spanish police have reportedly been using software that analyzes the available data about the victim of a killing and the context of the crime, and then produces the likely profile of the killer. Between 2018 and 2019, agents of the office of the Secretary of State for Security have collaborated with the police by using such software in at least five investigations, according to a press report (Pérez Colomé, 2019b) | Local | Spain | ES | Local police of Rivas-Vaciamadrid | Local Government | Public order and safety | Police Services | Pilot | 2.016 | Enforcement | Predictive enforcement processes | No | No | Artificial Intelligence | G2C | x | x | x | https://automatingsociety.algorithmwatch.org/report2020/spain/ | Planning | Planning and Scheduling | Knowledge representation | 20/11/2023 | |||||||||||||||||||
| PSTW-416 | Automated analysis of social media content | https://automatingsociety.algorithmwatch.org/report2020/spain/ | In January 2018, the regional Government of Catalonia started a pilot project to try and measure the impact among the public of its STEMcat’s initiatives, a plan aimed at promoting scientific and technological vocations among young people. For a month and a half, the Catalan government used Citibeats. This text-analysis software used machine-learning algorithms to collect and analyze around 12,000 tweets that spoke about the STEM disciplines in Catalonia. One of the insights the authorities said that they had gained was that women were more responsive to messages about natural sciences than about technology, according to the Catalan government’s PR. The authorities then used that and other insights to “optimize their strategy and propose new initiatives” to make young people interested in the STEM disciplines. The project was part of SmartCAT, the Catalan government’s strategy to become a smart region (as noted in this chapter, regional governments in Spain have a high degree of autonomy to develop their policies). The SmartCAT director said the software had allowed them “to evaluate in a more objective way the impact of the (government’s) initiatives” to make people interested in science and technology. Citibeats, developed by Social Coin, a Barcelona-based start-up, was also used in December 2017 by the Barcelona municipality to gather people’s attitudes towards public transport and mobility in the city by analyzing around 30,000 comments by more than 15,000 people. In a case study of this project, Citibeats spoke of “citizens as sensors”. In the two cases described above, and while the authorities praise the software’s ability to gather and analyze thousands of online comments (something it would take much more time and money to do using traditional survey methods), it’s not clear how representative those samples are and how valid the conclusions might be; and there doesn’t seem to be any information on how those analyses then influenced public policy. Since March 2019, the regional government of Navarra has also been using the Citibeats software to detect online hate speech by analyzing text published on Facebook, Twitter and Instagram. As with other cases dealing with personal data, it’s not clear how the software works and what oversight mechanisms the public authority may have in place when using it. | Regional | Spain | ES511 | Catalan Regional Government | Local Government | General public services | General public services n.e.c. | Pilot | 2.018 | Analysis, monitoring and regulatory research | Information analysis processes | No | No | Artificial Intelligence | G2G | x | x | x | x | x | x | https://automatingsociety.algorithmwatch.org/report2020/spain/ | Communication | Natural language processing | Machine learning | sentiment analysis | 20/11/2023 | |||||||||||||||
| PSTW-417 | IBM Watson: Automated assistance in tax filing in Spain | https://automatingsociety.algorithmwatch.org/report2020/spain/ | Since July 2017, the Tax Authority in Spain has been using the IBM Watson software to provide automated assistance regarding a particular aspect of VAT filing which mostly affects big companies. In public communications about it, both IBM and the Tax Authority highlighted that the software can work 24/7 and, as such, was freeing public servants from having to deal with a large number of emails from people trying to do their VAT filing. According to their PR, between July 2017 and February 2018, the number of emails to civil servants about VAT issues decreased from 900 to 165 per week. And, reportedly, the automated assistant went from receiving around 200 questions per week, when it was launched in July 2017 to around 2,000 by November 2017 (Computing, 2018). | National | Spain | ES | Spanish Tax Authority | Central-Government | General public services | Executive and legislative organs, financial and fiscal affairs, external affairs. | Implemented | 2.017 | Public services and engagement | Service personalisation (various) | No | No | Artificial Intelligence | G2C | x | x | x | https://automatingsociety.algorithmwatch.org/report2020/spain/ | Communication | Natural language processing | Machine learning | chatbot | 20/11/2023 | ||||||||||||||||||
| PSTW-418 | REACHOUT: Smart Cities: from smart waste to smart tourism | https://reachout-cities.eu/post_type_city/logrono/ | As cities aim to start using big data and automated processes to become “smart”, a series of ADM systems have been embedded at the municipal level in Spain. These systems usually support decision-making rather than working entirely autonomously. One such example is the Smart Waste platform, which collects data from sensors installed in bins and trucks, and also from social media, surveys, the census, and satellite information. The combined data helps local authorities decide what services will be needed when and where. Smart Waste was developed by The Circular Lab (from the innovation center of Ecoembes) which is a non-profit organization charged with collecting plastic packaging, cans, cartons, paper, and cardboard packaging for recycling. Minsait, a division of Indra, a Spanish multinational transport, defense, and security technology consultancy company also helped develop the platform. During 2018, the Logroño municipality and the La Rioja and Cantabria regional governments first ran the platform as a pilot and today it is available to local and regional authorities all over Spain. As is the norm in almost every case in Spain, there does not seem to be any available information on how the software works, what kind of output it produces, and what decisions or changes the different authorities have adopted due to its use. | Local | Spain | ES | Logroño municipality and the La Rioja and Cantabria regional governments | Local Government | Housing and community amenities | Housing and community amenities n.e.c. | Pilot | 2.021 | 2025 | Public services and engagement | Service integration (various) | No | No | Artificial Intelligence | G2G | x | x | https://automatingsociety.algorithmwatch.org/report2020/spain/ | Learning | Machine learning | Planning and Scheduling | big data | 20/11/2023 | ||||||||||||||||||
| PSTW-419 | Smart video surveillance by the local police: Briefcam | https://automatingsociety.algorithmwatch.org/report2020/belgium/ | Since 2019, the local police in the cities of Kortrijk, Kuurne, and Lendelde (VLAS) have been using a ‘smart’ video surveillance system developed by an American company called Briefcam. The system stores all ‘objects’ (for example: people, small and large vehicles, and animals) that appear in the video images. An algorithm then decides what category each object belongs to, and, after this first categorization, a sub-categorization is made. For example, when it comes to people, the system categorizes each person as either a man, woman, or child before further categorizing by clothing: short/long sleeves, short/long trousers, color of clothing, and things such as hats, handbags, backpacks, etc. The same system of categorization is used for vehicles. | Local | Belgium | BE | Local police in the cities of Kortrijk, Kuurne, and Lendelde (VLAS) | Local Government | Public order and safety | Police Services | Implemented | 2.019 | Enforcement | Smart Recognition processes | No | No | Artificial Intelligence | G2G | x | x | x | https://automatingsociety.algorithmwatch.org/report2020/belgium/ | Perception | Computer vision | Machine learning | object recognition | 20/11/2023 | ||||||||||||||||||
| PSTW-42 | RenoiRH - Chatbot in HR management rules to facilitate access | https://www.youtube.com/watch?v=J0cFEJh8f70 | Interministerial Center for IT Services Relating to Human Resources (CISIRH) has developed a chatbot specialized in HR management rules to facilitate access to information. The public service includes a large number of standards, nomenclatures and written rules such as those relating to the mobility of agents and their career development. | National | France | FR | Interministerial Center for IT Services Relating to Human Resources | Central-Government | General public services | Executive and legislative organs, financial and fiscal affairs, external affairs. | Pilot | 2.018 | Internal management | Internal support processes | No | No | Artificial Intelligence | G2C | x | x | x | x | https://www.youtube.com/watch?v=J0cFEJh8f70 | Communication | Natural language processing | Knowledge representation | chatbot | 17/10/2023 | |||||||||||||||||
| PSTW-420 | Algorithmic school registrations | https://automatingsociety.algorithmwatch.org/report2020/belgium/ | In many Belgian cities, there are problems when registering children for schools, especially when a lot of parents want to register their children at the same school. This has led to parents spending several nights in tents outside schools so that they can be the first to register their children. In response to this situation, which was considered unfair, several cities started organizing school registration via a central online system that uses an algorithm to decide in which school a child can be registered. In the system for primary schools, that is used in Leuven, a city east of Brussels, a number of variables are taken into account. On the basis of the answers given by the parents to a series of questions relating to the education level of the mother and whether or not the student receives a grant, students are then divided into ‘indicator students’ and ‘non-indicator students’. An indicator student is a student who is defined as having fewer life chances and is based upon the level of education of the mother and if the student is eligible for an education allowance. Further categorization happens on the basis of two criteria: distance from home to school and preference of school. The schools can decide how much weight they assign to distance and preference i.e. between 30%, 50%, or 70% for each (Meldjeaan, 2020). This weight can differ between cities, for instance, in Antwerp the schools have to assign a minimum of 50% to the distance criterium. For secondary schools, some cities also use an online registration system, which uses an algorithm to decide which school the child will go to. However, the system is not the same as for primary schools. As not every municipality has a secondary school, the distance criterium is considered discriminatory and, therefore, it is not taken up (Dierickx and Berlanger, 2019). The system does take into account priority students (i.e., children of the staff of the school) and indicator-students (see above). The algorithm works randomly on the basis of the first choice in three rounds (Aanmelden school, 2020). As the system does not take distance into account, this has led to situations where students from Brussels took up places in Flemish secondary schools outside of Brussels, and children, living close to the school not getting in and having to be registered in schools much farther away (Dierickx and Berlanger, 2019). | Local | Belgium | BE | Municipality of Leuven | Local Government | Education | Pre-primary and primary education. | Implemented | 2.020 | Public services and engagement | Service integration (various) | No | No | Artificial Intelligence | G2C | x | x | https://automatingsociety.algorithmwatch.org/report2020/belgium/ | Reasoning | Automated reasoning | Planning and Scheduling | 20/11/2023 | ||||||||||||||||||||
| PSTW-421 | Predictive ADM systems for healthcare and upbringing | https://www.kantify.com/ | A Brussels startup called Kantify and the AI Lab at the Université Libre Bruxelles (Iridia) has—for the first time—developed a model for predicting atrial fibrillation, a heart rhythm disorder, which causes heart attacks. According to an interview in the Flemish newspaper De Standaard, Lauren Van Parys, a Flemish member of Parliament, said a newly formed government agency of Flanders called the Agency for Upbringing (Agentschap Opgroeien), will use AI to better predict whether problems will emerge with a particular child, based upon existing information . However, when asked about this further, the Agency for Upbringing indicated that there are no concrete plans yet, but that they are preparing a policy note about it. | Regional | Belgium | BE2 | Agency for Upbringing (Agentschap Opgroeien) | Local Government | Health | Health n.e.c. | Implemented | 2.021 | Public services and engagement | Service integration (various) | No | No | Artificial Intelligence | G2C | x | x | x | https://automatingsociety.algorithmwatch.org/report2020/belgium/ | Planning | Planning and Scheduling | Automated reasoning | 20/11/2023 | |||||||||||||||||||
| PSTW-422 | Taxation and the automatization of property evaluation | https://automatingsociety.algorithmwatch.org/report2020/denmark/ | The Danish government has been trying to centralize and automate tax administration for years. One of the key initiatives is automating property value assessments. The Ejendomsvurderingslov (law on property assessment, 2017) mandates the use of an automated system for property valuation. This system is expected to use machine learning to develop a "statistical predictive model" to calculate property values. However, the system has been delayed and there are concerns that it does not comply with Danish administrative law, is more expensive than originally estimated, and may not be accurate. | National | Denmark | DK | Danish Tax Authority | Central-Government | General public services | Executive and legislative organs, financial and fiscal affairs, external affairs. | Implemented | 2.021 | Enforcement | Registration and data notarisation processes | No | No | Artificial Intelligence | G2G | x | x | https://automatingsociety.algorithmwatch.org/report2020/denmark/ | Reasoning | Automated reasoning | Planning and Scheduling | 20/11/2023 | ||||||||||||||||||||
| PSTW-423 | Exam control in schools: fighting fraud or profiling students? | https://automatingsociety.algorithmwatch.org/report2020/denmark/ | Danish students have protested against the use of digital tools to detect exam fraud, arguing that they are invasive and violate their privacy. Additionally, there are concerns about the accuracy and fairness of these systems, and the potential for them to be used to discriminate against certain groups of students. One student described how to disable a digital exam monitor on Github, and a group of students at Copenhagen University developed a machine learning system to detect plagiarism, based on 130,000 student assignments. However, the use of this data was controversial, as it was done without permission from the high schools. The Danish Ministry of Education has put The Digital Exam Monitor on hold, but students continue to ask the authorities to shelve it entirely. | National | Denmark | DK | Danish Ministry of Education | Central-Government | Education | Education not definable by level. | Implemented | 2.019 | Enforcement | Predictive enforcement processes | No | No | Artificial Intelligence | G2G | x | x | https://automatingsociety.algorithmwatch.org/report2020/denmark/ | Learning | Machine learning | Natural language processing | 20/11/2023 | ||||||||||||||||||||
| PSTW-424 | The Youth Guarantee Support System (YGSS) to identifying young people not in education or employment | https://tooelu.ee/et | Since 2018, municipal governments in Estonia have been able to use a tool called The Youth Guarantee Support System (YGSS) (Mis on noortegarantii tugisüsteem? – Tööelu.ee o. J.). This tool helps case managers (social workers, child protection officers, youth workers, etc.) identify young people aged 16-26 who are not in education, employment or training (NEET). It is used to support them when they need to return to education or enter the labor market. Case managers of the Youth Guarantee Support System or the municipal government employees can see information about young people living in their specific locality. However, up until now, not all of the municipalities have joined the program. In order to join, the municipal governments have to send an application to the Municipal Government Information System for Social Services and Benefits (STAR). The case managers or municipal government employees are then shown a list in the STAR system of all the NEET youth who are registered as residents in a specific municipal area and who – according to other registry data – need help. This information is based on data from nine different registries, creating, therefore, a very comprehensive dataset that includes information on the young person’s address, email, phone number, educational background, and if they studied in Estonian or Russian. Young people have the right to forbid the analysis by a case manager, and in cases where the data is processed, young people must give their consent. The case manager then contacts the young people identified by the system and a letter or an SMS is sent to each person asking them to complete a survey. The Youth Guarantee Support System Request is automatically triggered twice a year (15.03 and 15.10). | National | Estonia | EE | Various municipalities in Estonia | Local Government | Social protection | Unemployment. | Implemented | 2.018 | Analysis, monitoring and regulatory research | Information analysis processes | No | No | Artificial Intelligence | G2G | x | x | https://automatingsociety.algorithmwatch.org/report2020/estonia/ | Reasoning | Knowledge representation | Automated reasoning | 20/11/2023 | ||||||||||||||||||||
| PSTW-425 | Prediction model for the healthcare needs of patients with chronic illnesses | https://automatingsociety.algorithmwatch.org/report2020/estonia/ | he EHIF has been cooperating with the World Bank since 2014. The pilot was created by the World Bank with the involvement of the Estonian Health Insurance Fund. Costa Rica is also involved in the project by allowing access to its medical billing database (to look at clinical/socio-economic data not included in EHIF databases). The pilot was officially launched in January 2017. Throughout the pilot, family practitioners joined a series of webinars, led by the local pilot coordinator (World Bank consultant), to reinforce and refresh the initial training. This solution contributes to the empowerment of primary care and also helps find the best algorithm to predict which patients with selected diagnoses are likely to be admitted to the hospital. The solution first identifies certain medical conditions/diagnoses in the EHIF’s medical invoice data- base. It then provides a practical model for family physicians to predict which patients are more likely to be admitted to the hospital or suffer other health problems. | National | Estonia | EE | Estonian Health Insurance Fund | Central-Government | Health | Health n.e.c. | Implemented | 2.014 | Analysis, monitoring and regulatory research | Prediction and planning | No | No | Artificial Intelligence | G2C | x | x | x | https://automatingsociety.algorithmwatch.org/report2020/estonia/ | Planning | Planning and Scheduling | Automated reasoning | 20/11/2023 | |||||||||||||||||||
| PSTW-426 | Checking of data Estonian Unemployment Insurance Fund | https://www.tootukassa.ee/en/data-protection-terms/data-protection-estonian-unemployment-insurance-fund | Estonia’s Unemployment Insurance Fund (EUIF) increasingly uses different automated solutions in its everyday work. After a citizen registers on the Unemployment Insurance Fund website as unemployed, the data is checked and, if it is correct, the citizen is then registered as unemployed. In the background, the system uses AI to check an applicant’s data in different databases. It then decides which document to send to the applicant. | National | Estonia | EE | Estonia Unemployment Insurance Fund (EUIF) | Central-Government | Social protection | Unemployment. | Implemented | 2.020 | Enforcement | Predictive enforcement processes | No | No | Artificial Intelligence | G2G | x | x | x | https://automatingsociety.algorithmwatch.org/report2020/estonia/ | Reasoning | Automated reasoning | Planning and Scheduling | 20/11/2023 | |||||||||||||||||||
| PSTW-427 | Checking entitlement of umemployment aid | https://automatingsociety.algorithmwatch.org/report2020/estonia/ | Estonia’s Unemployment Insurance Fund (EUIF) uses ADM to decide what a person is entitled to, including what amount of unemployment aid or unemployment insurance aid, and for how long. 50% of those decisions are made entirely through AI | National | Estonia | EE | Estonia Unemployment Insurance Fund (EUIF) | Central-Government | Social protection | Unemployment. | Implemented | 2.020 | Adjudication | Taking decisions on benefits | No | No | Artificial Intelligence | G2G | x | x | https://automatingsociety.algorithmwatch.org/report2020/estonia/ | Learning | Machine learning | Automated reasoning | 20/11/2023 | ||||||||||||||||||||
| PSTW-428 | Automatic identification of individual risk factors in social care and healthcare | https://automatingsociety.algorithmwatch.org/report2020/finland/ | In October 2019, the Japanese multinational IT service provider, Fujitsu, announced that it was developing an AI solution for South Karelia’s social care and healthcare district (known by its Finnish acronym Eksote). The project employs machine learning methods with the aim of helping Eksote identify factors underlying social exclusion of young adults, as well as predicting associated risks. With the predictive model, social and healthcare professionals will be provided an overview of risk factors. According to Fujitsu’s press release, the model identifies some 90% of young adults susceptible to social exclusion. In practical terms, the model that is being used is derived from pseudonymized data taken from the use of Eksote’s services by young adults, and it uses this data to predict social exclusion outcomes defined by Eksote’s professionals. According to Eksote, the legislation on the secondary and combined use of healthcare data makes it possible to use only non-identifiable, pseudonymized data. This means that Fujitsu’s model cannot be used to identify individual young adults considered to be at risk of social exclusion; rather, the model produces a list of risk factors on a general level. The next step in the project is to examine whether it is possible, under the current legislation, to set up a consent-based system: a client’s consent would be asked for before using the predictive model on their individual data when they, for example, have an appointment with a social care or healthcare professional. | Regional | Finland | FI | Eksote | Local Government | Health | Health n.e.c. | Planned | 2.021 | Analysis, monitoring and regulatory research | Prediction and planning | No | No | Artificial Intelligence | G2C | x | x | x | https://automatingsociety.algorithmwatch.org/report2020/finland/ | Learning | Machine learning | Automated reasoning | 20/11/2023 | |||||||||||||||||||
| PSTW-429 | Predicting youth problems - Identifying youth problems and providing support | https://automatingsociety.algorithmwatch.org/report2020/finland/ | In June 2018, Eksote announced that it had developed, in collaboration with the Finnish IT firm, Avaintec, an AI model to predict problems experienced by children and the youth. The aim was to identify problems early on, so that an intervention could be made and support provided to families sooner rather than later. Much like in the 2019 project on young adults and social exclusion, this model was based on explicitly defined undesired “endpoints”: low-grade averages, disciplinary interventions at school, high-class non-attendance figures, being taken into custody, acceptance into psychiatric care, and substance abuse. The model made use of data gathered from the IT systems of maternity clinics, kindergartens, schools, healthcare, and mental healthcare providers, as well as social services – e.g., it combined data from different administrative branches, namely social care, healthcare, and education. The outcome was the identification of a total of 1340 risk factors, ranging from bad teeth in children, to parents missing maternity clinic appointments, to the child’s siblings bullying others at school. These examples also give an idea of the kinds of data that were employed when making predictions. Ideally, the model would make it possible to continuously keep track of risk factors of individual children. | Regional | Finland | FI | Eksote | Local Government | Social protection | Family and children. | Planned | 2.018 | Analysis, monitoring and regulatory research | Prediction and planning | No | No | Artificial Intelligence | G2C | x | x | x | x | https://automatingsociety.algorithmwatch.org/report2020/finland/ | Planning | Planning and Scheduling | Automated reasoning | 20/11/2023 | ||||||||||||||||||
| PSTW-432 | RADAAR-iTE Predictive policing - risk assessment of militant Salafitsts | https://automatingsociety.algorithmwatch.org/report2020/germany/ | Since 2017, the Bundeskriminalamt (Federal Crime Agency, BKA) has used the risk-assessment tool RADAR-iTE (Bundeskriminalamt, 2017) to sort “militant Salafists” into three threat levels (high, conspicuous, and moderate). The system was developed in cooperation with the Department of Forensic Psychology at the University of Konstanz. In order to assess a person already known to the authorities, the caseworker fills in a standardized questionnaire about the “observable behavior” of the subject, drawing on data the police previously gathered on the person and everything the police is legally authorized to access. Once the results of the corresponding threat levels are provided, the caseworker (or the respective department) decides what action to take. | National | Germany | DE | Bundeskriminalamt (Federal Crime Agency, BKA) | Central-Government | Public order and safety | Police Services | Implemented | 2.017 | Enforcement | Predictive enforcement processes | No | No | Artificial Intelligence | G2G | x | x | x | https://automatingsociety.algorithmwatch.org/report2020/germany/ | Planning | Planning and Scheduling | Knowledge representation | 20/11/2023 | |||||||||||||||||||
| PSTW-433 | PRECOBS - Predictive policing in German administrations | https://automatingsociety.algorithmwatch.org/report2020/germany/ | In Bavaria, the tool PRECOBS (Institut für musterbasierte Prognosetechnik, 2018) calculates where burglaries are most likely to occur, however, the same software was discontinued in Baden Wurttemberg in 2019 due to data quality issues (Mayer, 2019). In the field of burglary prevention, the state of Hesse deploys the KLB-operativ forecast tool (Polizei Hessen, 2017), and Berlin uses KrimPro (Dinger, 2019). Both of these tools analyze data to identify where a potential break-in is most likely to occur. Based on IBM products, North Rhine-Westphalia developed SKALA (Polizei Nordrhein-Westfahlen, 2020), while Lower Saxony uses PreMAP (Niedersächsisches Ministerium für Inneres und Sport, 2018); these two tools make predictions about burglary hot spots, which the police incorporate into action plans. | Regional | Germany | DE | Baden Wurttemberg, Hesse, Berlin and North Rhine-Westphalia | Regional Government | Public order and safety | Police Services | Pilot | 2.018 | 2018 | Enforcement | Predictive enforcement processes | No | No | Artificial Intelligence | G2G | x | x | x | https://automatingsociety.algorithmwatch.org/report2020/germany/ | Planning | Planning and Scheduling | Automated reasoning | 20/11/2023 | ||||||||||||||||||
| PSTW-434 | AI to combat child pornography online | https://news.microsoft.com/de-de/ki-im-einsatz-gegen-kinderpornografie/ | An AI tool to identify pornographic images of children was developed in a collaboration between (Richter, 2019) Microsoft and the Ministry of Justice of the State of North Rhine-Westphalia, the Zentral- und Ansprechstelle Cybercrime (Contact Office for Cyber Crime, ZAC NRW) based in the department of public prosecution in Cologne. In order to comply with strict regulations related to data and child protection, software is used to anonymize the data before they are uploaded to Microsoft servers in a non-identifiable way. In the cloud, algorithms analyze the images for pornographic content, identify the faces of victims and abusers and compare them to existing profiles stored in a database. These results are returned to the police for further analysis. This software aims to reduce the workload and mental strain police endure while investigating child abuse | Regional | Germany | DE | the Zentral- und Ansprechstelle Cybercrime (Contact Office for Cyber Crime, ZAC NRW) | Regional Government | Public order and safety | Police Services | Implemented | 2.019 | Enforcement | Smart Recognition processes | No | No | Artificial Intelligence | G2G | x | x | x | https://automatingsociety.algorithmwatch.org/report2020/germany/ | Perception | Computer vision | Machine learning | 20/11/2023 | |||||||||||||||||||
| PSTW-435 | Suicide Prevention in Jail - Detecting of suspicious objects in a cell | https://automatingsociety.algorithmwatch.org/report2020/germany/ | In 2019, the Ministry of Justice of the State of North Rhine-Westphalia launched a program aimed at preventing suicide in jail. The ministry employed the Chemnitz-based firm FusionSystems GmbH to build a video surveillance system that can detect suspicious objects such as a knotted rope or a firelighter inside a cell and alert officers on duty. The system is supposed to be used on inmates who are categorized at a medium to high suicide risk level and it is meant to substitute the current in-person checks carried out at 15-minute intervals, which have been criticized because they potentially increase the emotional strain on inmates. | Regional | Germany | DE | Ministry of Justice of the State of North Rhine-Westphalia | Local Government | Public order and safety | Public order and safety n.e.c. | Pilot | 2.019 | Enforcement | Smart Recognition processes | No | No | Artificial Intelligence | G2G | x | x | x | https://automatingsociety.algorithmwatch.org/report2020/germany/ | Perception | Computer vision | Machine learning | 20/11/2023 | |||||||||||||||||||
| PSTW-436 | PRE-VIEW - Identification of international crisis | https://creativebureaucracy.org/discover/videos/krisenfruherkennung-preview/ https://www.bmvg.de/de/aktuelles/krisenfrueherkennung-bundeswehr-verstetigt-vernetzt-verbessert-5391892 | The Federal Foreign Office uses the data analytics tool PRE- VIEW– Prediction, Visualization, Early Warning (Auswärtiges Amt, 2019) to identify evolving international crises. The tool analyzes publicly available data related to current political, economic, and societal trends and conflicts in order to identify developing crises. According to the Federal Foreign Office, AI is used to process the data, which is then used to produce infographics and maps to help provide insights into the state of a particular conflict. Furthermore, trend analyses illustrate how political and societal developments may evolve. PREVIEW is deployed by the Federal Foreign Office’s Department S, which oversees international stabilization measures and crises engagement. The output also supports the civil servants in determining which steps to take next. | National | Germany | DE | Federal Foreign Office | Central-Government | Public order and safety | R&D public order and safety. | Implemented | 2.018 | Analysis, monitoring and regulatory research | Monitoring policy implementation | No | No | Artificial Intelligence | G2C | x | x | x | x | x | https://automatingsociety.algorithmwatch.org/report2020/germany/ | Planning | Planning and Scheduling | Automated reasoning | data analytics | 20/11/2023 | ||||||||||||||||
| PSTW-437 | Identity Check of Migrants - Analysis of content and language of phones | https://automatingsociety.algorithmwatch.org/report2020/germany/ | The Bundesamt für Migration und Flüchtlinge (Federal Office for Migration and Refugees, BAMF) has been using automated text and speech recognition systems to identify refugees since 2017. Agency employees can ask asylum seekers to give them access to their cell phone, tablet, or laptop to verify if they are telling the truth about where they come from. The agency has the ability to obtain all the data contained on the devices and run software on it. The software presents the employee with a limited overview of the content, which also includes language analysis of the text retrieved. According to the BAMF, both the software and the hardware was provided by the firm Atos SE, however, VICE Magazine found evidence, that the mobile forensic technology firm MSAB was also involved. Another tool deployed by the BAMF aims to identify disguised dialects in speech. When an asylum seeker does not have a valid proof of ID, a two-minute voice recording of the person describing a picture in their mother tongue is analyzed by software, which then calculates a percentage of how close the speech comes to a certain dialect. | National | Germany | DE | Bundesamt für Migration und Flüchtlinge (Federal Office for Migration and Refugees, BAMF) | Central-Government | Social protection | Social protection n.e.c. | Implemented | 2.017 | Analysis, monitoring and regulatory research | Monitoring policy implementation | No | No | Artificial Intelligence | G2C | x | x | x | https://automatingsociety.algorithmwatch.org/report2020/germany/ | Communication | Natural language processing | Machine learning | Audio processing | speech recognition | 20/11/2023 | |||||||||||||||||
| PSTW-438 | JUS-IT - Child Care Service | https://www.hamburg.de/jus-it/ | Since 2012, the Behörde für Arbeit, Soziales, Familie und Integration (Agency for Labor, Social Affairs, Family and Integration) in Hamburg has been using a piece of software called JUS-IT (Behörde für Arbeit Soziales Familie und Integration, 2018) for the General Social Service, the Child Care Service and the Economic Help for Youths Programme. It is used to administer cases and automate payments and is equipped with interfaces that connect it to police reports and health insurance funds. The system is based on Cúram – a modular off-the-shelf IBM product that can be tailored for specific needs. In 2019, it was recommended a major revision or a complete shutdown (Lasarzik, 2019) of the software. | Local | Germany | DE | Agency for Labor, Social Affairs, Family and Integration | Local Government | Social protection | Family and children. | Implemented | 2.012 | Adjudication | Taking decisions on benefits | No | No | Artificial Intelligence | G2C | x | x | https://automatingsociety.algorithmwatch.org/report2020/germany/ | Reasoning | Automated reasoning | Planning and Scheduling | 20/11/2023 | ||||||||||||||||||||
| PSTW-439 | ALLEGRO - administer unemployment benefit | https://automatingsociety.algorithmwatch.org/report2020/germany/ | The Bundesagentur für Arbeit (Federal Labor Agency) uses an IT-system called ALLEGRO to administer unemployment benefit. The agency workers input an applicants’ data and the system calculates the corresponding benefit levels. The system can connect to health insurance and pension funds and cooperate with customs and the Central Register of Foreign Nationals (Ausländerzentralregister) (Deutscher Bundestag, 2018). In 2012, ALLEGRO replaced the administration’s previous software, called A2LL, which was an error prone system developed by T-Systems. The new software was developed in-house at the Federal Labor Agency (Borchers, 2008). | National | Germany | DE | Federal Labor Agency | Central-Government | Social protection | Unemployment. | Implemented | 2.012 | Adjudication | Taking decisions on benefits | No | No | Artificial Intelligence | G2G | x | x | x | x | x | x | https://automatingsociety.algorithmwatch.org/report2020/germany/ | Reasoning | Automated reasoning | Automated reasoning | 20/11/2023 | ||||||||||||||||
| PSTW-44 | Aria - Chatbot answering retired people | https://www.youtube.com/watch?v=Ahz8UbS8moI | National Old Age Insurance Fund (Cnav) is working with "Aria", a chatbot for aswering requests made by retirees, . This chatbot can tell you the amount of income you have declared to the tax authorities, the calendar of next payments, what the direct debit will consist of, etc. , "Aria will be able to speak, will respond to non-retirees and will be able to tackle a larger number of subjects". | National | France | FR | National Old Age Insurance Fund (Cnav) | Central-Government | General public services | Executive and legislative organs, financial and fiscal affairs, external affairs. | Implemented | 2.018 | Public services and engagement | Service integration (various) | No | No | Artificial Intelligence | G2C | x | x | x | x | https://www.linkedin.com/pulse/d%C3%A9couvrez-aria-le-chatbot-de-lassurance-retraite-elisabeth-deymard/ | Communication | Natural language processing | Searching | chatbot | 17/10/2023 | |||||||||||||||||
| PSTW-440 | DyRiAS threat levels of abusive male partners | https://second.wiki/wiki/dyrias | Protection centers for women in the cities of Singen and Weimar use DyRiAS-Intimpartner (DyRiAS intimate partner) to determine the threat levels of abusive male partners. | Local | Germany | DE | Cities of Singen and Weima | Local Government | Social protection | Social protection n.e.c. | Implemented | 2.014 | Enforcement | Supporting inspection processes | No | No | Artificial Intelligence | G2C | x | x | https://automatingsociety.algorithmwatch.org/report2020/germany/ | Planning | Planning and Scheduling | Automated reasoning | 20/11/2023 | ||||||||||||||||||||
| PSTW-444 | ANPR Greece | https://datanoesis.gr/security/automatic-license-plate-recognition/ | Automatic Number Plate Recognition (ANPR) cameras were introduced in 2019. 50 Hellenic police vehicles are equipped with such cameras and they are capable of detecting the license plates of stolen vehicles or vehicles used in criminal activities. The ANPR can recognize 15,000 license plates per hour, and the cameras can detect license plates at speeds above 170 km per hour. In the near future, they will also be able to detect uninsured vehicles. | National | Greece | EL | Hellenic Police | Central-Government | Public order and safety | Police Services | Implemented | 2.018 | Enforcement | Smart Recognition processes | No | No | Artificial Intelligence | G2G | x | x | x | https://automatingsociety.algorithmwatch.org/report2020/greece/ | Perception | Computer vision | Machine learning | 20/11/2023 | |||||||||||||||||||
| PSTW-445 | Smart policing software - Development an integrated information system for police | https://automatingsociety.algorithmwatch.org/report2020/greece/ | Intracom Telecom, a global telecommunication systems and solutions vendor, signed a four million euro contract with the Hellenic Police and the Hellenic Ministry of Citizen Protection for the development of “Smart Policing” software. The contract states that Intracom Telecom will develop an integrated information system which will include the core building blocks for face recognition, automated fingerprint identification, document authentication, and complex information searches in existing databases. The system will allow the police to run checks in real-time during police stops. Based on the implementation timetable of the project, the vendor will deliver the system to the Hellenic Police within 20 months of signing the contract. | National | Greece | EL | Hellenic Police and the Hellenic Ministry of Citizen Protection | Central-Government | Public order and safety | Police Services | In development | 2.018 | Internal management | Internal primary processes | No | No | Artificial Intelligence | G2C | x | x | https://automatingsociety.algorithmwatch.org/report2020/greece/ | Planning | Planning and Scheduling | Automated reasoning | Searching | face recognition | 20/11/2023 | ||||||||||||||||||
| PSTW-447 | Predicting chronic pathologies and post-surgery complications | https://automatingsociety.algorithmwatch.org/report2020/italy/ | In the city of Vimercate, in the Lombardy region of northern Italy, the local branch of the public health authority (Azienda Socio Sanitaria Territoriale, ASST) has adopted open source cloud solutions (developed by Almaviva) which use algorithms to predict the beginning of chronic pathologies and post-surgery complications Building on a decade spent digitizing medical records, Vimercate hospital aims to more efficiently manage patients, including by personalizing treatments according to machine learning-powered analytics, thus reducing costs and optimizing logistics, while at the same time improving its “precision medicine” solutions. “This is the first structured usage of AI within a hospital in Italy”, says Head of AI Solutions at Almaviva, Antonio Cer-qua, who also revealed that the objective is to provide his company’s IoT platform, Giotto, “to a national network of hospitals”. According to Cerqua, “many have already shown their interest” (Il Giorno 2019). Representatives from the consulting giant Deloitte also visited the Vimercate hospital specifically because of this project, wrote Giornale di Monza.“AI must not replace physicians”, says Head of Informatics at ASST Vimercate, Giovanni Delgrossi, “but support them, a tool that helps them making better decisions” (Sole 24 Ore 2019) | Local | Italy | IT | City of Vimercate | Local Government | Health | Hospital services. | In development | 2.019 | Analysis, monitoring and regulatory research | Information analysis processes | No | No | Artificial Intelligence | G2C | x | x | x | x | https://automatingsociety.algorithmwatch.org/report2020/italy/ | Planning | Planning and Scheduling | Machine learning | 20/11/2023 | ||||||||||||||||||
| PSTW-448 | Predictive Jurisprudence - Tribunale di Pisa | https://www.predictivejurisprudence.eu/ | In 2019, the first experiment with automated decision-making within the justice system was developed at LIDER Lab Scuola Superiore Sant’Anna in collaboration with EMbeDS, KDD Lab and the Tribunal of Genoa (Gonews 2019).Predictive Justice is an ambitious long-term project built with an innovative approach and an underlying philosophy. The approach starts from the assumption that only the combination of different expertise and different tools in coherent and integrated pipelines can offer effective results in a short time. For this reason, the teams of each "sub-project" are interdisciplinary and the individual sub-projects also constitute autonomous projects from a scientific and operational point of view. Precisely the idea that the advancement of knowledge with its applicative implications offers pieces to be organized modularly in multiple ways has convinced us to organize the work in building-blocks projects. The ambitions are multiple and transversal: from the attempt to "export" knowledge, techniques, and solutions across disciplines (for example from omics to legal data mining) to the combination of protocols and software to automate the pseudonymization of texts or to the creation of innovative tools for querying legal materials through their automatic annotation to the construction of prediction tools based on data science and Intelligence Artificial, to the attempt to offer understandable explanations on the functioning of the tools produced / used adapting them to the needs / capabilities of the different end users. All these steps are obviously articulated in full coherence with the corresponding regulatory and ethical framework, convinced that the regulatory and ethical profiles in research are central and go beyond mere adherence to the rules. | Regional | Italy | IT | Tribunal of Pisa (and EMbeDS, KDD Lab) | Local Government | Public order and safety | Law courts | In development | 2.021 | Internal management | Internal primary processes | No | No | Artificial Intelligence | G2G | x | x | https://www.lanazione.it/pisa/cronaca/la-giustizia-diventa-predittiva-con-l-intelligenza-artificiale-della-scuola-sant-anna-1.6390186 | Learning | Machine learning | Searching | data mining | 20/11/2023 | |||||||||||||||||||
| PSTW-449 | Evasometro Anonimizzato - Big data analysis of taxpayer behaviour | https://automatingsociety.algorithmwatch.org/report2020/italy/ | Called “Evasometro Anonimizzato”, the tool will include “specific algorithms” and will be able to cross-check the different databases held by the Italian fiscal authorities for inconsistencies in consumption patterns or in any other financial operation. Anomalies recognized by the “digital eyes” of the system will alert fiscal authorities, who can then summon flagged individuals for further scrutiny. This algorithmic-driven monitoring has to be coupled with that of “open sources”, such as “news articles, websites and social media”, by the Italian fiscal authority, Agenzia delle Entrate. The monitoring system has been active since 2016, but was largely unknown to the public until January 2020. It was devised to “acquire all elements that could be useful in knowing the taxpayer”, thereby helping the institution check the consistency of each individual’s fiscal behavior. | National | Italy | IT | Italian Tax Authority (Agenzia delle Entrate) | Central-Government | General public services | Executive and legislative organs, financial and fiscal affairs, external affairs. | Implemented | 2.020 | Enforcement | Supporting inspection processes | No | No | Artificial Intelligence | G2C | x | x | https://automatingsociety.algorithmwatch.org/report2020/italy/ | Planning | Planning and Scheduling | Knowledge representation | 20/11/2023 | ||||||||||||||||||||
| PSTW-450 | KeyCrime software - Finding relationships among serial crimes | https://www.vice.com/en/article/kzggz3/the-milan-police-have-a-high-tech-solution-to-catch-robbers | KeyCrime software had been deployed in the city of Milan to catch robbers in the city. | Local | Italy | IT | Municipality of Milan | Local Government | Public order and safety | Police Services | Implemented | 2.019 | Enforcement | Predictive enforcement processes | No | No | Artificial Intelligence | G2G | x | x | x | https://www.vice.com/en/article/kzggz3/the-milan-police-have-a-high-tech-solution-to-catch-robbers | Planning | Planning and Scheduling | Knowledge representation | Searching | 20/11/2023 | ||||||||||||||||||
| PSTW-451 | XLAW - Trends and pattern discovery in crimes | https://www.xlaw.it/presentazione/index_eng.asp https://www.youtube.com/watch?v=dJAWBQTTBsM | XLAW software also developed by a law enforcement official and it has already been deployed in the cities of Naples, Modena, Prato, Salerno, Livorno, Trieste, Trento, and Venice (Business Insider 2019). Law information website Altalex reports that the system’s accuracy is 87-93% in Naples, 92-93% in Venice, and 94% in Prato, but, at the moment, no independent auditing or fact-checking is publicly available for each of these trials. XLAW is software that uses probabilistic, machine learning-powered solution for trends and pattern discovery in crimes. This implies that one can deduce — or more accurately, induce — how criminal behavior will unfold, before it has happened, by intelligent analysis of the criminal history of a location over time. Lombardo claims to have done this by carefully analyzing 20 years of data and also by calling on his experience in the field. As a result, thanks to XLAW, law enforcement officials can be alerted and deployed on the scene before a crime has even happened. At the same time, XLAW provides police officers with details as precise as “genre, height, citizenship, distinguishing features, and biometrics” of a potential suspect. XLAW has a strong predictive component to it. In the case of Venice, for example, State Police boasted that “84% of felonies (“fatti-reato”) that have been either attempted or committed had been foreseen by the system”. As a result, XLAW is regularly portrayed as a success story. | National | Italy | IT | Department of Public Security Central Anti-Crime Directorate | Central-Government | Public order and safety | Police Services | Implemented | 2.019 | Enforcement | Predictive enforcement processes | No | No | Artificial Intelligence | G2G | x | x | https://spainsnews.com/the-policeman-who-learned-to-program-to-predict-crimes-technology/ | Reasoning | Knowledge representation | Searching | 20/11/2023 | ||||||||||||||||||||
| PSTW-452 | Catch facial recognition software | https://automatingsociety.algorithmwatch.org/report2020/netherlands/ | Dutch police’s Catch face recognition system is of particular importance. An investigation published by VICE in July 2019 uncovered the existence of over 2.2 million images in the Catch system of a total of 1.3 million individuals who may be suspected of committing a serious criminal offense. In November 2019, the police confirmed that its face recognition system now has access to a complete database of people suspected of serious crimes. Current figures are unknown, but in 2017, 93 suspects were identified using the system. Furthermore, the national police introduced a smartphone app that allows police officers to send images to Catch. | National | Netherlands | NL | Dutch Police | Central-Government | Public order and safety | Police Services | Implemented | 2.020 | Enforcement | Smart Recognition processes | No | No | Artificial Intelligence | G2G | x | x | x | https://automatingsociety.algorithmwatch.org/report2020/netherlands/ | Perception | Computer vision | Machine learning | face recognition | 20/11/2023 | ||||||||||||||||||
| PSTW-454 | AI in e-Sociala program - Optimization of the social benefits tranfers | https://automatingsociety.algorithmwatch.org/report2020/slovenia/ | In 2010, the Slovenian government introduced the e-Sociala (e-social services) program to optimize social transfers, such as social and unemployment benefits, child benefits, subsidies, etc. that make up the welfare system. The system consists of many connected databases (Ministry of Public Administration, 2009) and was designed to optimize the work process for social workers, evaluate their work, and prevent errors when processing applications for social welfare. The system has been upgraded since its introduction and that it now includes AI, ADM, and machine learning capabilities. For example, citizens can use ADM to learn their social rights and see a prediction of benefit payments so that they can make an informed evaluation and calculation before applying for social benefits. Furthermore, the application processes for several social rights/benefits is fully automated, e.g., to research previous decisions related to social benefits and to see new (informative) ones for particular applicants. E-sociala can also detect people from the same family and access their financial information, thereby simplifying the process for social workers. The goal is to further automate the process so that the system can create a full “social rights profile” for every applicant. The system will then be able to see what benefits a particular citizen is eligible for, for how long, and for what amount of money. For legal reasons, social workers still need to personally evaluate, print, sign and send every application. At the moment, the process still requires some manual (human) intervention which is recorded and analyzed in order to improve the system and prevent errors. | National | Slovenia | SI | Ministry of Public Administration | Central-Government | Social protection | Social protection n.e.c. | Implemented | 2.011 | Adjudication | Taking decisions on benefits | No | No | Artificial Intelligence | G2G | x | x | x | x | x | x | x | https://automatingsociety.algorithmwatch.org/report2020/slovenia/ | Learning | Machine learning | Knowledge representation | 20/11/2023 | |||||||||||||||
| PSTW-455 | Detecting tax evasion schemes - Machine learning to detect tax evasion | https://automatingsociety.algorithmwatch.org/report2020/slovenia/ | The Ministry of Finance’s financial administration has been using machine learning to detect tax evasion schemes, and tax fraud, and to find errors in tax reports. During the research for this report, we also learned that the ministry ranks “risky” citizens who it thinks are more likely to become tax evaders. | National | Slovenia | SI | Ministry of Finance | Central-Government | General public services | Executive and legislative organs, financial and fiscal affairs, external affairs. | Implemented | 2.018 | Enforcement | Supporting inspection processes | No | No | Artificial Intelligence | G2G | x | x | https://automatingsociety.algorithmwatch.org/report2020/slovenia/ | Reasoning | Automated reasoning | Machine learning | 20/11/2023 | ||||||||||||||||||||
| PSTW-456 | Detect early learning problems in primary schools (METS) | https://automatingsociety.algorithmwatch.org/report2020/slovenia/ | Slovenia was one of the first countries in the world to develop and test an intelligent system to detect early learning problems in primary schools (METIS). The system was designed to monitor pupils’ grades and absences, to search for specific learning patterns, and help teachers find “problematic” pupils. However, the system has been critized. The educational experts were critical of the methodology and they claimed that grades and absences by themselves were not sufficient indicators to reliably detect learning problems. In addition, the budget was too small, and thus researchers had to use interpolated data and take other shortcuts. The public debate also addressed another related issue: that a lot of school data is collected and owned by a private (commercial) contractor - which has a de facto monopoly on AI development in education. | National | Slovenia | SI | Ministry of Education, Science and Sport | Central-Government | Education | Pre-primary and primary education. | Pilot | 2.011 | Analysis, monitoring and regulatory research | Information analysis processes | No | No | Artificial Intelligence | G2G | x | x | x | https://automatingsociety.algorithmwatch.org/report2020/slovenia/ | Learning | Machine learning | Optimisation | 20/11/2023 | |||||||||||||||||||
| PSTW-457 | Checks for financial support - AI for checking companies requesting support | https://automatingsociety.algorithmwatch.org/report2020/sweden/ | The Public Employment Services is actively working and experimenting with AI. ADM is used to perform financial checks on companies seeking financial support to help them employ the long-term unemployed. The eligibility of a company to receive this support is automatically rated: green = eligible for support, yellow = needs an additional manual check, and red = not eligible). There are limited possibilities for caseworkers to challenge the automated decision in this specific area. | National | Sweden | SE | Public Employment Service | Central-Government | Social protection | Unemployment. | Pilot | 2.019 | Adjudication | Taking decisions on benefits | No | No | Artificial Intelligence | G2B | x | x | x | https://automatingsociety.algorithmwatch.org/report2020/sweden/ | Planning | Planning and Scheduling | Knowledge representation | 20/11/2023 | |||||||||||||||||||
| PSTW-458 | Yasmine - Robot employee | https://automatingsociety.algorithmwatch.org/report2020/sweden/ | Nacka municipality is part of Stockholm county, and it has developed and implemented a so-called robot employee called Yasmine. The robot is part of an RPA service platform that was provided by the Norwegian company Basefarm. So far, the administration of Nacka has automated three processes. Two of these are in the so-called Establishment Unit (Etablering), and the other is in the Work and Business Unit. The Establishment Unit is responsible for economic support, unaccompanied children and minors (refugees). The Work and Business Unit administers adult education, societal orientation, and labor market initiatives | Local | Sweden | SE | Nacka municipality | Local Government | General public services | Executive and legislative organs, financial and fiscal affairs, external affairs. | Pilot | 2.018 | 2020 | Adjudication | Taking decisions on benefits | No | No | Artificial Intelligence | G2C | x | x | x | https://automatingsociety.algorithmwatch.org/report2020/sweden/ | Integration and Interaction | Robotics and Automation | Automated reasoning | 20/11/2023 | ||||||||||||||||||
| PSTW-459 | Fall-Screening-Tool FaST - Assisting risk-oriented sanctioning | https://automatingsociety.algorithmwatch.org/report2020/switzerland/ | The Swiss Execution of Penal Sentences and Justice has been introducing a tool called Fall-Screening-Tool to assist in the classification of cases in Risk-Oriented Sanctioning. | National | Switzerland | CH | Swiss Execution of Penal Sentences and Justice | Central-Government | Public order and safety | Police Services | Implemented | 2.017 | Enforcement | Supporting inspection processes | No | No | Artificial Intelligence | G2G | x | x | x | https://automatingsociety.algorithmwatch.org/report2020/switzerland/ | Learning | Machine learning | Searching | 20/11/2023 | |||||||||||||||||||
| PSTW-46 | LaBonneBoîte - Identification of companies with a high probability of hiring | https://ec.europa.eu/social/BlobServlet?docId=20605&langId=en | La Bonne Boite is an online tool that identifies companies with a high probability of hiring within the next six months in the sector and area selected by the seeker. The objective of La Bonne Boite is to help jobseekers find job opportunities that are not published by employers (i.e. "hidden vacancies") and to predict which companies are most likely to hire in the near future. La Bonne Boite is one of the most used job searching services in France and it is about to be further developed in order to target more specific types of jobseekers, like students, that are looking for part-time jobs. This search engine improves a jobseeker's chance of securing a job interview on the basis of spontaneous job applications. La Bonne Boite's computer code can be copied and used by others. There is also an Application Programming Interface (API) which enables the duplication of La Bonne Boite on other websites. | National | France | FR | Pôle emploi | Central-Government | Social protection | Unemployment. | Implemented | 2.016 | Public services and engagement | Service integration (various) | No | Yes | Artificial Intelligence | G2G | x | x | x | x | https://ec.europa.eu/social/BlobServlet?docId=20605&langId=en | Planning | Automated reasoning | Knowledge representation | 17/10/2023 | ||||||||||||||||||
| PSTW-462 | Financial Assistance Automation | https://skr.se/skr/tjanster/larandeexempel/allalarandeexempel/saharautomatiseradenackaprocessenekonomisktbistand.50611.html | Nacka wants to be a modern municipality where the administrators will have more time for individual support with a focus on self-sufficiency through reduced administration. In 2017, work was therefore started on introducing e-service and in December of the same year, the processing process was automated. Nacka was then the second municipality in Sweden to automate the process of financial assistance.Through automation, an increase in quality has been achieved for those who apply digitally. The process is more efficient and customer-oriented. The client chooses when he wants to initiate a case and can then follow his case. | Local | Sweden | SE | Municipality of Nacka | Local Government | General public services | Executive and legislative organs, financial and fiscal affairs, external affairs. | Pilot | 2.017 | 2019 | Internal management | Internal primary processes | No | No | Artificial Intelligence | G2C | x | x | x | https://skr.se/skr/tjanster/larandeexempel/allalarandeexempel/saharautomatiseradenackaprocessenekonomisktbistand.50611.html | Integration and Interaction | Robotics and Automation | Automated reasoning | 20/11/2023 | ||||||||||||||||||
| PSTW-463 | Automated processes Uddevalla - AI to internal processes | https://skr.se/skr/tjanster/larandeexempel/allalarandeexempel/uddevallakommunhar10automatiseradeprocesserigang.51089.html | Uddevalla municipality has 10 automated processes underway, which corresponds to 20 full-time positions' annual work. Until 2021, more automated processes will be started, which will free up twice as many full-time jobs. Before the end of the year, Uddevalla municipality will, through automation, free up resources corresponding to 20 full-time positions' annual work within the social administration. They will also be working on new processes so that another 20 full-time positions can be released by 2021. An automated process can also handle increased volumes without additional resources. The freed up resources can, for example, be used to strengthen childcare and handle increased volumes in the home care service. Right now, Uddevalla municipality has 10 automated processes and the processes involved are: Compensation, Sick pay costs, Authorization admin, Info technology group, Planning system, Financial aid, Automatic closing, Accounting Försäkringskassan, Lunch boxes, Absence, Extra time, New decisions, Change in income, Resource allocation | Local | Sweden | SE | Uddevalla municipality | Local Government | General public services | Executive and legislative organs, financial and fiscal affairs, external affairs. | Implemented | 2.021 | Internal management | Internal primary processes | No | No | Artificial Intelligence | G2G | x | x | x | https://skr.se/skr/tjanster/larandeexempel/allalarandeexempel/uddevallakommunhar10automatiseradeprocesserigang.51089.html | Learning | Robotics and Automation | Optimisation | 20/11/2023 | |||||||||||||||||||
| PSTW-464 | RPA in Södertälje - Automation of internal services | https://skr.se/skr/tjanster/larandeexempel/allalarandeexempel/tekniskavagvalocherfarenhetervidinforandetavrpaisodertalje.50823.html | Municipality of Södertälje has introduced RPA to automate several services within the following areas: Absence reporting of hourly employees, terminate hourly employees, travel service booking and employer certificate. | Local | Sweden | SE | Municipality of Södertälje | Local Government | General public services | Executive and legislative organs, financial and fiscal affairs, external affairs. | Pilot | 2.019 | Internal management | Internal support processes | No | No | Artificial Intelligence | G2G | x | x | x | https://skr.se/skr/tjanster/larandeexempel/allalarandeexempel/tekniskavagvalocherfarenhetervidinforandetavrpaisodertalje.50823.html | Learning | Robotics and Automation | Optimisation | 20/11/2023 | |||||||||||||||||||
| PSTW-465 | Machine Learning SoSi (ML_SoSi) | https://www.experimental.bfs.admin.ch/expstat/en/home/projects/ml-sosi.html | Grouping of typical prospective progression patterns with regard to benefit payments in the system of social security and gainful employment as well as estimation of group membership by using individual characteristics and retrospective progression data using a machine learning approach. | National | Switzerland | CH | Federal Statistical Office | Central-Government | General public services | R&D general public services. | Pilot | 2.019 | Analysis, monitoring and regulatory research | Information analysis processes | No | No | Artificial Intelligence | G2G | x | x | https://www.experimental.bfs.admin.ch/expstat/de/home/innovative-datenwissenschaft/ml-sosi.html | Learning | Machine learning | 20/11/2023 | |||||||||||||||||||||
| PSTW-467 | MedicalGuide projec | https://medicalguide.ch/de/ | Canton Aargau has been involved in the MedicalGuide project, which provides users with an initial assessment of disease by using a Chatbot | Local | Switzerland | CH | Canton Aargau | Local Government | Health | Health n.e.c. | Implemented | 2.020 | Public services and engagement | Service personalisation (various) | No | No | Artificial Intelligence | G2C | x | x | x | https://www.egovernment.ch/de/dokumentation/trends-in-der-digitalisierung/kunstliche-intelligenz-ki/ | Learning | Machine learning | Knowledge representation | chatbot | 20/11/2023 | ||||||||||||||||||
| PSTW-468 | Manchester’s Research & Intelligence Database - Identifying troubled families | https://www.local.gov.uk/sites/default/files/documents/childrens-social-care-and-b32.pdf | Manchester City Council is using a system it calls the Manchester Research & Intelligence Database to identify Troubled Families, families in need of support, to enable caseworkers to access more information more quickly than previously and to enable the collection and analysis of data to assess services and impact. The Council developed the system by buying an IBM product called iBase. The approach to using the system has been internally developed. It is noted that the aim is to empower ‘lead professionals to make the best use of data they are legally able to see, and is not about replacing decision making or interpretation with system algorithms or decisions’. The stated aim is to enable a more ‘holistic’ understanding of people, needs and services. Future goals include developing decision making tools, building performance reporting tools, building threshold and alerting tools and rolling the system out to more users, as well as connecting more data. | Local | United Kingdom | UK | Manchester City Council | Local Government | Social protection | Family and children. | Implemented | 2.016 | Analysis, monitoring and regulatory research | Prediction and planning | No | No | Artificial Intelligence | G2G | x | x | x | https://data-scores.org/case-studies | Perception | Planning and Scheduling | Knowledge representation | 20/11/2023 | |||||||||||||||||||
| PSTW-47 | ClaudIA - Chatbot for the invoicing portal for purchases by public authorities | https://portail.chorus-pro.gouv.fr/aife_csm?id=aife_contact | Chatbot Claudia has been setup by the AIFE (State Financial IT Agency) for users of the information system Chorus of SME's and microbusinesses. This chatbot, is based on IBM's Watson Artificial Intelligence technology. The AIFE indicates that the number of support contacts "has not stopped increasing, going from 20,000 per month to more than 40,000 (with a peak at 55,000 in January) all channels combined (phone calls, files, live chat , emails, avatar, chatbot). The requests handled manually by level 1 support operators now represent a volume of more than 15,000 per month (18,000 in January!). The AIFE anticipates a doubling of support requests each year. Before Claudia, only half of the requests were processed automatically. Today, the rate has risen to 65%. “In two months, ClaudIA handled more than 10,000 conversations, with an average of 3.5 interactions per conversation,” says AIFE. Claudia takes the user context into account and knows how to detect inappropriate interactions. | National | France | FR | State Financial IT Agency | Central-Government | General public services | Executive and legislative organs, financial and fiscal affairs, external affairs. | Implemented | 2.018 | Internal management | Internal support processes | No | No | Artificial Intelligence | G2C | x | x | x | x | https://www.cio-online.com/actualites/lire-chorus-pro-aussi-aide-ses-utilisateurs-avec-un-chatbot-10199.html | Communication | Natural language processing | Searching | chatbot | 17/10/2023 | |||||||||||||||||
| PSTW-470 | Predictive Healthcare Assistance DB (BDA) in Regione Lombardia | https://www.ariaspa.it/wps/portal/Aria/Home/progetti/digital/intelligenza-artificiale/ | The evolution of the Assisted Database from a predictive point of view of the Region, which up to now has been involved in stratifying the Lombard population, according to their consumption, on 62 chronic pathologies for tracers, level of complexity, territory, gender, age group and assistance. The project has having regard to the scientific direction of the Logical Epidemic Observatory of the Lombardy Region. | Regional | Italy | IT | Aria Spa | Regional Government | Health | Health n.e.c. | Implemented | 2.021 | Analysis, monitoring and regulatory research | Prediction and planning | No | No | Artificial Intelligence | G2G | x | x | x | x | x | https://www.ariaspa.it/wps/portal/Aria/Home/progetti/digital/intelligenza-artificiale/ | Planning | Planning and Scheduling | Machine learning | 20/11/2023 | |||||||||||||||||
| PSTW-471 | Finding the ‘next-best-clinical-action" | https://www.ariaspa.it/wps/portal/Aria/Home/progetti/digital/intelligenza-artificiale/ | Use of data & process mining techniques, of the characteristics of a specific pathology: cognitive dementia. The project aims to identify the so-called 'next-best-clinical-action', that is to analyze and predict, according to consumption and health events of the chronic population affected by this pathology, what the medical pathway may be, the 'patient journey ', carried out by a chronic patient, year by year, in the five years following the onset of the disease. | Regional | Italy | IT | Aria Spa | Regional Government | Health | Health n.e.c. | Implemented | 2.021 | Analysis, monitoring and regulatory research | Prediction and planning | No | No | Artificial Intelligence | G2G | x | x | x | x | https://www.ariaspa.it/wps/portal/Aria/Home/progetti/digital/intelligenza-artificiale/ | Learning | Machine learning | Automated reasoning | 20/11/2023 | ||||||||||||||||||
| PSTW-472 | Geo Machine Learning for Health | https://www.ariaspa.it/wps/portal/Aria/Home/progetti/digital/intelligenza-artificiale/ | In this project we look at patients suffering from respiratory diseases, in particular respiratory insufficiency, chronic obstructive pulmonary disease (COPD) and asthma. In particular, by applying machine learning techniques we are able to determine what we have defined UMTA or Minimum Unit Territorial Aggregation. A kind of geographical area where they are assisted aggregates characterized by homogeneous sanitary properties, still related to the tracers above cited defined by the Regional Logical Epidemic Observatory | Regional | Italy | IT | Aria Spa | Regional Government | Health | Health n.e.c. | Implemented | 2.021 | Analysis, monitoring and regulatory research | Prediction and planning | No | No | Artificial Intelligence | G2G | x | x | x | https://www.ariaspa.it/wps/portal/Aria/Home/progetti/digital/intelligenza-artificiale/ | Learning | Machine learning | Planning and Scheduling | 20/11/2023 | |||||||||||||||||||
| PSTW-474 | ANCI Lombardia - CVqui-Jobiri | https://www.jobiri.com/intelligenza-artificiale-nella-pubblica-amministrazione/ | The solution created by Jobiri with the collaboration of the Informagiovani of Cremona, Crema, Lodi, Novate Milanese and Bergamo. It is an integrated ecosystem of intelligent career services capable of digitizing the services for the work of youth information in the Lombardy Region. Citizens in the area can develop their own professional project, consult job opportunities, create resumes with thousands of examples, take advantage of dozens of cover letter templates, train in interviews with video simulations and improve their CV with automatic suggestions. Public institutions can improve the offer of employment services for citizens and businesses in the area thanks to self-service technologies that favor job matching and develop employability skills. Companies who can engage candidates more effectively thanks to employer branding tools, publish job opportunities, manage the selection process and collaborate with institutions to share employment trends. | Local | Italy | IT | Municipality of Cremona | Local Government | Social protection | Unemployment. | Implemented | 2.021 | Public services and engagement | Service personalisation (various) | No | Yes | Artificial Intelligence | G2C | x | x | https://www.jobiri.com/intelligenza-artificiale-nella-pubblica-amministrazione/ | Communication | Natural language processing | Searching | text analysis | 21/11/2023 | |||||||||||||||||||
| PSTW-477 | Mobilità Integrata Trentino Trasporti (MITT) | http://www.trasporti.provincia.tn.it/ | The MITT makes it possible to optimize the management of the provincial public transport system in such a way as to offer a better and more effective service to the citizen. It provides for the introduction of smart cards, for the management of integrated and differentiated tariffs, which can then be used in a multiservice logic. Real-time monitoring of local public transport vehicles and travel time management for Trentino Trasporti, AI technologies are used to detect the position of buses in real time and transmit information on journey times to passengers as well as to predict and plan the bus scheduling | Regional | Italy | ITH20 | Provincia autonoma di Trento - Trentino Trasporti (in house) | Local Government | Economic Affairs | Transport | Implemented | 2.021 | Public services and engagement | Service integration (various) | No | No | Artificial Intelligence | G2C | x | x | x | https://cms.uitp.org/wp/wp-content/uploads/2021/03/IOT-KB-final.pdf | Learning | Machine learning | Optimisation | 21/11/2023 | |||||||||||||||||||
| PSTW-478 | GADgET: Detection of addition patterns in online game | https://arquivo.pt/wayback/20221230035605mp_/https://former.fct.pt/media/docs/Brochura_ResearchinDataScienceandAIappliedtoPA.pdf | To tackle the problem of online gambling, we propose a system based on a version of Recurrent Neural Networks the architecture of which will be optimized by a neuroevolution algorithm. To effectively resolve the problem under consideration, this system must be able to render efficient comparisons of time series associated with different gamblers’ behaviors, in a way that also takes the temporal dimension of the problem into account. The system, therefore, must be able to: 1) identify common behavioral patterns among gamblers within in an acceptable timeframe; 2) detect actions that are representative of a risky behavior in the context of gambling; and 3) run in real-time, to allow for continuous control of gambling activities. | National | Portugal | PT | FCT (Fundação para a Ciência e Tecnologia) | Central-Government | Social protection | Social protection n.e.c. | Pilot | 2.019 | 2022 | Enforcement | Predictive enforcement processes | No | No | Artificial Intelligence | G2G | x | x | https://arquivo.pt/wayback/20221230035605mp_/https://former.fct.pt/media/docs/Brochura_ResearchinDataScienceandAIappliedtoPA.pdf | Learning | Machine learning | Planning and Scheduling | 21/11/2023 | |||||||||||||||||||
| PSTW-479 | AICE (Data Science and Over-Indebtedness: Use of AI algorithms in Credit and Debts) | https://arquivo.pt/wayback/20221230035605mp_/https://former.fct.pt/media/docs/Brochura_ResearchinDataScienceandAIappliedtoPA.pdf | Research indicates that vulnerability for over-indebtedness is mainly determined by socio-economic factors and financially relevant life events such as job loss. Given this scenario, this project proposes the use of Machine Learning (ML) for developing descriptive and predictive models, to understand the influencing factors of over-indebtedness on Portuguese consumers. Descriptive models will be obtained using Unsupervised ML algorithms like Self Organizing Maps and Agglomerative Hierarchical Clustering and will be used for establishing consumer clusters and guidelines for over-indebtedness regulation and consumer financial empowerment. | National | Portugal | PT | FCT (Fundação para a Ciência e Tecnologia) | Central-Government | Social protection | Social protection n.e.c. | Pilot | 2.020 | 2022 | Analysis, monitoring and regulatory research | Information analysis processes | No | No | Artificial Intelligence | G2G | x | x | https://arquivo.pt/wayback/20221230035605mp_/https://former.fct.pt/media/docs/Brochura_ResearchinDataScienceandAIappliedtoPA.pdf | Learning | Machine learning | Knowledge representation | 21/11/2023 | |||||||||||||||||||
| PSTW-48 | IAlim - Targeting restaurant health inspections | https://agriculture.gouv.fr/telecharger/116478?token=34e41e9143e50e1be2324f7d9bf7f7fceffe7183e5e97acb34d333c90a70b5a6 | Since November 2019, Ministry of Agriculture inspectors have been able to use “Food AI” (IAlim) to assist them in targeting their restaurant health inspections more effectively. Refine the targeting of establishments to be inspected in the direct-to-consumer delivery sector (restaurants, food service businesses, distributors) through consumer feedback on online notification sites. | National | France | FR | The General Food Directorate (DGAL) of the Ministry of Agriculture and Food | Central-Government | Health | Public health services. | Implemented | 2.017 | 2019 | Enforcement | Supporting inspection processes | No | No | Artificial Intelligence | G2G | x | x | x | x | https://www.etalab.gouv.fr/intelligence-artificielle-decouvrez-les-6-projets-laureats-de-lappel-a-manifestation-dinteret-ia | Planning | Searching | Machine learning | 17/10/2023 | |||||||||||||||||
| PSTW-480 | MapIntel - Interactive Visual Analysis Platform for Competitive Intelligence | https://arquivo.pt/wayback/20221230035605mp_/https://former.fct.pt/media/docs/Brochura_ResearchinDataScienceandAIappliedtoPA.pdf | Competitive Intelligence (CI) is concerned with gathering and analyzing information on any aspect of the business environment needed to support executives in strategic planning and decision-making. In this project they propose a neural network-based document clustering system, which is a genuine content addressable memory system, meaning it clusters and stores text documents so they can be retrieved based on their content. Using Self-Organizing Maps (SOM’s), documents are mapped as points on a semantic map, in a topological order that describes the similarity of their contents. This map is then used as a metaphor to interact with the text corpus, creating an interactive visual analytics tool, allowing for its exploration through different, but correlated views and iteratively selecting and examining document. | National | Portugal | PT | AMA (Agência para a Modernização Administrativa) | Central-Government | Economic Affairs | General economic, commercial and labour affair | Pilot | 2.019 | 2021 | Analysis, monitoring and regulatory research | Prediction and planning | No | No | Artificial Intelligence | G2G | x | x | https://arquivo.pt/wayback/20221230035605mp_/https://former.fct.pt/media/docs/Brochura_ResearchinDataScienceandAIappliedtoPA.pdf | Reasoning | Automated reasoning | Machine learning | 21/11/2023 | |||||||||||||||||||
| PSTW-481 | MILITARY CARE (improve customer satisfaction through cognitive models of text and voice) | https://www.ama.gov.pt/web/agencia-para-a-modernizacao-administrativa/mais-ap | MILITARY CARE - AIcare aims to improve customer and business satisfaction through cognitive models of text and voice. | National | Portugal | PT | AMA (Agência para a Modernização Administrativa) | Central-Government | Defence | Military defence. | Implemented | 2.019 | 2020 | Public services and engagement | Service personalisation (various) | No | No | Artificial Intelligence | G2B | x | x | x | Perception | Audio processing | Natural language processing | 21/11/2023 | |||||||||||||||||||
| PSTW-482 | Extended Situational and Operational Knowledge Management Service for National Cyberspace | https://www.ama.gov.pt/web/agencia-para-a-modernizacao-administrativa/mais-ap | National Cybersecurity Center – Extended Situational and Operational Knowledge Management Service for National Cyberspace. | National | Portugal | PT | AMA (Agência para a Modernização Administrativa) | Central-Government | Defence | R&D defence. | In development | 2.019 | 2021 | Enforcement | Predictive enforcement processes | No | No | Artificial Intelligence | G2G | x | x | Reasoning | Optimisation | Knowledge representation | 21/11/2023 | ||||||||||||||||||||
| PSTW-483 | Methodologies for AI use in data analysis and statistical validation from markets regulated by ERSAR | https://www.ama.gov.pt/web/agencia-para-a-modernizacao-administrativa/mais-ap | Definition, testing and adoption of methodologies for the application of artificial intelligence in the analysis and statistical validation of data from markets regulated by ERSAR. | National | Portugal | PT | AMA (Agência para a Modernização Administrativa) | Central-Government | Economic Affairs | Economic affairs n.e.c | In development | 2.019 | 2021 | Internal management | Internal support processes | No | No | Artificial Intelligence | G2G | x | x | Learning | Machine learning | Knowledge representation | 21/11/2023 | ||||||||||||||||||||
| PSTW-484 | CEOS - Knowledge of the Evolution of Opportunities between the Genders | https://www.mdpi.com/2227-9709/10/4/81 | CEOS - Knowledge of the Evolution of Opportunities between the Genders | National | Portugal | PT | AMA (Agência para a Modernização Administrativa) | Central-Government | Social protection | Social protection n.e.c. | Implemented | 2.019 | 2020 | Analysis, monitoring and regulatory research | Information analysis processes | No | No | Artificial Intelligence | G2G | x | x | x | Learning | Machine learning | Knowledge representation | 21/11/2023 | |||||||||||||||||||
| PSTW-485 | Autoridade de Segurança Alimentar e Económica (ASAE)- Intelligent Management and Operational Control Center - CIGESCOP | https://www.asae.gov.pt/destaques55/projeto-cigescop.aspx | The CIGESCOP project has as main objectives: (1) strengthen the institutional capacity of the Autoridade de Segurança Alimentar e Económica (ASAE) as a Criminal Police and Administrative Authority, strengthening and qualitatively increasing the interaction between ASAE, citizens and companies; (2) Undertake a process reengineering leveraged with innovation models based on Artificial Intelligence and Data Science, in order to optimize management and operational control, providing a more effective and efficient response to the activity inspection, enhancing public health, consumer protection and safeguarding the rules of free competition; (3) Streamline work processes, human and technological resources, with task automation, promoting the Organization's digital transformation. | National | Portugal | PT | AMA (Agência para a Modernização Administrativa) | Central-Government | General public services | General services. | Implemented | 2.019 | 2021 | Enforcement | Supporting inspection processes | No | No | Artificial Intelligence | G2G | x | x | https://www.asae.gov.pt/destaques55/projeto-cigescop.aspx | Planning | Planning and Scheduling | Optimisation | 21/11/2023 | |||||||||||||||||||
| PSTW-486 | Understanding the determinants of academic performance from Portuguese secondary education system | https://link.springer.com/article/10.1007/s10639-020-10316-y | Using an anonymous 2014–15 school year dataset from the Directorate-General for Statistics of Education and Science (DGEEC) of the Portuguese Ministry of Education, the work carried out a predictive power comparison between the classic multilinear regression model and a chosen set of machine learning algorithms to study what factors influence students' performance at high school. A multilinear regression model is used in parallel with random forest, support vector machine, artificial neural network and extreme gradient boosting machine stacking ensemble implementations. | National | Portugal | PT | FCT (Fundação para a Ciência e Tecnologia) | Central-Government | Education | Secondary education. | Pilot | 2.019 | 2021 | Analysis, monitoring and regulatory research | Information analysis processes | No | No | Artificial Intelligence | G2G | x | x | https://link.springer.com/article/10.1007/s10639-020-10316-y | Learning | Machine learning | Planning and Scheduling | 21/11/2023 | |||||||||||||||||||
| PSTW-487 | Modeling student flow in the Portuguese education system | https://www.fct.pt/apoios/projectos/consulta/vglobal_projecto?idProjecto=154455&idElemConcurso=12346 | Modeling student flow in the Portuguese education system | National | Portugal | PT | FCT (Fundação para a Ciência e Tecnologia) | Central-Government | Education | Secondary education. | In development | 2.019 | 2022 | Analysis, monitoring and regulatory research | Prediction and planning | No | No | Artificial Intelligence | G2G | x | x | Reasoning | Automated reasoning | Planning and Scheduling | 21/11/2023 | ||||||||||||||||||||
| PSTW-488 | HEALTHI.CO: Factors for promoting dialogue and healthy behaviors in online school communities. | https://arquivo.pt/wayback/20221230035605mp_/https://former.fct.pt/media/docs/Brochura_ResearchinDataScienceandAIappliedtoPA.pdf | This research proposal is concerned with using data to better understand the underlying dynamics of social conversation online within school communities – that is, secondary school students, and their teachers. This new understanding can be used in different ways, particularly in long term educational programmes, to foster more empathetic, inclusive, civil and healthy dialogues online. | National | Portugal | PT | FCT (Fundação para a Ciência e Tecnologia) | Central-Government | Education | Secondary education. | Pilot | 2.021 | 2023 | Public services and engagement | Engagement management | No | No | Artificial Intelligence | G2C | x | x | x | https://arquivo.pt/wayback/20221230035605mp_/https://former.fct.pt/media/docs/Brochura_ResearchinDataScienceandAIappliedtoPA.pdf | Learning | Machine learning | Natural language processing | 21/11/2023 | ||||||||||||||||||
| PSTW-489 | SARAI – Security Advanced Research with Artificial Intelligence | https://www.ua.pt/pt/projetos-id/774 | Explore the mechanisms and techniques of Artificial Intelligence and data science to respond to the challenge of obtaining accurate information in a timely manner, creating a next-generation response. The objective is to create a functional prototype capable of helping the cybersecurity team detect, correct and prevent the exploitation of computer and information security flaws by analysing information produced on a large scale. | National | Portugal | PT | AMA (Agência para a Modernização Administrativa) | Central-Government | General public services | General services. | Pilot | 2.019 | 2021 | Enforcement | Improving Cybersecurity | No | No | Artificial Intelligence | G2G | x | x | https://www.ua.pt/pt/projetos-id/774 | Learning | Machine learning | Knowledge representation | 21/11/2023 | |||||||||||||||||||
| PSTW-49 | OpenJustice - Open case law, pseudonymization and enrichment of court decisions | https://entrepreneur-interet-general.etalab.gouv.fr/defis/2019/openjustice.html | The Court of Cassation, in conjunction with the Ministry of Justice, wishes to develop automatic learning techniques in order to identify the data to be pseudonymized in court decisions before making them accessible and reusable. The results of this work will profoundly transform the dissemination of case law, strengthen the consistency of decisions rendered and citizens' confidence in the judiciary; they can be widely applied to other types of data.This machine learning model to automatically pseudonymize case law data and foster open data of case law. . Aims to foster open data and the development of legal tech start ups | National | France | FR | French Supreme Court | Central-Government | Public order and safety | Law courts | In development | 2.019 | Public services and engagement | Data Sharing Management | No | No | Artificial Intelligence | G2B | x | x | x | x | x | https://entrepreneur-interet-general.etalab.gouv.fr/defis/2019/openjustice.html | Learning | Machine learning | Searching | 17/10/2023 | |||||||||||||||||
| PSTW-490 | CDAP@UP (Predictive Analysis to Promote Student Success and Fight School Dropout) | https://sigarra.up.pt/fcup/en/PROJECTOS_GERAL.FICHA_PROJECTO?P_ID=74997 | Predictive analysis to promote student success and combat school dropout at the University of Porto. | National | Portugal | PT | AMA (Agência para a Modernização Administrativa) | Central-Government | Education | Education not definable by level. | In development | 2.019 | 2021 | Analysis, monitoring and regulatory research | Prediction and planning | No | No | Artificial Intelligence | G2G | x | x | x | https://sigarra.up.pt/fcup/en/PROJECTOS_GERAL.FICHA_PROJECTO?P_ID=74997 | Planning | Planning and Scheduling | Knowledge representation | 21/11/2023 | ||||||||||||||||||
| PSTW-491 | P.IA.ES - Modeling and prediction of failure and school dropout in Higher Education | https://www.researchgate.net/publication/351066139_Early_Prediction_of_Student%27s_Performance_in_Higher_Education_A_Case_Study | This work aims to contribute to the reduction of academic failure at higher education, by using machine learning techniques to identify students at risk of failure at an early stage of their academic path, so that strategies to support them can be put into place. A dataset from a higher education institution is used to build classification models to predict academic performance of students. The dataset includes information known at the time of student’s enrollment – academic path, demographics and social-economic factors. The problem is formulated as a three category classification task, in which there’s a strong imbalance towards one of the classes. Algorithms to promote class balancing with synthetic oversampling are tested, and classification models are trained and evaluated, both with standard machine learning algorithms and state of the art boosting algorithms. Our results show that boosting algorithms respond better to the specific classification task than standard methods. However, even these state of the art algorithms fall short in correctly identifying the majority of cases in one of the minority classes. Future directions of this study include the addition of information regarding student’s first year performance, such as academic grades from the first academic semesters. | National | Portugal | PT | AMA (Agência para a Modernização Administrativa) | Central-Government | Education | Secondary education. | Pilot | 2.019 | 2021 | Analysis, monitoring and regulatory research | Prediction and planning | No | No | Artificial Intelligence | G2C | x | x | x | https://www.researchgate.net/publication/351066139_Early_Prediction_of_Student%27s_Performance_in_Higher_Education_A_Case_Study | Reasoning | Knowledge representation | 21/11/2023 | |||||||||||||||||||
| PSTW-492 | ICDS4IM - Intelligent Support for Clinical Decision in Intensive Care Medicine | https://www.researchgate.net/publication/340637924_A_New_Architecture_for_Intelligent_Clinical_Decision_Support_for_Intensive_Medicine | Real-time and intelligent decision support systems are of most importance to supply intensive care professionals with important information in useful time. The work presented hereby shows an architectural overview of the communication system with bedside devices such as vital sign monitors. Intelligent Decision Support System for Intensive Medicine (ICDS4IM) goal is to ensure information quality and availability to Intensive Medicine professionals to take supported decisions in a mutable environment where complex and unpredictable events are a common state. | National | Portugal | PT | FCT (Fundação para a Ciência e Tecnologia) | Central-Government | Health | Hospital services. | Pilot | 2.019 | 2021 | Analysis, monitoring and regulatory research | Prediction and planning | No | No | Artificial Intelligence | G2G | x | x | https://www.researchgate.net/publication/340637924_A_New_Architecture_for_Intelligent_Clinical_Decision_Support_for_Intensive_Medicine | Learning | Machine learning | Automated reasoning | decision support | 21/11/2023 | ||||||||||||||||||
| PSTW-496 | Artificial Intelligence to reduce mortality and identify healthy living standards | Artificial Intelligence to reduce mortality and identify healthy living standards | National | Portugal | PT | FCT (Fundação para a Ciência e Tecnologia) | Central-Government | Health | Public health services. | In development | 2.020 | 2022 | Analysis, monitoring and regulatory research | Information analysis processes | No | No | Artificial Intelligence | G2G | x | x | Planning | Optimisation | Machine learning | 21/11/2023 | |||||||||||||||||||||
| PSTW-498 | AI applied to diabetes for improvement in the quality of patient care and cost rationalization | Data Science applied to diabetes for continuous improvement in the quality of patient care and cost rationalization. | National | Portugal | PT | AMA (Agência para a Modernização Administrativa) | Central-Government | Health | Public health services. | In development | 2.019 | 2021 | Public services and engagement | Service personalisation (various) | No | No | Artificial Intelligence | G2G | x | x | x | Learning | Machine learning | Optimisation | 21/11/2023 | ||||||||||||||||||||
| PSTW-499 | Audit +: CHBV artificial intelligence engine and business intelligence system | https://cintesis.eu/en/portfolio-items/audit-2/ | Audit + is a project focused on an artificial intelligence engine and business intelligence system of the Hospital Center of Baixo Vouga (HCBV), leader of the project, in partnership with the Faculty of Medicine of the University of Porto (FMUP) and CINTESIS. | National | Portugal | PT | Hospital Center of Baixo Vouga (HCBV) | Central-Government | Health | Hospital services. | Pilot | 2.020 | 2021 | Enforcement | Improving Cybersecurity | No | No | Artificial Intelligence | G2G | x | x | https://cintesis.eu/en/portfolio-items/audit-2/ | Learning | Machine learning | Knowledge representation | 21/11/2023 | |||||||||||||||||||
| PSTW-50 | Poland - Fraud Detection COVID-19 support | https://algorithmwatch.org/en/tracers/covid-subsidies-algorithm-poland/ | AI system supporting fraud prevention. It consists in automatic verification of statements submitted in applications, mainly financial data from National Tax Administration and The Social Insurance Institution databases. Additionally, some irregularities are analyzed, e.g. too high amounts in relation to the number of employees. Among other things the system analyzes the criterion of a decline in turnover. It must be directly related to the pandemic and not, for example, to a failed business plan or a failed investment. The system will also examine what the subsidy money was spent on. - The rule is that financial subsidy money can only be used to pay for business expenses. The above mentioned information are the only available sources describing the system and were shared with the press by the Polish Development Fund which is responsible for granting subsidies. | National | Poland | PL | Polish Development Fund (PFR) | Central-Government | General public services | Executive and legislative organs, financial and fiscal affairs, external affairs. | Implemented | 2.019 | Adjudication | Taking decisions on benefits | No | No | Artificial Intelligence | G2G | x | x | x | https://opendatakosovo.org/wp-content/uploads/2021/03/ODK_alGOVrithms-2-0_report-2021_1.pdf?x54370 | Learning | Machine learning | Automated reasoning | Knowledge representation | fraud detection | 17/10/2023 | |||||||||||||||||
| PSTW-502 | LAIfeBlood - Artificial Intelligence for Blood Management | https://www.lasige.pt/project/laifeblood | The Instituto Português do Sangue e da Transplantação (IPST) is a public institute of the Ministry of Health and the recognized authority for the collection and regulation of blood donation and transplantation at the national level. Operational productivity of IPST is crucial for the blood supply chain in Portugal since it monitors the quality and safety of donation, procurement, processing, storage, preservation and distribution of human blood, blood components, organs, tissues and human origin cells. The goal of LAIfeBlood project is to provide IPST with new tools to improve the efficiency of blood supply operations in Portugal. LAIfeBlood project is particularly focused on: (1) extracting temporal and geographical patterns from historical collection and transfusion data; (2) developing predictive models for the expected collections and transfusions in different temporal and geographic areas; and (3) developing software tools to optimize the planning of collections at the national level according to the availability of IPST teams and resources and collection events. LAIfeBlood project tackles an important societal challenge of maximizing blood services effectiveness while minimizing wastage of an increasingly scarce resource and optimizing the efficiency of blood supply operations. We expect our results to be used to derive implementable policies at IPST to plan collections and manage the daily inventory rebalancing problem, as well as contributing to the development in the field of optimization and dynamic supply chain management. | National | Portugal | PT | Instituto Português do Sangue e da Transplantação (IPST) | Central-Government | Health | Public health services. | Pilot | 2.020 | 2023 | Analysis, monitoring and regulatory research | Prediction and planning | No | No | Artificial Intelligence | G2G | x | x | x | https://www.lasige.pt/project/laifeblood | Learning | Machine learning | Optimisation | Planning and Scheduling | 21/11/2023 | |||||||||||||||||
| PSTW-504 | Modelling, Prediction and Decision in the Context of Jurisprudence | https://orbi.uliege.be/bitstream/2268/252237/1/DS0220605ENN.en.pdf | This pilot project will use past court decisions to assist magistrates when receiving inquiries or documents from lawyers. It will enable faster conclusions by magistrates, thus enabling faster justice for citizens. | National | Portugal | PT | Ministry of Justice | Central-Government | Public order and safety | Law courts | Pilot | 2.020 | Internal management | Internal primary processes | No | No | Artificial Intelligence | G2G | x | x | https://orbi.uliege.be/bitstream/2268/252237/1/DS0220605ENN.en.pdf | Planning | Planning and Scheduling | Machine learning | 21/11/2023 | ||||||||||||||||||||
| PSTW-505 | SIAP - Artificial Intelligence System for detection and warning of risks on Heritage | https://alentejo.sulinformacao.pt/2021/09/drc-alentejo-e-laboratorio-hercules-organizam-palestra-sobre-sistema-de-inteligencia-artificial-para-o-patrimonio/ | The Project SIAP - Artificial Intelligence System for the detection and alert of risks on Heritage aims "the use of artificial intelligence tools for data processing to increase the effectiveness of heritage supervision services and optimize intervention strategies, through sensorization and monitoring of historical structures, enabling the early detection of potential risks contributing to increased security and sign reduction costs of intervention and maintenance'. | National | Portugal | PT | AMA (Agência para a Modernização Administrativa) | Central-Government | Recreation, culture and religion | Cultural services. | In development | 2.019 | 2021 | Analysis, monitoring and regulatory research | Information analysis processes | No | No | Artificial Intelligence | G2G | x | x | x | x | https://alentejo.sulinformacao.pt/2021/09/drc-alentejo-e-laboratorio-hercules-organizam-palestra-sobre-sistema-de-inteligencia-artificial-para-o-patrimonio/ | Learning | Machine learning | Planning and Scheduling | 21/11/2023 | |||||||||||||||||
| PSTW-506 | Decoding the Legislation | https://oecd-opsi.org/innovations/a-applied-to-the-decoding-of-law/ | The Project "Decoding the Legislation" intended to develop Artificial Intelligence tools for facilitating consultation by citizens. Repositories were implemented with data sources and metadata from the Diário da República Eletrónico (DRE) and, using natural language processing, the legal attributes are transformed into code language, and a web application was developed that allows intelligent queries to a given Law. The case studies chosen to test the AI tools are the Consumer Rights Legislation and the Retirement Statute. A proof of concept was carried out in which the DRE has an intelligent search mechanism in which Citizens can ask questions about these sets of legislation and get answers automatically. | National | Portugal | PT | Portuguese government | Central-Government | Public order and safety | Law courts | Pilot | 2.022 | Public services and engagement | Service personalisation (various) | No | No | Artificial Intelligence | G2C | x | x | x | x | x | x | x | x | https://oecd-opsi.org/innovations/a-applied-to-the-decoding-of-law/ | Communication | Natural Language Processing | Machine learning | text analysis | 21/11/2023 | |||||||||||||
| PSTW-507 | IRIS – Application of Artificial Intelligence Techniques in the Supreme Court of Justice | https://www.inesc-id.pt/projects/PR07005/ | The objective of project IRIS is twofold: on the one hand, it focus on the development of automatic summarization approaches for court decisions; on the other hand, the project aims to create a suitable representation able to be browsed in a way that is helpful in the decision process. The summarization approaches should be capable of generating technical summaries, important as an instrument for the study, processing, and dissemination of court decisions, and documents that are understandable by non-technical people. The development of a browsable representation that captures the key elements of judicial proceedings will ease the complex task of analysing these type of documents, augmenting the support for the decision process. | National | Portugal | PT | Supremo Tribunal de Justiça | Central-Government | Public order and safety | Law courts | Pilot | 2.020 | 2023 | Internal management | Internal support processes | No | No | Artificial Intelligence | G2G | x | x | https://www.inesc-id.pt/projects/PR07005/ | Communication | Natural Language Processing | Machine learning | text analysis | 21/11/2023 | ||||||||||||||||||
| PSTW-508 | BALCAT – Project on ballistics analysis | https://www.ama.gov.pt/documents/24077/231757/7.+Projeto+Balcat+a+Intelig%C3%AAncia+Artificial+ao+servi%C3%A7o+da+Pol%C3%ADcia+Cient%C3%ADfica.pdf/e6bacd04-5c51-48d5-8a28-9b108614e05e | This project will aim to create a database for ballistics forensic analysis. In the case of a serious crime, collected evidence (i.e.information about the weapon’s owner) is essential for the investigation. A proper database for identifying the owner and other information based on the weapon’s registration will be easily accessible to police authorities. Thanks to the tool they would be able to access the information and the analysis almost immediately | National | Portugal | PT | AMA (Agência para a Modernização Administrativa) | Central-Government | Public order and safety | Law courts | In development | 2.019 | 2021 | Internal management | Internal support processes | No | No | Artificial Intelligence | G2G | x | x | Learning | Machine learning | Knowledge representation | 21/11/2023 | ||||||||||||||||||||
| PSTW-509 | MEData - AI tools to define a strategy for predicting the behavior of Measurement Instruments | https://www.ama.gov.pt/web/agencia-para-a-modernizacao-administrativa/mais-ap | Development of Artificial Intelligence tools to define a strategy for predicting the behavior of Measurement Instruments - MEData. | National | Portugal | PT | AMA (Agência para a Modernização Administrativa) | Central-Government | General public services | General services. | In development | 2.019 | 2021 | Internal management | Internal support processes | No | No | Artificial Intelligence | G2B | x | x | Planning | Planning and Scheduling | Knowledge representation | 21/11/2023 | ||||||||||||||||||||
| PSTW-510 | Artificial Intelligence Prototype-SAF | https://www.ama.gov.pt/web/agencia-para-a-modernizacao-administrativa/mais-ap | Artificial Intelligence Prototype-SAF | National | Portugal | PT | AMA (Agência para a Modernização Administrativa) | Central-Government | General public services | General services. | Pilot | 2.019 | 2019 | Public services and engagement | Service integration (various) | No | No | Artificial Intelligence | G2G | x | x | x | x | Learning | Machine learning | AI Services | 22/11/2023 | ||||||||||||||||||
| PSTW-511 | PredictERPgDoc - Integration of ERP and IPB's docs management system for predictive decision making | https://si.a3es.pt/sia3es/doc/RetrieveDocument/document?docHASH=4ICttRPiklY%3D | PredictERPgDoc - Integration of ERP and IPB's document management system for predictive decision making. | National | Portugal | PT | AMA (Agência para a Modernização Administrativa) | Central-Government | General public services | General services. | Pilot | 2.019 | 2020 | Public services and engagement | Service integration (various) | No | No | Artificial Intelligence | G2G | x | x | x | Reasoning | Automated reasoning | Planning and Scheduling | 22/11/2023 | |||||||||||||||||||
| PSTW-512 | GeADAPTalks – Intel service | https://www.simplex.gov.pt/app/files/13c429b1b502e3899671afb1586c63c7.pdf | Application of artificial intelligence tools to improve and always make available service in its various aspects for participants in evaluation processes. | National | Portugal | PT | AMA (Agência para a Modernização Administrativa) | Central-Government | Economic Affairs | General economic, commercial and labour affair | Pilot | 2.019 | 2021 | Public services and engagement | Engagement management | No | No | Artificial Intelligence | G2C | x | x | Communication | Natural Language Processing | Machine learning | Audio processing | speech recognition | 22/11/2023 | ||||||||||||||||||
| PSTW-513 | PAGIRAA - Analytical Platform for the Intelligent Management of Water Supply Networks | https://www.adnorte.pt/pt/comunicacao/noticias/?id=69&idn=534 | PAGIRAA - Analytical Platform for the Intelligent Management of Water Supply Networks | National | Portugal | PT | AMA (Agência para a Modernização Administrativa) | Central-Government | Housing and community amenities | Water supply. | Implemented | 2.019 | 2020 | Analysis, monitoring and regulatory research | Monitoring policy implementation | No | No | Artificial Intelligence | G2B | x | x | Reasoning | Automated reasoning | Optimisation | 22/11/2023 | ||||||||||||||||||||
| PSTW-514 | LAB BUPi - Creation of the Single Counter Laboratory Simplified Cadastral Information System | https://bupi.gov.pt/en/pilot-project/ | The reform shall consist of a pilot project for the creation of a simplified national cadastral information system which shall identify the land structure and land ownership of rural territories, the entry into operation of the Land Cover Monitoring System (SMOS) and the development of the BUPi (Digital Land Registry) platform, a physical and virtual counter with geo-referenced information on properties, that shall aggregate the information necessary for their registration and shall facilitate citizens’ interaction with the public administration within the scope of the land register. The reform also sets up the necessary legal framework to operationalise Investment RE-C08-i02: Rural property registry and Land Cover Monitoring System . | National | Portugal | PT | AMA (Agência para a Modernização Administrativa) | Central-Government | Housing and community amenities | Housing development. | Pilot | 2.019 | 2020 | Internal management | Internal primary processes | No | No | Artificial Intelligence | G2C | x | x | x | x | x | Communication | Natural Language Processing | Planning and Scheduling | text analysis | 22/11/2023 | ||||||||||||||||
| PSTW-52 | Govbot - Administrative search engine for citizens' enquiries | https://service.wirtschaft.nrw/ | GovBot which is in use with the administrative search engine of the administration of the German State North Rhine-Westphalia. The search engine for administrative matters guarantees citizens easy and clear access to information. It indexes all websites of the state of North Rhine-Westphalia, the regional associations, many chambers, all districts and municipalities of the state of North Rhine-Westphalia and thus accesses over 12 million individual websites in a search index. Using their own search interface, users can search for administrative terms and problems, are pointed out to correct administrative terms with search word recommendations and, if necessary, are given specific responsibilities for a problem. The full text search result - broken down by administrative level - completes the offer, with a map section showing the specific location of the relevant authority. https://www.verwaltungssuchmaschine.nrw/ | Regional | Germany | DE | Ministerium für Inneres und Kommunales des Landes Nordrhein-Westfalen | Central-Government | General public services | Executive and legislative organs, financial and fiscal affairs, external affairs. | Implemented | 2.017 | Internal management | Internal support processes | No | No | Artificial Intelligence | G2C | x | x | x | x | https://publicplan.de/projekt/verwaltungssuchmaschine-nrw | Communication | Natural language processing | Searching | chatbot | 17/10/2023 | |||||||||||||||||
| PSTW-522 | IVDP DATA+ - AI models for processing relevant data for the economy of the Douro Wine Region. | https://datamais.ivdp.pt/ | The IVDP DATA+ project is based on the development of a new model of experimentation in close collaboration with the scientific community promoting knowledge transfer and adopting the advanced tools and techniques of artificial intelligence and data science. The implementation of the AI model will support decision-making based on the processing of existing data. | National | Portugal | PT | AMA (Agência para a Modernização Administrativa) | Central-Government | Economic Affairs | Agriculture, forestry, fishing and hunting | Pilot | 2.019 | 2021 | Analysis, monitoring and regulatory research | Information analysis processes | No | No | Artificial Intelligence | G2B | x | x | x | https://datamais.ivdp.pt/ | Planning | Planning and Scheduling | Machine learning | 22/11/2023 | ||||||||||||||||||
| PSTW-523 | i-Territory – Intelligent Modeling of Territorial Access to Services of General Interest | https://www.ama.gov.pt/web/agencia-para-a-modernizacao-administrativa/mais-ap | i-Territory – Intelligent Modeling of Territorial Access to Services of General Interest | National | Portugal | PT | AMA (Agência para a Modernização Administrativa) | Central-Government | Environmental Protection | Environmental protection n.e.c. | In development | 2.019 | 2021 | Analysis, monitoring and regulatory research | Prediction and planning | No | No | Artificial Intelligence | G2G | x | x | Planning | Planning and Scheduling | Machine learning | 22/11/2023 | ||||||||||||||||||||
| PSTW-524 | SegnalaCI - Transparent management of citizen reports about City status | https://segnalazioni.comune.genova.it/ | The administration takes charge of the report, informs the competent office and resolves the problem (eg: repair the hole, empty the trash) .At the end of the procedure, the citizen receives a notification on the outcome of his report. Artificial Intelligence (Machine Learning) is used to elaborate gathered data and provide a smart dashboard to city administrators helping the staff and resource planning | Local | Italy | IT | Municipality of Genoa | Local Government | General public services | General services. | Implemented | 2.021 | Internal management | Internal support processes | No | Yes | Artificial Intelligence | G2C | x | x | x | x | x | https://smart.comune.genova.it/notizie/segnalaci | Planning | Planning and Scheduling | Machine learning | 22/11/2023 | |||||||||||||||||
| PSTW-525 | Brain4it : monitoring the SmartCity | http://brain4it.org/project_vehicle_stats.html | Brain4it is an open source software, an expert system, designed by the City Council of Sant Feliu de Llobregat to automate the City-Os infrastructures management, as well as to develop other artificial intelligence (AI) applications for the Internet of Things. It runs as a network service that provides a REST API (Representational State Transfer Application Programming Interface) which allows to control and program the City-Os platform remotely using a functional language that facilitates the implementation of expert systems and machine learning applications. Likewise, it develops all those use cases that a Smart City may need, managing security, data governance and with a modular and adaptable orientation. | Local | Spain | ES | City Council of Sant Feliu de Llobregat | Local Government | General public services | General services. | Implemented | 2.021 | Internal management | Internal support processes | No | No | Artificial Intelligence | G2G | x | x | https://joinup.ec.europa.eu/collection/joinup/solution/brain4it/about | Planning | Planning and Scheduling | Machine learning | internet of things | 22/11/2023 | |||||||||||||||||||
| PSTW-53 | Skala - Predictive policing | https://lafp.polizei.nrw/sites/default/files/2018-07/180628_Abschlussbericht_SKALA.PDF | The State Criminal Police Office (LKA) of North Rhine-Westphalia, for example, has been using the “Skala” software since 2015, a system for evaluating crime and anticipating situations. Skala uses past experiences, such as the near-repeat theory. Once a week, Skala spits out forecasts of residential burglaries for police authorities in Bonn, Duisburg, Dusseldorf, Essen, Gelsenkirchen, and Cologne – maps showing residential districts with a high probability of burglary. The police use the forecasts to decide, for example, where to send more patrol cars and whether to personally advise the population in vulnerable areas on burglary protection. At the beginning of May 2018, NRW Minister of the Interior Herbert Reul announced that it would extend its deployment to the whole of North Rhine-Westphalia, initially to all main crime departments. | Regional | Germany | DE | State Criminal Police Office (LKA) of North Rhine-Westphalia | Local Government | Public order and safety | Police Services | Implemented | 2.016 | Enforcement | Predictive enforcement processes | No | No | Artificial Intelligence | G2G | x | x | x | https://lafp.polizei.nrw/sites/default/files/2018-07/180628_Abschlussbericht_SKALA.PDF | Learning | Machine learning | Knowledge representation | Planning and Scheduling | 17/10/2023 | ||||||||||||||||||
| PSTW-532 | Genome representation and artificial intelligence | https://www.csipiemonte.it/en/project/genome-representation-and-artificial-intelligence | CSI, together with the University of Turin (Department of Medical Sciences - Medical Genetics for genomic data analysis and nephrolology field, Department of Clinical and Biological Sciences - Nephrology for the clinical scope related to the management of rare diseases), ISI Foundation and GenomSys company, is working on a research project that can help in the diagnosis and treatment of rare diseases: the project uses advanced technologies for the rapid and effective reading of the genome and develops artificial intelligence algorithm to analyse genetic data and provide information for the design of targeted diagnosis and treatment pathways. | Regional | Italy | IT | CSI Piemonte (Inhouse ICT of Regione Piemonte) | Regional Government | Health | R&D health. | In development | 2.021 | Public services and engagement | Service personalisation (various) | No | No | Artificial Intelligence | G2C | x | x | x | x | www.csipiemonte.it | Learning | Machine learning | Knowledge representation | 22/11/2023 | ||||||||||||||||||
| PSTW-533 | Citizen Conversational AI Platform | https://www.csipiemonte.it/en/project/citizen-conversational-ai-platform | Bots (short for robots) that perform automatic tasks, repeating the operations performed by a user, are widely used. Chatbots, i.e. programs with a "conversational" User Experience, are now becoming the new reality in technologies for "man-machine" interaction. To make a chatbot able to understand, respond to requests and propose solutions using everyday natural language, it is necessary to introduce very innovative context management and artificial intelligence technologies. Three prototypes were produced with the goal of: 1) engineering and automating the production of bots, to quickly implement new services; 2) improve effectiveness by inserting conversation patterns, e.g. fluid conversation mechanisms, with current speech memory and list references. For instance, CSI made prototypes useful for searching for general practitioners and pediatricians of the Piedmont Region on Alexa and Google Home, with refinement of the search. | Regional | Italy | IT | CSI Piemonte (Inhouse ICT of Regione Piemonte) | Regional Government | General public services | General services. | In development | 2.019 | 2020 | Public services and engagement | Service personalisation (various) | No | Yes | Artificial Intelligence | G2C | x | x | x | www.csipiemonte.it | Communication | Natural language processing | Machine learning | Audio processing | speech recognition | 22/11/2023 | ||||||||||||||||
| PSTW-535 | DARE: Digital Environment for collaborative Alliances to Regenerate urban Ecosystems in middle-sized cities | https://www.hpc.cineca.it/projects/dare | DARE wants to demonstrate the effectiveness of an innovative digital-based and citizen-centred governance approach, aimed at facilitating, supporting & fastening the implementation & evaluation of the darsena (ravenna) urban regeneration process, to be replied in other eu middle-sized cities. The dare approach proposes: a) the creation of a 3-layers digital environment, composed by dmp (data layer), cms (editorial layer) and vir-virtual realm (presentation layer), intended as the enabling technology needed to activate urban actors; b) the innovation of the public administration role, called to act as process enabler. This change asks for the creation of a new level of management, that is the process organizers team, which will connect strategy (policy), opportunities (economical world) & needs (citizens); c) the widespread of digital culture among citizens to accompany them in becoming digital aware city changers. | Regional | Italy | IT | Municipality of Ravenna | Local Government | General public services | General services. | Pilot | 2.019 | 2022 | Public services and engagement | Service integration (various) | No | Yes | Artificial Intelligence | G2C | x | x | https://www.darsenaravenna.it/objects/storytelling-from-the-uia-expert | Reasoning | Knowledge representation | Automated reasoning | Machine learning | 22/11/2023 | ||||||||||||||||||
| PSTW-536 | RainBO (follow-up of BLUEAP Bologna Urban Environment Adaptation Plan for a resilient city) | https://partecipa.rainbolife.eu/ | The overall objective is to develop and improve methods and tools to predict severe rainfall events and their impact, focusing on the hydrologic response of the small watercourses within the urban area of Bologna. The final objective is to reach a higher resilience in such watercourses, by means of a monitoring and modeling system allowing it to forecast any sudden flooding event. | Regional | Italy | IT | Lepida Spa (inhouse ICT of Regione Emilia Romagna) | Regional Government | Environmental Protection | Environmental protection n.e.c. | Pilot | 2.016 | 2018 | Analysis, monitoring and regulatory research | Prediction and planning | No | Yes | Artificial Intelligence | G2G | x | x | https://www.rainbolife.eu/en/rainbo-project | Planning | Planning and Scheduling | Optimisation | 22/11/2023 | |||||||||||||||||||
| PSTW-54 | VDA - Voicebot on calls from Irish taxpayer on tax clearance | https://www.youtube.com/watch?v=k9KUCq3Fdi8 | In 2018, Irish Revenue Commissioners began investigating the potential of Artificial Intelligence to provide a more efficient, effective experience for customers using their telephony services. This resulted in the implementation of a Virtual Digital Agent (VDA) designed to focus on a subset of calls from the Irish taxpayer relating to tax clearance. 1) taxpayers contact Irish Revenue tax clearance customer support asking how to apply for tax clearance; 2) enquiring what their current tax clearance status is; 3) requesting more information on expired, refused & rescinded tax clearance applications as well as just looking for information on tax clearance itself. Result is up to 50% of calls were handled from start to finish by the voicebot, 70% of first-time applicants engaged by voicebot submitting their application, 75% of tax clearance holders were able to retrieve their tax clearance access number (TCAN). Only in 10% of the calls, the calls were transferred to a human operator. | National | Ireland | IE | Irish Revenue Commissioners | Central-Government | General public services | Executive and legislative organs, financial and fiscal affairs, external affairs. | Implemented | 2.018 | Public services and engagement | Engagement management | No | No | Artificial Intelligence | G2C | x | x | x | https://www.youtube.com/watch?v=k9KUCq3Fdi8 | Communication | Natural language processing | Machine learning | Audio processing | voice assistant | 17/10/2023 | |||||||||||||||||
| PSTW-541 | ConsolONE: proactive monitoring and management system for real-time control of all company resources | https://consolone.com/ | This solution is available on the data catalogue of AgID. Proactive monitoring and management system for real-time control of all company resources, understood as technological infrastructures (IT, BMS, IoT, Environmental Control, DCIM, Asset Management, Traceability), in a reliable, intuitive and integrated way. Functionalities include: Monitoring and proactive IT infrastructure management; Integration and management of BMS (Building Management System) and home automation systems; Monitoring and proactive management of IoT sensors of different technologies and protocols (IP, Radio frequency 868Mhz, LoraWan, Narrow Band); Monitoring and proactive management of Environmental Control systems; Monitoring and proactive management of on-Premise, Cloud, Hybrid Cloud Data Center systems; Management and Control, in real time, of all company assets (such as PC, Server, MAC, Tablet, Smartphone, etc.); Traceability of Vehicles and People within the company for control purposes for Security & Safety. | National | Italy | IT | AGID (Agenzia per Italia Digitale) | Central-Government | General public services | General services. | Implemented | 2.021 | Analysis, monitoring and regulatory research | Information analysis processes | No | Yes | Artificial Intelligence | G2B | x | x | https://catalogocloud.agid.gov.it/show/all | Reasoning | Automated reasoning | Machine learning | 22/11/2023 | ||||||||||||||||||||
| PSTW-542 | IBM Watson Content Hub | https://catalogocloud.acn.gov.it/service/381 | IBM Watson Content Hub (WCH) centrally manages web content and digital assets with a simple and intuitive UI. Integrated with AI services provided by IBM Watson for automatic asset tagging, it includes a rich set of APIs both for the editorial part and for the use of the content model, making it the ideal tool to feed any digital channel (via Akamai CDN, included). Native use of IBM Watson AI services to simplify business activity in effectively cataloging and searching for digital content and assets SOLR-based search engine for assets and content and ability to manage the size and rendition of images for optimal omni-channel management The rich set of REST APIs guarantees consistent reuse and ensures a consistent presence on all digital channels, together with integration with IBM (natively) and third-party solutions Reduction of operating costs related to the SaaS nature of the service and delivery operated through Akamai's Content Delivery Network platform IBM periodically updates and enriches the service and takes care to maintain the correct levels of security | National | Italy | IT | AGID (Agenzia per Italia Digitale) | Central-Government | General public services | General services. | Implemented | 2.021 | Internal management | Internal primary processes | No | Yes | Artificial Intelligence | G2G | x | x | https://catalogocloud.agid.gov.it/show/all | Reasoning | Automated reasoning | Machine learning | Knowledge representation | 22/11/2023 | |||||||||||||||||||
| PSTW-546 | LombardiaInforma: proactive Citizen Communication | https://developers.italia.it/it/software/r_lombar-regionelombardia-lombardiainforma | This solution regards the management and sending of personalized communications, in a multi-channel and multi-service logic, to support the daily work of spreading the contents of an editorial staff. For this purpose, the application adopts a logical architecture and an Omnichannel Customer Experience platform which, through a public portal called Lombardia Informa, allows you to: collect the contact data of citizens and the topics of interest in a centralized manner; create and manage personalized and multi-channel communication actions offering a unique and coherent browsing experience; integrate the systems responsible for sending communications, implementing harmonization and centralization of data from heterogeneous channels; create integrated communication tools, such as landing pages and surveys; enrich the contents with multimedia elements (image slideshows, videos) and documents (.pdf attachments) user management and profiling as per GDPR. | Regional | Italy | IT | Regione Lombardia | Regional Government | General public services | General services. | Implemented | 2.021 | Public services and engagement | Engagement management | No | Yes | Artificial Intelligence | G2C | x | x | https://developers.italia.it/ | Reasoning | Automated reasoning | Machine learning | 23/11/2023 | ||||||||||||||||||||
| PSTW-547 | YUCCA-Smart Data Platform | https://developers.italia.it/it/software/r_piemon-yucca-sdp-yucca-sdp | Yucca Smart Data Platform is an open and pre-competitive cloud platform available for private and public entities that offers tools to experiment and create innovative technological solutions related to the world of data. It is a system that aggregates data from the Internet of Things (cameras, sensors, weather stations), from the Internet of People (e.g. tweets) and public and private data, provides for the selective sharing of the information collected, allows the self-service data processing in real-time and advanced data analysis tools and supports the display of information (data and metadata) via API. The platform offers functionality to create new value-added information and enables the creation of end-to-end solutions on a variety of themes. | Regional | Italy | IT | Regione Piemonte | Regional Government | General public services | General services. | Implemented | 2.021 | Public services and engagement | Data Sharing Management | No | Yes | Artificial Intelligence | G2B | x | x | x | https://developers.italia.it/ | Learning | Machine learning | Knowledge representation | Searching | internet of things | 23/11/2023 | |||||||||||||||||
| PSTW-548 | CityFlows-Barcelona | https://cityflows-project.eu/barcelona/ | CityFlows is an EIT Urban Mobility flagship project bringing together a diverse consortium of partners to launch a state-of-the-art Crowd Management Decision-Support System (CM-DSS) to improve the safety and comfort of busy pedestrian spaces. The recent launch of City Analytics, a start-up licensing the CityFlows CM-DSS software to government authorities, represents a major project milestone. City Analytics will boost the quality of pedestrian spaces, a timely development as cities look for reliable tools that can help them respond to the Corona crisis | Local | Spain | ES | Municipality of Barcelona | Local Government | Public order and safety | Public order and safety n.e.c. | Pilot | 2.018 | 2022 | Analysis, monitoring and regulatory research | Prediction and planning | No | No | Artificial Intelligence | G2G | x | x | https://cityflows-project.eu/ | Planning | Planning and Scheduling | Machine learning | 23/11/2023 | |||||||||||||||||||
| PSTW-549 | CityFlows-Milano | https://cityflows-project.eu/milan/ | CityFlows is an EIT Urban Mobility flagship project bringing together a diverse consortium of partners to launch a state-of-the-art Crowd Management Decision-Support System (CM-DSS) to improve the safety and comfort of busy pedestrian spaces. The recent launch of City Analytics, a start-up licensing the CityFlows CM-DSS software to government authorities, represents a major project milestone. City Analytics will boost the quality of pedestrian spaces, a timely development as cities look for reliable tools that can help them respond to the Corona crisis. | Local | Italy | IT | Municipality of Milan | Local Government | Public order and safety | Public order and safety n.e.c. | Pilot | 2.018 | 2022 | Analysis, monitoring and regulatory research | Prediction and planning | No | No | Artificial Intelligence | G2G | x | x | https://cityflows-project.eu/ | Planning | Planning and Scheduling | Machine learning | 23/11/2023 | |||||||||||||||||||
| PSTW-55 | The Dublin Beat - Citizen opinion analysis | https://smartdublin.ie/the-dublin-beat-understanding-citizen-sentiment/ | The Dublin Beat analyses citizen opinions in the Dublin Region for an overview of their most pressing concerns. Each month public tweets are collated by the AItext analytics platform Citibeats, whose Artificial Intelligence algorithms have been trained for understanding opinions in the local context of Dublin, assisting local authorities to better understand how local people feel about civic issues. The resulting analysis based on the gathered online data is presented via visual dashboards and through monthly reports provided online. The different reports give an overview of key issues such as how people feel about environmental issues, cultural events or city region developments expressed on the online media. The Dublin Beat can help local authorities to better understand how citizens feel about key issues and ensure that civic efforts and policy reflect the needs of communities. Local authorities employ other methods to ensure truly inclusive citizen engagement. | Local | Ireland | IE06 | Municipality of Dublin | Local Government | General public services | R&D general public services. | Implemented | 2.020 | Public services and engagement | Service personalisation (various) | No | No | Artificial Intelligence | G2C | x | x | x | x | x | x | x | https://smartdublin.ie/smart-dublin-explores-how-ai-social-media-can-help-improve-the-city-region/ | Learning | Machine learning | Natural language processing | sentiment analysis | 17/10/2023 | ||||||||||||||
| PSTW-556 | Smart Dementia project | https://tropico-project.eu/cases/administration-costs-for-bureaucracy/smart-dementia-project-the-netherlands/ | The eHealth technology (a wristwatch and app with which the whereabouts of the patients can be traced) is used to provide elderly people with Alzheimer more freedom. The technology enables the nurses and the institution to trace the elderly better, thus giving them more freedom to move around. The technology fits in a policy of the organisation to work with life cycles. This means that a team decides how much freedom a specific patient can have. The aim is to grant as much freedom as possible, given the patient health and mental situation. If people can move around more, they stay fit longer both physically and mentally, the organisation argues. The organisation also emphasizes that the ICT tool is above all a supportive tool and that the most important element still is the (risk) assessment of the patient. The eHealth innovation was an example of how such technologies can support health professionals, as personal health data is collected, stored and communicated between relevant stakeholders. In general, in health technology, patient data is used to provide more precise and personalized health care (e.g. personalized interventions, predicating and preventing diseases). In this specific case of health technology, a mobile device, mobile sensor, and wearables were used to increase the health and wellbeing of users. This device with sensor technology helps Alzheimer patients to walk around more freely again in a nursing home and outside the nursing home through GPS tracking, which would otherwise be impossible for those suffering from dementia. In that sense, the ICT technology is important and vital for the innovation. | Local | Netherlands | NL | Tante Louise | Local Government | Health | Public health services. | Pilot | 2.021 | Public services and engagement | Service integration (various) | No | No | Artificial Intelligence | G2C | x | x | https://tropico-project.eu/case-studies/ | Perception | Audio processing | Machine learning | 23/11/2023 | ||||||||||||||||||||
| PSTW-557 | Track AI | https://dive-medical.com/trackai/ | The objective of the Track AI project is to incorporate artificial intelligence (AI) into the DIVE medical device so it can “estimate the probability of the patient having a certain pathology”. The innovation was created due to the difficulty in exploring the visual function (e.g. vision) among children, but it can be used for both collaborative and non-collaborative patients (i.e. patients who are able to collaborate with physicians as opposed to patients – such as children – who are unable to collaborate with physicians). The partnership allows technology to be shared between organisations and combines their experience in the health and technological fields. The innovation in this project consists of the development of a specific app that uses AI in a Huawei P30 mobile phone in order to analyse data from visual explorations using the DIVE-Medical device. This innovation helps physicians to determine whether or not a patient has a visual impairment by comparing patient gaze patterns with the database generated by previous diagnoses (which can be accessed online and offline). In some cases, it also makes it possible to estimate the probability of a particular pathology. The project is focused on non-collaborative patients, but it can also be used in collaborative patients (i.e. patients that are able to collaborate with physicians as opposed to patients – such as children – who are unable to collaborate with physicians). | Local | Spain | ES2 | Miguel Servet Hospital (Zaragoza, Spain) | Local Government | Health | Public health services. | Pilot | 2.018 | 2019 | Public services and engagement | Service personalisation (various) | No | No | Artificial Intelligence | G2C | x | x | https://tropico-project.eu/case-studies/ | Perception | Computer vision | Machine learning | 23/11/2023 | |||||||||||||||||||
| PSTW-558 | MasterMind - Basque Country | https://tropico-project.eu/cases/administration-costs-for-bureaucracy/mastermind-spain/ | The objective of the MasterMind project was “to make high quality treatment for depression more widely available for adults suffering from the illness by the use of ICT” (http://mastermind-project.eu). Collaboration by 23 partners framed in a European H2020 project was created in order to accomplish this objective. The innovation in this project was a Computerised Cognitive Behaviour Therapy (CCBT) for patients with mild and moderate depression. It allows people with these illnesses to receive distance therapy, involving fewer face-to-face appointments with health professionals. The main component of the innovation is a web application “Overcome your depression”, which can be used through a computer, tablet or smartphone. By using this application, patients can receive therapy in six modules in the form of text, videos, images, graphs, etc. The application makes patients perform tests, which then serve to communicate the evolution of their illness to the health professionals. The health professionals check these tests periodically and receive an alarm if a patient’s results are a cause for concern. | Local | Spain | ES2 | Osakidetza (Servicio Vasco de Salud/Basque Health System) | Local Government | Health | Public health services. | Pilot | 2.015 | 2017 | Public services and engagement | Service personalisation (various) | No | No | Artificial Intelligence | G2C | x | x | x | https://tropico-project.eu/case-studies/ | Reasoning | Knowledge representation | Automated reasoning | 23/11/2023 | ||||||||||||||||||
| PSTW-559 | MasterMind - Southern Denmark | https://tropico-project.eu/cases/administration-costs-for-bureaucracy/mastermind-spain/ | The objective of the MasterMind project was “to make high quality treatment for depression more widely available for adults suffering from the illness by the use of ICT” (http://mastermind-project.eu). Collaboration by 23 partners framed in a European H2020 project was created in order to accomplish this objective. The innovation in this project was a Computerised Cognitive Behaviour Therapy (CCBT) for patients with mild and moderate depression. It allows people with these illnesses to receive distance therapy, involving fewer face-to-face appointments with health professionals. The main component of the innovation is a web application “Overcome your depression”, which can be used through a computer, tablet or smartphone. By using this application, patients can receive therapy in six modules in the form of text, videos, images, graphs, etc. The application makes patients perform tests, which then serve to communicate the evolution of their illness to the health professionals. The health professionals check these tests periodically and receive an alarm if a patient’s results are a cause for concern. | Regional | Denmark | DK03 | Region of Southern Denmark | Regional Government | Health | Public health services. | Pilot | 2.015 | 2017 | Public services and engagement | Service personalisation (various) | No | No | Artificial Intelligence | G2C | x | x | https://tropico-project.eu/case-studies/ | Reasoning | Knowledge representation | Automated reasoning | 23/11/2023 | |||||||||||||||||||
| PSTW-56 | Project PIERINO (Platform for the Extraction and Retrieval of Online Information) | https://dh.fbk.eu/news/collaboration-miur | The Pierino project (PIattaforma for the Extraction and Retrieval of Online Information) was curated by the Digital Humanities research group of the Bruno Kessler and Tommaso Caselli Foundation of the Vrije Universiteit Amsterdam and led to the creation of a platform for the automatic analysis of linguistic data, which works through AI techniques of semantic analysis and modules for the automatic processing of natural language. The platform was used for the first time by the Ministry of Education to analyze the data of the public consultation "La buona scuola" and made it possible to process and synthesize 270 thousand comments in less than a week, making it possible to significantly reduce analysis times questionnaires. The platform has been designed in such a way as to be as flexible as possible to quickly process data from future consultations. | National | Italy | IT | Ministry of Education | Central-Government | Education | R&D education. | Pilot | 2.014 | Analysis, monitoring and regulatory research | Information analysis processes | No | No | Artificial Intelligence | G2C | x | x | x | https://dh.fbk.eu/news/collaboration-miur | Communication | Natural language processing | Knowledge representation | text analysis | 17/10/2023 | ||||||||||||||||||
| PSTW-561 | Trentino Salute 4.0: TREC+ | https://trec.trentinosalute.net/ | TreC + consolidates and puts into service the trials that have been tested in recent years in Trentino together with citizens and health professionals. Access to online health services is guaranteed by a single platform and a single app in which a constant exchange of data produced by patients and doctors flows and in which the level of care that is offered to citizens remains unchanged, constant and Safe. It integrates the innovative vision for the Artificial Intelligence of the future with the collaboration wiith FBK research center. The design and experimenting of the part of TreC + that wants to become increasingly intelligent and integrated with applications such as virtual coaches, predictive models, chatbots, etc., which use artificial intelligence has been made with FBK research center. The TreC + ecosystem is based on Open Source technologies and thanks to an open architectural model it is possible to connect proprietary tools and solutions while keeping the health data at the center of the system, rigorously kept in the APSS archives and under public control, so as to guarantee the citizen security, protection and full availability of data concerning him. Thanks to the system specifications, the solution developed by APSS is now reusable in other healthcare contexts (regional / provincial / ASL and hospitals). It can be integrated with the management systems in use at other regional healthcare companies (CUP, FSE, Payments, existing telemonitoring systems), thus activating a television service extended to the entire population. | Local | Italy | ITH20 | Provincia Autonoma di Trento | Local Government | Health | Public health services. | Implemented | 2.021 | Public services and engagement | Data Sharing Management | No | No | Artificial Intelligence | G2C | x | x | x | x | x | https://www.ufficiostampa.provincia.tn.it/Comunicati/Nuovo-portale-e-nuova-app-TreC | Learning | Machine learning | Planning and Scheduling | chatbot | 23/11/2023 | ||||||||||||||||
| PSTW-562 | KEYCRIME: Crime Analysis for the next generation Predictive Policing | https://www.poliziadistato.it/statics/16/la-chiave-del-crimine.pdf https://www.youtube.com/watch?v=DvpzULSfyOs | With Keycrime, the software created by a policeman from the Milan police headquarters to analyze thefts and robberies committed in the city. Recently this has been trasformed in a new company with the same name and the software named Delia. Delia is a software from the KeyCrime company that supports police officers in crime prevention and enforcement operations. By analyzing thousands of data, the aim is to compare different crimes to determine which ones were committed by the same person or by the same group of people. Software has been tested in production in Italy by the State Police in Milan, to combat the phenomenon of robberies. | Local | Italy | ITC4C | Polizia di Stato - Questura di Milano | Local Government | Public order and safety | Police Services | Implemented | 2.021 | Enforcement | Predictive enforcement processes | No | No | Artificial Intelligence | G2G | x | x | https://milano.corriere.it/notizie/cronaca/18_aprile_10/milano-programma-anti-rapine-diventa-startup-sicurezza-a355ba22-3c81-11e8-87b2-a646d975b0f5.shtml | Reasoning | Knowledge representation | Automated reasoning | 23/11/2023 | ||||||||||||||||||||
| PSTW-564 | Shareart: measure the public's satisfaction in front of the works of art exhibited in museum | https://www.privacy-network.it/wp-content/uploads/2021/11/MET-P000-019.pdf | ShareArt is the monitoring system through which it would be possible to measure the public's satisfaction in front of the works of art exhibited in museums, tested by the Sustainability Department of Production and Territorial Systems of ENEA in collaboration with the Bologna Museums Institution. This software works through a camera that automatically detects the faces that look in the direction of the work and allows the system to acquire data concerning people and information related to their behavior during the observation of the work of art. Through the use of Big Data and convolutional neural networks, the system is able to correlate the data referable to the fruition of the works with those relating to the characteristics of people to infer useful information. | Local | Italy | IT | Istituzione Bologna Musei | Local Government | Recreation, culture and religion | Cultural services. | Implemented | 2.021 | Analysis, monitoring and regulatory research | Information analysis processes | No | No | Artificial Intelligence | G2G | x | x | https://www.ansa.it/osservatorio_intelligenza_artificiale/notizie/societa/2021/06/10/musei-shareart-monitora-comportamenti-ed-emozioni-pubblico_78b7a7e8-bcdc-4556-98da-7cf255b655c0.html | Perception | Computer vision | Machine learning | action recognition | 23/11/2023 | |||||||||||||||||||
| PSTW-566 | SARI (Automatic Image Recognition System) | https://www.poliziadistato.it/articolo/15557c52775a3724103220539 | SARI (Automatic Image Recognition System) is a facial recognition software, in use at the Ministry of the Interior and Central Anti-Crime Directorate of the State Police since 2017. The software is produced and supplied to the Ministry by the company Parsec 3.26 S.r.l. The SARI system consists of two components: SARI Enterprise and SARI Real-Time. The first component aims to facilitate the search and identification of people, starting from images of the face already in possession of the Police database. The second is a facial recognition software, which thanks to the use of cameras can recognize people on a watch-list in real time. | National | Italy | IT | Ministero dell'Interno | Central-Government | Public order and safety | Police Services | Implemented | 2.017 | Enforcement | Smart Recognition processes | No | No | Artificial Intelligence | G2G | x | x | x | https://www.privacy-network.it/osservatorio/sari/#1609329358169-37006cf1-d21e | Perception | Computer vision | Machine learning | face recognition | 23/11/2023 | ||||||||||||||||||
| PSTW-57 | Borbot - Virtual assistant for museums | https://intelligenzartificiale.unisal.it/borbot-il-chatbot-a-servizio-dei-turisti/ | Borbot (acronym for Bourbons and Robotics) is a virtual assistant, adopted by the National Museum of the Royal Palace of Caserta, which through machine learning techniques is able to answer user questions, providing detailed tourist information and news about the monument. The mobile system supports the Museum's front office service and allows customer service staff to concentrate on the services with greater added value. | Local | Italy | IT | Reggia di Caserta | Local Government | Recreation, culture and religion | Cultural services. | Implemented | 2.017 | Public services and engagement | Service personalisation (various) | No | No | Artificial Intelligence | G2C | x | x | x | https://intelligenzartificiale.unisal.it/borbot-il-chatbot-a-servizio-dei-turisti/ | Communication | Natural language processing | Machine learning | chatbot | 17/10/2023 | ||||||||||||||||||
| PSTW-571 | AI Robort Judge for small claims in Estonia | https://aastaraamat.riigikohus.ee/en/artificial-intelligence-a-substitute-or-supporter-of-judges/ | The project want to implement a “robot judge” that could adjudicate small claims disputes of less than €7,000 (about $8,000). Officials hope the system can clear a backlog of cases for judges and court clerks. The project is in its early phases and a pilot started in 2019 focusing on contract disputes. In concept, the two parties will upload documents and other relevant information, and the AI will issue a decision that can be appealed to a human judge. Many details are still to be worked out. Velsberg says the system might have to be adjusted after feedback from lawyers and judges. | National | Estonia | EE | Estonian Ministry of Justice | Central-Government | Public order and safety | Law courts | Pilot | 2.019 | Enforcement | Predictive enforcement processes | No | No | Artificial Intelligence | G2C | x | x | x | x | x | https://www.wired.com/story/can-ai-be-fair-judge-court-estonia-thinks-so/ | Communication | Automated reasoning | Robotics and Automation | 28/11/2023 | |||||||||||||||||
| PSTW-576 | Sentilo BCN - Plataforma de Sensors i Actuadors de Barcelona | https://connecta.bcn.cat/connecta-catalog-web/component/map https://www.researchgate.net/figure/Sentilo-Data-Collection-platform_fig2_304580274 | The Barcelona City Council, through the Municipal Institute of Informatics (IMI), started in November 2012 a project conceived for define the strategy and the necessary actions in order to achieve global positioning Barcelona as a reference in the field of Smart Cities. Sentilo is an open source sensor and actuator platform designed to fit in the Smart City architecture of any city who looks for openness and easy interoperability. It is built, used, and supported by an active and diverse community of cities and companies that believe that using open standards and free software is the first smart decision a Smart City should take. In order to avoid vertical solutions, Sentilo is designed as a cross platorm with the objective of sharing information between heterogeneous systems and to easily integrate legacy applications. | Local | Spain | ES51 | City of Barcelona | Local Government | General public services | General services. | Implemented | 2.012 | Public services and engagement | Service integration (various) | No | Yes | Artificial Intelligence | G2C | x | x | x | x | x | x | IPSO DB | Communication | Natural language processing | Machine learning | internet of things | 28/11/2023 | |||||||||||||||
| PSTW-577 | SKRINJA 2.0 - Business Intelligence in the civil service (BI) | https://nio.gov.si/nio/asset/poslovna+inteligenca+skrinja?lang=en | The ICT department of the Ministry of Public Administration implemented a data warehouse and business intelligence system that is configured as a horizontal service on Government Computer Cloud to promote data-driven decision making in public administration. The Ministry also handles the procurement activities of the country and therefore there is a prospect of utilising the system in the procurement procedures as well. | National | Slovenia | SI | Ministry of Public Administration | Central-Government | General public services | General services. | Implemented | 2.020 | Analysis, monitoring and regulatory research | Information analysis processes | No | No | Artificial Intelligence | G2B | x | x | x | x | IPSO DB | Planning | Planning and Scheduling | Knowledge representation | data analytics | 28/11/2023 | |||||||||||||||||
| PSTW-578 | ProZorro, Bid prediction | https://prozorro.gov.ua/en | The ProZorro team is using Artificial Intelligence and machine learning in its work with the aim of developing a model that would predict the likelihood of a tender happening and being succesful. Another tool is able to predict the probability that a particular tender participant will leave the platform before completing the tender. | National | Ukraine | UA | ProZorro | Central-Government | General public services | General services. | Implemented | 2.017 | Analysis, monitoring and regulatory research | Information analysis processes | No | Yes | Artificial Intelligence | G2B | x | x | x | IPSO DB | Learning | Machine learning | Planning and Scheduling | 28/11/2023 | |||||||||||||||||||
| PSTW-579 | ProZorro, CPV Prediction | https://prozorro.gov.ua/en | Prozorro has developed an AI tool that can predict the correct CPV codes and unit of measurement. The tool has not yet been implemented. It aims to make the platforms that provide the user-interface for organisations using the Prozorro data easier to use, reducing mis-classifications and errors. | National | Ukraine | UA | ProZorro | Central-Government | General public services | General services. | Implemented | 2.017 | Enforcement | Certification and validation processes | No | Yes | Artificial Intelligence | G2B | x | x | x | IPSO DB | Learning | Machine learning | Planning and Scheduling | 28/11/2023 | |||||||||||||||||||
| PSTW-58 | TALIA SF - Extract and organize knowledge coming from the analysis of textual documents | https://www.innova.puglia.it/visualizza-newsletter/-/asset_publisher/R6CJINjpYAnO/content/dal-progetto-talia-alla-machine-learning | The TALIA SF is able to extract and organize knowledge coming from the analysis of a huge quantity of textual documents produced by the projects funded by the Interreg MED Programme. This knowledge proves to be invaluable to the management of innovation policies and for the capitalization of the most successful projects results. TALIA semantic framework is handled by Innovapuglia the in-house company of the Regional Government of Apulia. | Regional | Italy | IT | Regional Government of Apulia | Regional Government | General public services | R&D general public services. | Pilot | 2.019 | Internal management | Internal support processes | No | No | Artificial Intelligence | G2G | x | x | x | x | https://www.innova.puglia.it/visualizza-newsletter/-/asset_publisher/R6CJINjpYAnO/content/dal-progetto-talia-alla-machine-learning | Reasoning | Knowledge representation | Automated reasoning | knowledge graph | 17/10/2023 | |||||||||||||||||
| PSTW-580 | DoZorro AI tool | https://ti-ukraine.org/en/news/dozorro-artificial-intelligence-to-find-violations-in-prozorro-how-it-works/ | The monitoring portal DoZorro is a platform where each participant in the system (supplier, customer, controlling authority, citizen) can provide feedback to the government customer or supplier. The new version of the platform provides software, which through its AI capabilities, is able to identify tenders with a high risk of corruption. The results of the beta test of this system were that 26% more tenders with unfounded selection of the winner were identified, 37% more tenders with groundless disqualification, and 298% more with participants' conspiracy. The system is intended to complement and support the work done by experts - making their work more efficient. | National | Ukraine | UA | ProZorro | Central-Government | General public services | General services. | Implemented | 2.018 | Enforcement | Predictive enforcement processes | No | Yes | Artificial Intelligence | G2B | x | x | IPSO DB | Communication | Natural language processing | Machine learning | text analysis | 28/11/2023 | |||||||||||||||||||
| PSTW-583 | State Treasury eInvoicing plans | https://ec.europa.eu/cefdigital/wiki/display/CEFDIGITAL/2018/06/13/Finland+is+using+AI+in+attempt+to+achieve+one-hundred+per+cent+eInvoicing | The State Treasury of Finland plans to automate eInvoice processing by utilising AI and robotics. It is believed that AI tools could analyse an invoice within seconds to find the necessary information such as an agreement number and amount. Currently, Finland has identified the most significant challenge to be that IT companies and other operators need to be aware of what data needs to be in the correct place to achieve ultimate automation goals. | National | Finland | FI | State Treasury of Finland | Central-Government | General public services | General services. | In development | 2.018 | Internal management | Internal support processes | No | No | Artificial Intelligence | G2G | x | x | IPSO DB | Reasoning | Automated reasoning | Optimisation | 28/11/2023 | ||||||||||||||||||||
| PSTW-584 | YPO, Procurement Information Provider | https://www.ukauthority.com/articles/ypo-launches-procurement-chatbot/ | YPO has introduced a chatbot - the Procurement Information Provider (PIP) to help public sector buyers navigate their way through YPO's services and discover the frameworks on offer. The chatbot can provide information from other areas of the website and direct users to relevant procurement teams. | National | United Kingdom | UK | YPO | Central-Government | General public services | General services. | Implemented | 2.018 | Public services and engagement | Service integration (various) | No | Yes | Artificial Intelligence | G2B | x | x | x | IPSO DB | Communication | Natural language processing | Machine learning | AI Services | chatbot | 28/11/2023 | |||||||||||||||||
| PSTW-585 | Dashboard to Explore state spending in Finland | https://tutkihankintoja.fi/?lang=en | The "explore state spending" website allows citizens and companies to explore data on government spending. Users can search according to different types of procurement spending (e.g. ICT procurement, administrative services, machinery, equipment and transport equipment, etc). AI technology is used in order to categorise the procurement spending. Other forms of analysis using AI technologies are also done on the data for the benefit just of procurement authorities. | National | Finland | FI | Hansel Ltd. | Central-Government | General public services | General services. | Implemented | 2.018 | Public services and engagement | Data Sharing Management | No | Yes | Artificial Intelligence | G2C | x | x | x | x | x | IPSO DB | Reasoning | Automated reasoning | Knowledge representation | 28/11/2023 | |||||||||||||||||
| PSTW-586 | eNest solution | https://ec.europa.eu/inea/en/connecting-europe-facility/cef-telecom/2016-fi-ia-0040 | Under the new eNest solution, verification of information provided by suppliers against official records will be done automatically during the tendering process. The system will use the European Single Procurement Document as a standard, which will mean that service providers do not need to attach official records to tenders. | National | Finland | FI | Hansel Ltd. | Central-Government | General public services | General services. | Pilot | 2.016 | 2017 | Internal management | Internal support processes | No | No | Artificial Intelligence | G2B | x | x | IPSO DB | Reasoning | Knowledge representation | Automated reasoning | 28/11/2023 | |||||||||||||||||||
| PSTW-587 | Palkeet, RPA Project | https://www.palkeet.fi/ajankohtaista/pohjoismaat-kansainvalista-rpa-karkea.html | The Finnish Government Shared Services Centre for Finance and HR (Palkeet) have delivered a project aimed at automating business processes with software robotics. Tasks that have been automated include purchase invoice validation and supplier register maintenance etc. This was the first major Robotic Process Automation (RPA) implementation in Finnish public sector. The project is part of a wider digitalisation initiative by the Finnish government. | National | Finland | FI | Finnish Government Shared Services Centre for Finance and HR | Central-Government | General public services | General services. | In development | 2.017 | Internal management | Internal support processes | No | No | Artificial Intelligence | G2B | x | x | IPSO DB | Reasoning | Automated reasoning | Robotics and Automation | 28/11/2023 | ||||||||||||||||||||
| PSTW-588 | Ministry of Finance, mTender | https://mtender.gov.md/ | With support from the EBRD, the Moldovan Government developed an open source electronic procurement system for electronic open tender, reverse auctions, aggregated procurement planning and online framework agreements. The system makes use of the open contracting data standard. It provides a fully digitised procurement planning tool, which reportedly automates (using robotic process automation) tracking of execution of contracts. | National | Moldova | MD | Ministry of Finance | Central-Government | General public services | General services. | Implemented | 2.019 | Internal management | Internal primary processes | No | No | Artificial Intelligence | G2B | x | x | x | x | IPSO DB | Reasoning | Automated reasoning | Optimisation | 28/11/2023 | ||||||||||||||||||
| PSTW-590 | KRATID - detecting traffic anomalies and incidents of the Estonian data exchange layer (X-Road) | https://www.kratid.ee/in-english | The Information System Authority of Estonia is using machine learning for detecting anomalies and incidents on the traffic of the Estonian data exchange layer - X-Road. Predictive analytics is used to decide where to send the police for traffic regulation. The system is well used in cities; however the algorithm does not yet work well in rural areas. The Estonian Unemployment Insurance Fund matches job seekers with open positions using AI. It helps job seekers get matched with the right job. The current job matching algorithm is developed further with job seeker profiling algorithm. Estonian Agricultural Registers and Information Board is using machine learning to detect land mowing. Satellite images are analysed to detect whether agricultural land has been mowed. This is necessary as mowing land is one of the requirements for receiving government grants. Before satellite image analysis this work was carried out manually using on-spot control. In line with the Digital Agenda 2020 for Estonia, the government encourages the use of AI applications and test projects. The aim is to have at least 50 use cases in public sector by 2020. Interestingly, Estonia has also launched a task force to collect ideas from the general public on how to best make use of AI for the development of Estonia's economy and state. | National | Estonia | EE | Information System Authority | Central-Government | General public services | General services. | Implemented | 2.018 | Enforcement | Predictive enforcement processes | No | No | Artificial Intelligence | G2G | x | x | x | x | IPSO DB | Perception | Computer vision | Machine learning | 28/11/2023 | ||||||||||||||||||
| PSTW-595 | Automated parking control | https://www.amsterdam.nl/parkeren/?PagClsIdt=16899643#PagCls_16899643 | In Amsterdam, the number of cars allowed to park in the city is limited, keeping the city liveable and accessible. The municipality checks whether a parked car has the right to be parked, for example, because parking fees have been paid via a parking meter or app, or because the owner has a parking permit. Enforcement is done with the help of scan cars equpiped with cameras, automating the process of license plate identification and background checks with specific scanning equipment and AI-based identification service. The service is currently in use for more than 150,000 street parking spaces in the City of Amsterdam. | Local | Netherlands | NL | Amsterdam Parking Services | Local Government | Economic Affairs | Transport | Implemented | 2.018 | Enforcement | Smart Recognition processes | No | No | Artificial Intelligence | G2C | x | x | https://algoritmeregister.amsterdam.nl/en/automated-parking-control/ | Planning | Planning and Scheduling | Machine learning | 28/11/2023 | ||||||||||||||||||||
| PSTW-597 | Reporting issues in public space | https://meldingen.amsterdam.nl/incident/beschrijf | When someone encounters rubbish or a maintenance issue on the street or in a park, they can report this to the municipality via an online reporting system. A dangerous traffic situation or disturbance from people or cafes can also be reported. This system used to be a collection of drop-down menus, from which the user would pick the category that best suited their report. The department responsible for a certain category would then take care of the report. However, as the municipality is a complex organisation, there are countless categories. Many times the wrong category would be chosen, resulting in delays. Now, an algorithm recognizes certain keywords, for example, waste and sidewalk. From these keywords, it determines which category it belongs to, and ultimately, which department within the municipality should examine the case. As a result, there are fewer administrative steps for the person reporting on the issue. Also, the report can be processed much faster, because it arrives at the right department more quickly. | Local | Netherlands | NL | Research, Information & Statistics (OIS) | Local Government | General public services | General services. | Implemented | 2.018 | Public services and engagement | Engagement management | No | Yes | Artificial Intelligence | G2C | x | x | x | x | x | x | IPSO DB | Planning | Planning and Scheduling | Natural language processing | 29/11/2023 | ||||||||||||||||
| PSTW-598 | Parking chatbot | https://www.hel.fi/fi/kaupunkiymparisto-ja-liikenne/pysakointi | The parking chatbot is a customer service channel of city’s parking services. Service provides automated answers to the parking-related questions of city residents and visitors. The service is available at the city parking website of Helsinki. | Local | Finland | FI1B | City of Helsinki | Local Government | Economic Affairs | Transport | Implemented | 2.018 | Public services and engagement | Service integration (various) | No | No | Artificial Intelligence | G2C | x | x | IPSO DB | Communication | Natural language processing | Machine learning | Optimisation | chatbot | 29/11/2023 | ||||||||||||||||||
| PSTW-599 | Health center chatbot | https://ai.hel.fi/en/health-center-chatbot/ | The chatbot provides health and illness-related advice easily without queuing. Chatbot directs the users to the right digital health services and advises on questions related to dental, mental health, substance abuse and social services. The service answers the most frequently asked questions and direct to the sources of reliable information based on users’ needs. The chatbot is integrated with other digital services of health centres. Through it, customers may be directed to, for example, the city’s digital services, Omaolo, Omakanta or social counselling chat. The service enables transactions around the clock anonymously and securely. All health centers use the service in Helsinki, and it covers all services of the health centers. The clinical guidance of the service is based on national practices of evidence-based treatments, the Current Care guidelines and the emergency care evaluation criteria. The service utilises natural language processing based Artificial Intelligence to analyse the searches entered by the customer and to identify the intended service need, as well as to find the respective instructions. The service expands the accessibility of health center services by enabling remote transactions around the clock. The service enhances the customer experience of digital services for health centers by providing a single channel for all digital services. The service streamlines the service production of health centers by automating the service on the frequently asked questions and by the automated collection of background information. The service also has positive effects on harmonising the quality of the service and on improving the employee experience of counselling services. | Local | Finland | FI1B | Helsinki City Hospital | Local Government | Health | Public health services. | Implemented | 2.019 | Public services and engagement | Service personalisation (various) | No | No | Artificial Intelligence | G2C | x | x | IPSO DB | Reasoning | Automated reasoning | Natural language processing | chatbot | 29/11/2023 | |||||||||||||||||||
| PSTW-6 | Flemish Infoline - Automatic classification of incoming phone calls | https://www.innovatieveoverheidsopdrachten.be/en/projects/1700-supported-artificial-intelligence | NLP is used to automatically classify incoming telephone questions at the 1700 (Flemish Infoline), to integrally transcribe and document the conversations, and to suggest answers. Informatie Vlaanderen use it to detect and categorise the incoming questions faster and more 'finely-meshed', and also integrate this 'finely-meshed' into the editorial management. In this way, the answers can be suggested more quickly, more adequately and also more 'automatically' to the answer provider, regardless of the chosen communication channel (oral or written). In essence, the project aims at two objectives: (1) the quicker and more efficient capturing and categorising of the question, and (2) the quicker and more efficient forwarding of the 'correctly captioned' question to the 'correct' answer provider with the 'correct' skills, whereby a valid and standardised answer (suggestion) is immediately sent along with it (so that the answer provider does not have to look up the intended answer script). | Regional | Belgium | BE2 | Information Flanders, Belgium | Local Government | General public services | Executive and legislative organs, financial and fiscal affairs, external affairs. | Implemented | 2.020 | Public services and engagement | Engagement management | No | No | Artificial Intelligence | G2C | x | x | x | https://www.innovatieveoverheidsopdrachten.be/en/projects/1700-supported-artificial-intelligence | Communication | Natural language processing | Machine learning | Searching | Audio processing | speech recognition | 06/10/2023 | ||||||||||||||||
| PSTW-60 | Toscana Open Research - Allows users to access information through "queries" | http://www.toscanaopenresearch.it/explore-the-data/#/ | The portal of the Tuscany Region designed to communicate and enhance the Tuscan system of research, innovation and higher education and to promote increasingly transparent and inclusive governance. The integration of data through a domain ontology allows users to query without having to use the technical terminology related to the physical organisation of databases and their complex internal structure. | Regional | Italy | IT | Regional Conference for Research and Innovation | Local Government | General public services | R&D general public services. | Implemented | 2.021 | Public services and engagement | Data Sharing Management | No | No | Artificial Intelligence | G2C | x | x | x | x | x | x | x | http://www.toscanaopenresearch.it/en/ | Reasoning | Knowledge representation | Optimisation | Searching | data anomalies detection | 17/10/2023 | |||||||||||||
| PSTW-600 | Oodi's book recommendation service Obotti | https://ai.hel.fi/en/oodis-book-recommendation-service-obotti/ | Obotti is Central Library Oodis recommendation chatbot. The service recommends books from Oodis selection according to the customers interest and feedback. The service is aimed at all Central Library Oodis customers and can be downloaded as a mobile application for Android and IoS devices. The service recommends books to the customer based on contextual analysis that the customer would not otherwise find. The purpose of the service is to present the material available in Oodi library to customers interestingly and to make it easier for customers to find interesting and new material. The recommended materials are freely available in the selections of the Central Library Oodi at the time of the recommendation. The service is divided thematically into six chatbots, each recommending content according to their theme. You can ask the service for recommendations using ready-made answer options, or in free search terms in the form of text or speech. The service utilises contextual analysis of natural language to determine the customer’s interests, as well as to produce corresponding book recommendations. | Local | Finland | FI1B | Helsinki Central Library Oodi | Local Government | Recreation, culture and religion | Cultural services. | Implemented | 2.019 | Public services and engagement | Service personalisation (various) | No | No | Artificial Intelligence | G2C | x | x | x | x | x | x | IPSO DB | Communication | Natural language processing | Automated reasoning | Searching | chatbot | 29/11/2023 | ||||||||||||||
| PSTW-601 | ChatBot Botty Bonn | https://codeforbonnrheinsieg.de/wer-entwickelt-den-chatbot-bonn-weiter-mit/ | The chatbot received a new technical basis and will be set up in a live and developer environment. As a community offer, the chatbot is then freely available as an open platform for all interested co-developers. All municipal service information will be available in the chatbot by the end of the year. The previous expert bots will then also be taken over. The technical basis and server hosting is financed and operated by the City of Bonn and GovBot. That's why no one has to worry or invest anything themselves. The developer environment is ready and will be further expanded in the coming months. | Local | Germany | DE | City of Bonn | Local Government | General public services | General public services n.e.c. | Implemented | 2.017 | Public services and engagement | Service personalisation (various) | No | No | Artificial Intelligence | G2C | x | x | x | x | x | x | IPSO DB | Communication | Natural language processing | Searching | AI Services | chatbot | 29/11/2023 | ||||||||||||||
| PSTW-602 | Noa - chatbot | https://www.inpi.fr/co/noa-chatbot | Noa's chatbot "Guidaci in l'Amministrazione" is a public service accessible online to guide start-ups in their administrative processes. | Regional | France | FR | Prefecture de l'Ile de France | Regional Government | General public services | General public services n.e.c. | Implemented | 2.020 | Public services and engagement | Service personalisation (various) | No | No | Artificial Intelligence | G2C | x | x | x | x | x | x | IPSO DB | Communication | Automated reasoning | Natural language processing | AI Services | chatbot | 29/11/2023 | ||||||||||||||
| PSTW-603 | Bobbi - Berlin administration | https://service.berlin.de/chatbot/chatbot-bobbi-606279.php | The state of Berlin already offers convenient solutions with the ServicePortal and the citizen hotline 115 for citizens' requests. The chatbot “Bobbi” can serve as an additional channel to help citizens quickly and conveniently with their concerns, even outside of 115 service hours. | Local | Germany | DE | City of Berlin | Local Government | General public services | General public services n.e.c. | Implemented | 2.014 | Public services and engagement | Service personalisation (various) | No | No | Artificial Intelligence | G2C | x | x | x | x | x | x | IPSO DB | Communication | Natural language processing | Knowledge representation | AI Services | chatbot | 29/11/2023 | ||||||||||||||
| PSTW-62 | Hugo - Virtual Assistant for governments | https://tilde.com/products-and-services/ai-powered-chatbots/case-studies/hugo | The institution of direct administration under the authority of the Minister for Culture, the Culture Information Systems Centre (hereinafter - KISC), has commenced a single development of a virtual assistant platform of State administration. KISC has created and further developed the language technology platform for public administration, Hugo.lv. The Hugo.lv website provides machine translation, speech recognition and synthesis. National regulatory authorities will have to face challenges when they start using a virtual assistant, as they will have to learn to adapt it to their needs. It should be noted that regulatory frameworks often change and institutions will have to maintain an up-to-date virtual assistant knowledge base. This is a NLP Chatbot for Government which provides Software as a Service (SaaP) possibility on a shared platform. | National | Latvia | LT | Culture Information Systems Centre Latvia | Central-Government | General public services | General services. | Pilot | 2.019 | Public services and engagement | Service personalisation (various) | No | No | Artificial Intelligence | G2C | x | x | x | https://ec.europa.eu/cefdigital/wiki/download/attachments/61932141/2_04_Janis%20Ziedins_Artus%20Vasiljevskis_Hugo.lv-AI_powered_service.pdf?version=1&modificationDate=1544438787726&api=v2 | Communication | Natural language processing | Machine learning | chatbot | 23/10/2023 | ||||||||||||||||||
| PSTW-621 | DPER Robotic Process Automation (RPA) Pilot | https://www.ops.gov.ie/app/uploads/2019/11/Project-Board-Report-MASTER.pdf | During 2017, the Department of Public Expenditure and Reform (DPER) ran a pilot study in RPA where four Government Departments selected some routine, stable and completely computer based processes for the purpose of exploring the efficiencies to be gained by automating this work using RPA. | National | Ireland | IE | Department of Public Expenditure and Reform | Central-Government | Economic Affairs | R&D economic affairs | Pilot | 2.017 | 2020 | Internal management | Internal support processes | No | No | Artificial Intelligence | G2G | x | x | IPSO DB | Reasoning | Automated reasoning | Knowledge representation | automatic classification | 29/11/2023 | ||||||||||||||||||
| PSTW-622 | Housing Assistance Payment Robotics Pilot | https://www.ops.gov.ie/case-studies/housing-assistance-payment-robotics-pilot/ | Limerick City and County Council operate the Housing Assistance Payment Shared Service Centre (HAP SSC) on behalf of the local government sector and are continuously striving for ways to improve their business. The organisation deals with more than 47,000 tenancies and 27,000 landlords, makes payments in excess of 400million, and collects more than 100million in rents. By 2021 it is anticipated that the HAP SSC will deal with 80,000 tenancies, 55,000 landlords and 600million in payments. In order to help deal with these volumes, the deployment of Robotic Process Automation (RPA) in the HAP Shared Service Centre was investigated. During 2018 a proof of concept pilot project was carried out by Agilisys, examining 3 micro processes within the centre. The proof of concept project demonstrated that opportunities for efficiencies and savings can be achieved through the deployment of RPA. Applying the outcome of the proof of concept project to a business case, it was concluded that if 10 complex processes could be replaced by RPA, then considerable savings could be made, while at the same time improving services to all key stakeholders. The HAP SSC is now seeking to identify existing processes where RPA may be immediately deployed, as well as opportunities for further business systems integration and automation within the HAP SSC. | Regional | Ireland | IE | Housing Assistance Payment Shared Service Centre | Local Government | General public services | General services. | Pilot | 2.017 | 2020 | Public services and engagement | Service personalisation (various) | No | No | Artificial Intelligence | G2C | x | x | IPSO DB | Reasoning | Automated reasoning | Knowledge representation | case-based reasoning | 29/11/2023 | ||||||||||||||||||
| PSTW-624 | Estonia to give citizens Alexa-like access to public services | https://www.computerweekly.com/news/252479025/Estonia-to-give-citizens-Alexa-like-access-to-public-services | Because the Estonian government makes all its services available online, the system will be able to access all the information it needs about a citizen to process things such as applications for a new passport. After the citizen makes a voice request, the virtual assistant might ask for a fingerprint to verify their identity or a selfie to be used on a document, but beyond that applications for services such as renewing passports and registering births will be automated. | National | Estonia | EE | Estonian Government | Central-Government | General public services | General services. | Planned | 2.021 | Public services and engagement | Service integration (various) | No | No | Artificial Intelligence | G2C | x | x | x | https://www.computerweekly.com/news/252479025/Estonia-to-give-citizens-Alexa-like-access-to-public-services | Communication | Natural language processing | Machine learning | Audio processing | personal assistant | 29/11/2023 | |||||||||||||||||
| PSTW-63 | UNA - Chatbot for process enterprise registration | https://www.ur.gov.lv/en/about-us/una/ | In 2018, the Register of Enterprises of Latvia introduced the Chatbot UNA (Future assistant for entrepreneurs - FAE) to answer frequently asked questions regarding the process of enterprise registration. Chatbot is available 24/7 and thus able to make communication between citizens and the state accessible and friendly. UNA is available on both the website of the Register of Enterprises as well as on the Facebook page as part of the Facebook messenger application. UNA is able to answer frequently asked questions about the registration of their businesses as well as the liquidation, merchants, companies and organizations. If citizens already have an application in progress, they are also able to ask about the progress of their documents. UNA only works in the Latvian language. According to the first performance indicators, 44% of the questions asked on UNA are considered to be general of nature and easily taken care of by the Chatbot. | National | Latvia | LT | Register of Enterprises of the Republic of Latvia | Central-Government | Economic Affairs | General economic, commercial and labour affair | Implemented | 2.018 | Public services and engagement | Engagement management | No | No | Artificial Intelligence | G2B | x | x | x | x | https://oecd-opsi.org/innovations/una-the-first-virtual-assistant-of-public-administration-in-latvia/ | Communication | Natural language processing | Automated reasoning | chatbot | 23/10/2023 | |||||||||||||||||
| PSTW-632 | How the Ministry of Justice used AI to compare prison reports | https://www.gov.uk/government/case-studies/how-the-ministry-of-justice-used-ai-to-compare-prison-reports--2 | The Ministry of Justice trained a neural network on the prison reports to track how people use specific words in prison contexts. The algorithm groups words with similar meanings to form an ‘intelligent search’ tool. New reports are automatically added to the tool’s library so the data remains up-to-date. This means staff can rapidly uncover information buried in the reports and identify trends. | National | United Kingdom | UK | Ministry of Justice | Central-Government | Public order and safety | Prisons. | Implemented | 2.019 | Internal management | Internal primary processes | No | No | Artificial Intelligence | G2G | x | x | https://www.gov.uk/government/case-studies/how-the-ministry-of-justice-used-ai-to-compare-prison-reports--2 | Communication | Natural language processing | Machine learning | speech recognition | 29/11/2023 | |||||||||||||||||||
| PSTW-635 | How the Department for Transport used AI to improve MOT testing | https://www.gov.uk/government/organisations/driver-and-vehicle-standards-agency | The DVSA applied a clustering model against garage test data from the last 3 months, as there was no labelled data available. The clustering model grouped MOT centres based on the behaviour they show when conducting MOT tests. The DVSA created a risk score for each garage in Great Britain. The risk score combined the output of the clustering algorithm with historical data about how frequently garages had been disciplined for not applying correct MOT standards. This allowed the DVSA to rank garages and their testers, and helped the DVSA identify regional trends. The DVSA updated their garage test data every 3 months. This allowed the DVSA to ensure the model used fresh data whilst also providing stability to garage ratings, providing examiners 3 month windows with which to visit garages. | National | United Kingdom | UK | Driver and Vehicle Standards Agency (DVSA) | Central-Government | Public order and safety | Police Services | Implemented | 2.019 | Enforcement | Supporting inspection processes | No | No | Artificial Intelligence | G2C | x | x | https://www.gov.uk/government/case-studies/how-the-department-for-transport-used-ai-to-improve-mot-testing | Planning | Planning and Scheduling | Automated reasoning | data analytics | 30/11/2023 | |||||||||||||||||||
| PSTW-637 | Whatsapp InfoCenter City of Milan (020202) | https://www.comune.milano.it/-/innovazione.-nuovi-servizi-per-l-assistente-virtuale-020202-su-whatsapp | The municipal administration activated a virtual assistant that indicates a series of options to choose from to obtain an immediate response: Citizenship support services; Resumption of economic activities; Public services and places of worship; Permitted transfers; Viability and parking; People with disabilities; Help the city of Milan; Health information; Decrees, ordinances and circulars. | Local | Italy | IT | Municipality of Milan | Local Government | Economic Affairs | Communication | Implemented | 2.020 | Public services and engagement | Service personalisation (various) | No | Yes | Artificial Intelligence | G2C | x | x | x | x | x | x | https://www.corrierecomunicazioni.it/media/milano-battezza-il-chatbot-center-via-whatsapp-e-il-primo-comune-deuropa/ | Communication | Natural language processing | Optimisation | AI Services | chatbot | 30/11/2023 | ||||||||||||||
| PSTW-638 | A unique artificial intelligence system now directs Ülemiste City drivers to available parking spots | https://pixevia.com/smart-parking-occupancy | A new system available to drivers in Ülemiste can guide them precisely to an available parking spot. The system combines signposts, LED displays, web interface and the most advanced AI video camera image analysis tool. It is one of the largest AI powered parking systems in Europe and the whole world. A new system available to drivers in Ülemiste City can guide them precisely to an available parking spot. The system combines signposts, LED displays, web interface and the most advanced AI video camera image analysis tool. It is one of the largest AI powered parking systems in Europe and the whole world. | Local | Estonia | EE | Municipality of Ülemiste | Local Government | Economic Affairs | Transport | Implemented | 2.018 | Public services and engagement | Service integration (various) | No | No | Artificial Intelligence | G2C | x | x | https://www.mainorulemiste.ee/news/a-unique-artificial-intelligence-system-now-directs-ulemiste-city-drivers-to-available-parking-spots | Perception | Computer vision | Machine learning | Connected and Automated vehicles | internet of things | 30/11/2023 | ||||||||||||||||||
| PSTW-639 | Detection of mowing events on grasslands from Sentinel-data | https://www.nature.com/articles/s41598-022-04932-6 | Nowadays, a vast amount of available data from the Sentinel mission significantly boosted research in agriculture. Estonia is among the first countries to take advantage of this data source to automate mowing and ploughing events detection across the country. | National | Estonia | EE | Estonian Agricultural Registers and Information Board (ARIB) | Central-Government | Environmental Protection | Environmental protection n.e.c. | Implemented | 2.018 | Analysis, monitoring and regulatory research | Information analysis processes | No | No | Artificial Intelligence | G2G | x | x | x | https://www.nature.com/articles/s41598-022-04932-6 | Perception | Computer vision | Machine learning | image processing | 30/11/2023 | ||||||||||||||||||
| PSTW-642 | Frag-den-Michel! Innovativer Online-Bürgerservice in Betrieb | www.hamburg.de/fragdenmichel | Citizens can ask questions to the Hamburg authorities regardless of normal business hours. Frag-den-Michel is a text-based dialogue system – a so-called chatbot – which is available for general information as part of a test operation. Frag-den-Michel will supplement the telephone information under the central authority number. | Local | Germany | DE | City of Hamburg | Local Government | General public services | General services. | Implemented | 2.019 | Public services and engagement | Service personalisation (various) | No | No | Artificial Intelligence | G2C | x | x | x | x | x | x | https://www.hamburg.de/pressearchiv-fhh/12679216/2019-06-07-pr-frag-den-michel/ | Communication | Natural language processing | Searching | AI Services | chatbot | 30/11/2023 | ||||||||||||||
| PSTW-643 | Municipality Welcome Manager (L2B2 Service Robot) in Ludwigsburg | https://www.bable-smartcities.eu/explore/use-cases/use-case/municipality-welcome-manager-l2b2-service-robot-in-ludwigsburg.html | First Information and guide for citizens visiting the Service Department: The digital helper named "L2B2" welcomes in the entrance area of the Bürgerbüros, drives independently through the corridors and accompanies the visitors to the respective departments. | Local | Germany | DE | City of Ludwigsburg | Local Government | General public services | R&D general public services. | Implemented | 2.018 | Public services and engagement | Service personalisation (various) | No | No | Artificial Intelligence | G2C | x | x | x | https://www.bable-smartcities.eu/explore/use-cases/use-case/municipality-welcome-manager-l2b2-service-robot-in-ludwigsburg.html | Integration and Interaction | Robotics and Automation | Optimisation | service robot | 30/11/2023 | ||||||||||||||||||
| PSTW-647 | London Police Facial Recognition System | https://www.met.police.uk/advice/advice-and-information/fr/facial-recognition-technology/ | The technology London will deploy goes beyond many of the facial recognition systems used elsewhere, which match a photo against a database to identify a person. The new tools use software that can immediately identify people on a police watch list as soon as they are filmed on a video camera. | Local | United Kingdom | UK | City of London Police | Local Government | Public order and safety | Public order and safety n.e.c. | Planned | 2.021 | Enforcement | Smart Recognition processes | No | No | Artificial Intelligence | G2G | x | x | https://www.nytimes.com/2020/01/24/business/london-police-facial-recognition.html | Perception | Computer vision | Machine learning | Connected Vehicle | 30/11/2023 | |||||||||||||||||||
| PSTW-648 | The Municipality of Oslo explores chatbots to respond to citizen requests | https://www.capgemini.com/news/client-stories/the-municipality-of-oslo-explores-chatbots-to-respond-to-citizen-requests/ | Working collaboratively, Oslo and Capgemini created an interdisciplinary team to develop proof of concept solutions. Beginning with the internal automated chatbot interface, the team tested the solution by having the municipality employees ask the robot to confirm their employment via chat. If successful, the request triggered the generation of a confirmation document through an existing automated process and then delivered final confirmation in the chat window as soon as resources were available. | Local | Norway | NO | Municipality of Oslo | Local Government | General public services | General public services n.e.c. | In development | 2.019 | Public services and engagement | Service personalisation (various) | No | No | Artificial Intelligence | G2C | x | x | x | x | x | x | https://www.capgemini.com/news/client-stories/the-municipality-of-oslo-explores-chatbots-to-respond-to-citizen-requests/ | Communication | Natural language processing | Searching | AI Services | chatbot | 30/11/2023 | ||||||||||||||
| PSTW-649 | Chatbot - City of Vienna | https://www.wien.gv.at/bot/ | The City of Vienna website provides comprehensive, detailed content, while the WienBot is all about information for immediate use. People looking for specific information while out and about need a different kind of content to those accessing the web from home. The WienBot is aimed at an audience that wants a smart way of consuming information quickly and on the go, but without foregoing the personal component. The chatbot can also reply in proper Viennese dialect. | Local | Austria | AT | City of Vienna | Local Government | General public services | General public services n.e.c. | Implemented | 2.018 | Public services and engagement | Service personalisation (various) | No | No | Artificial Intelligence | G2C | x | x | x | x | x | x | https://www.wien.gv.at/bot/ | Communication | Natural language processing | Searching | AI Services | chatbot | 30/11/2023 | ||||||||||||||
| PSTW-65 | FITS ITEMS - Road safety | https://investinlatvia.org/en/news/lgs-and-lmt-to-develop-solutions-for-drone-traffic | The State Public Traffic Safety Directorate uses the FITS ("Future Intelligent Transport Systems") ITEMS, which significantly improves road safety and saves people's lives. This AI system is capable of recognizing car numbers for driving speed, ensurance and roadworthiness test control on roads. At the end of 2018, the number of road accidents decreased by 43% compared to the number prior to the installation of photo cameras (1 084, after 613) at the roadside stages where photo cameras were installed and operated. | National | Latvia | LT | State Public Traffic Safety Directorate | Central-Government | Economic Affairs | Transport | Implemented | 2.018 | Enforcement | Smart Recognition processes | No | No | Artificial Intelligence | G2G | x | x | x | Mail to AI Watch (15-5-2020), https://investinlatvia.org/en/key-sectors/sectors/smart-city | Perception | Computer vision | Machine learning | 23/10/2023 | |||||||||||||||||||
| PSTW-650 | London TravelBot | https://blog.tfl.gov.uk/2017/06/12/facebook-messenger-tfl-travelbot/ | Transports for London created an automated service on Facebook Messenger to help you check the status of your Tube, rail or bus route. The service is free and uses latest data. The status checker is available for all Tube lines, DLR, London Overground, TfL Rail, trams and all bus routes. It can be used on Facebook Messenger. | Local | United Kingdom | UK | Transports for London | Local Government | General public services | General public services n.e.c. | Implemented | 2.017 | Public services and engagement | Service personalisation (various) | No | No | Artificial Intelligence | G2C | x | x | x | x | x | x | https://blog.tfl.gov.uk/2017/06/12/facebook-messenger-tfl-travelbot/ | Communication | Natural language processing | Searching | AI Services | chatbot | 30/11/2023 | ||||||||||||||
| PSTW-654 | Finland Migration Service Chatbot | https://migri.fi/etusivu | The Finnish Immigration Service has now introduced its new chatbot, Kamu. During the pilot stage, Kamu will answer frequently asked questions about processing times for applications and about the contact details of the Finnish Immigration Service. Kamu is available on all pages on the migri.fi website. You can ask questions in either English or Finnish. | National | Finland | FI | Finnish Immigration Service | Central-Government | Social protection | Social protection n.e.c. | Implemented | 2.018 | Public services and engagement | Service integration (various) | No | No | Artificial Intelligence | G2C | x | x | x | New chatbot answers questions about processing times and contact details | Communication | Natural language processing | Machine learning | chatbot | 30/11/2023 | ||||||||||||||||||
| PSTW-655 | Virtual Digital Assistant with the Revenue Commissioners of Ireland | https://www.techcentral.ie/title-revenue-commissioners-pilot-ai-driven-virtual-assistant/ | The virtual assistant uses voice-processing technology to recognize and respond to phone queries about tax clearance certificates and, in some cases, to process applications for those certificates. The pilot is testing the applicability of voice-driven virtual assistants in successfully answering general information questions and simple requests that are made to Revenue over the phone. | National | Ireland | IE | Office of the Revenue Commissioners | Central-Government | General public services | General services. | Implemented | 2.018 | Public services and engagement | Service personalisation (various) | No | No | Artificial Intelligence | G2C | x | x | x | x | x | x | https://newsroom.accenture.com/news/2018/accenture-pilots-virtual-digital-assistant-with-the-revenue-commissioners-of-ireland#:~:text=DUBLIN%3B%20Sept.,by%20advanced%20Artificial%20Intelligence%20technologies. | Communication | Natural language processing | Machine learning | chatbot | 30/11/2023 | |||||||||||||||
| PSTW-657 | Project “Sibyl A.I. Virtual" with Regione Puglia | https://www.progettiesoluzioni.it/progetti-speciali/sibyl-ai-virtual-assistant | The project “Sibyl A.I. Virtual ", funded through a PIA call dedicated to small businesses by the Puglia region, under the POR FESR fund, aims to create a digital platform with virtual assistance to support the interaction between the institution and citizens. | Regional | Italy | IT | Regione Puglia | Regional Government | General public services | R&D general public services. | Pilot | 2.021 | Public services and engagement | Service personalisation (various) | No | No | Artificial Intelligence | G2C | x | x | x | x | x | x | https://www.consorzioit.net/articolo/sibyl-gli-assistenti-virtuali-al-servizio-della-pubblica-amministrazione-locale | Communication | Natural language processing | Searching | AI Services | chatbot | 30/11/2023 | ||||||||||||||
| PSTW-658 | Artificial Intelligence: high technology and innovation to make life easier for citizens | https://www.comune.trieste.it/it/il-comune-di-trieste-avvia-il-chatbot-un-innovativo-servizio-di-assistenza-vocale-di-utilita-e-facile-fruizione-per-gli-utenti-del-sito-istituzionale-12801 | The new chatbot service - developed by Insiel SpA and co-financed by the Friuli Venezia Giulia Region - will debut on the website of the Municipality of Trieste at the beginning of 2020. In the first phase it will concern demographic services and will allow citizens to request information from the Municipality and receive answers in real time. | Local | Italy | IT | Municipality of Trieste | Local Government | General public services | General services. | In development | 2.019 | Public services and engagement | Service personalisation (various) | No | No | Artificial Intelligence | G2C | x | x | x | x | x | x | https://www.ai4business.it/vendor-point-of-view/chatbot-insiel-comune-trieste/ | Communication | Natural language processing | Searching | AI Services | chatbot | 30/11/2023 | ||||||||||||||
| PSTW-66 | Automatic decision making of the Electronic Declaration System of the State Revenue Service | https://www.vid.gov.lv/en/electronic-declaration-system | The Electronic Declaration System (EDS) of the State Revenue Service shall use the decision-making automating elements by automatically verifying the submitted declarations. It allows the approval of a declaration up to 2/3 which does not reveal non-compliance and thus allows experts to devote time only to checking declarations where non-compliance has been detected. In the future, there is great potential for ML solutions that will help to explore the client of public administration by promoting more efficient services for citizens, reducing the shadow economy and money laundering. At: https://www.vid.gov.lv/en/electronic-declaration-system "EDS provides automated verification of correctness of document completion and information of the customer about results." | National | Latvia | LT | State Revenue Service | Central-Government | General public services | Executive and legislative organs, financial and fiscal affairs, external affairs. | Implemented | 2.018 | Public services and engagement | Service personalisation (various) | No | No | Artificial Intelligence | G2C | x | x | x | Mail to AI Watch (15-5-2020) | Learning | Machine learning | Automated reasoning | data risk indicator | 23/10/2023 | ||||||||||||||||||
| PSTW-660 | Caterina, the first (virtual) municipal employee for identity cards and changes of residence | https://www.comune.siena.it/La-Citta/Comunita/Caterina | Caterina is the first virtual employee and her task will be to make the life of the Sienese easier thanks to the use of artificial intelligence. Young and old, therefore, will be able to contact you to obtain an identity card, change residence, renew the electoral card and complete other administrative procedures. Citizens residing in Siena, therefore, will be able to avoid long queues and stay comfortably at home to deal with those that sometimes are nothing more than boring paperwork. | Local | Italy | IT | Municipality of Siena | Local Government | General public services | General public services n.e.c. | Implemented | 2.019 | Public services and engagement | Service personalisation (various) | No | No | Artificial Intelligence | G2C | x | x | x | x | x | x | https://firenze.repubblica.it/cronaca/2019/10/28/news/siena_caterina_dipendente_comunale_virtuale-239755120/ | Communication | Natural language processing | Searching | AI Services | chatbot | 30/11/2023 | ||||||||||||||
| PSTW-664 | AI technology speeds up historical image handling at Hungary's National Archive | https://videos.microsoft.com/customer-stories/watch/uwk2D7xW2KEsAkQShhxjZh? | NAVA—part of MTVA, the National Audiovisual Archive of Hungary—acts to preserve the country’s rich database of twentieth-century imagery and audio heritage. Microsoft Azure Cognitive Services has proven the only tool to help do what the team needs: accurately classify millions of images that will serve as the country’s long-term collective memory bank. | National | Hungary | HU | NAVA | Central-Government | Recreation, culture and religion | Cultural services. | Pilot | 2.019 | Internal management | Internal support processes | No | No | Artificial Intelligence | G2G | x | x | x | https://videos.microsoft.com/customer-stories/watch/uwk2D7xW2KEsAkQShhxjZh? | Perception | Computer vision | Machine learning | image processing | 30/11/2023 | ||||||||||||||||||
| PSTW-667 | U.K. to use AI to spot dangerous side effects in the COVID-19 vaccinations | https://www.unite.ai/uk-goverment-look-to-ai-to-assess-possible-side-effects-of-covid-vaccines/ | To automate the process, the Medicines and Healthcare Products Regulatory Agency (MHRA) has given a $1.96 million contract to the U.K. arm of Genpact, the U.S.- listed business process outsourcing firm, to design a machine learning system that can ingest reports of side effects and pick up on potential safety concerns.The regulator told the Financial Times that, based on its previous experience with vaccination campaigns, it would expect that, over a six- to 12-month period, there might be 50,000 to 100,000 reports of suspicious side effects for every 100 million doses injected | National | United Kingdom | UK | U.K. Medicines and Healthcare Products Regulatory Agency (MHRA) | Central-Government | Health | R&D health. | Planned | 2.021 | Analysis, monitoring and regulatory research | Information analysis processes | No | No | Artificial Intelligence | G2G | x | x | https://fortune.com/2020/11/05/u-k-a-i-covid-19-vaccinations-side-effects/ | Learning | Machine learning | Knowledge representation | 30/11/2023 | ||||||||||||||||||||
| PSTW-668 | Aurora, the new virtual assistant of the South East Tuscany AUSL is online | https://www.quest-it.com/comunicati-stampa/online-aurora-il-nuovo-assistente-virtuale-della-ausl-toscana-sud-est/ | The South East Tuscany USL Company inaugurates one of the first projects in Europe of artificial intelligence applied to the world of information communication. Through the dedicated banner, it is possible for any citizen of the provinces of Siena, Arezzo and Grosseto to receive information services simply by querying the Aurora 3D avatar directly from a smartphone or PC. | Regional | Italy | IT | Azienda USL Toscana Sud Est (Regional Health structure) | Local Government | Health | Public health services. | Implemented | 2.020 | Public services and engagement | Service personalisation (various) | No | No | Artificial Intelligence | G2C | x | x | https://www.readygoone.it/news/online-aurora-nuovo-assistente-virtuale-ausl-toscana-sud-est/ | Communication | Natural language processing | Searching | AI Services | chatbot | 30/11/2023 | ||||||||||||||||||
| PSTW-669 | Self-driving buses roll into Gothenburg | https://www.themayor.eu/en/a/view/self-driving-buses-roll-into-gothenburg-7044 | The Swedish city of Gothenburg is already looking towards the next chapter of mobility innovation when it comes to the public transport service provision. Transport operator Keolis has brought its autonomous electric self-driving shuttles to inaugurate a new 1.8-km line that will serve various points within the Lindholmen Industrial and Science Park. The two vehicles started operating on 18 January but for the time being this is a trial run of the service which will last 4.5 months. | Regional | Sweden | SE | City of Gothenburg | Local Government | Economic Affairs | Transport | Planned | 2.021 | Public services and engagement | Service integration (various) | No | No | Artificial Intelligence | G2C | x | x | x | https://www.themayor.eu/en/a/view/self-driving-buses-roll-into-gothenburg-7044 | Integration and Interaction | Connected and Automated vehicles | Machine learning | Automated reasoning | autonomous vehicle | 30/11/2023 | |||||||||||||||||
| PSTW-67 | Toms - Chatbot facilitating customer communication with the State Revenue service | https://www.vid.gov.lv/ | A Chatbot facilitating customer communication with the State Revenue service (working time, locations, etc.), registration of economic operators, use of the Electronic Declaration System (access facilities, general issues on EDs), annual income statement and eligible expenditure (mandatory submission, types of eligible expenditure, repayment and payment deadlines), as well as the mobile application “Eligible expenditure”. Consulting is availability 24/7, freeing employees from answering typical questions. | National | Latvia | LT | State Revenue Service | Central-Government | General public services | Executive and legislative organs, financial and fiscal affairs, external affairs. | Implemented | 2.018 | Public services and engagement | Engagement management | No | No | Artificial Intelligence | G2C | x | x | x | x | https://www.iota-tax.org/news/latvian-tax-administration-has-virtual-assistant-tom | Communication | Natural language processing | Searching | chatbot | 23/10/2023 | |||||||||||||||||
| PSTW-670 | AI to track down those who do not pay taxes: the Revenue Agency project | https://www.agendadigitale.eu/cultura-digitale/lai-per-stanare-chi-non-paga-le-tasse-il-progetto-dellagenzia-delle-entrate/ | The European Union will finance the "A data driven approach to tax evasion risk analysis in Italy" project, which involves the use of innovation to preventively identify those at risk of tax evasion. With the collaboration of SOGEI (in-house of the Ministry of Finance), it is to deeply innovate, through the best innovations of digital technologies, the non-compliance risk assessment processes: in essence, it will introduce, experiment and use innovative techniques of network analysis, machine learning and data visualization, in order to create a new system to support the processes of identifying subjects at high risk of evasion. | National | Italy | IT | Agenzia delle Entrate | Central-Government | General public services | Executive and legislative organs, financial and fiscal affairs, external affairs. | Pilot | 2.021 | Enforcement | Supporting inspection processes | No | No | Artificial Intelligence | G2G | x | x | https://www.agendadigitale.eu/cultura-digitale/lai-per-stanare-chi-non-paga-le-tasse-il-progetto-dellagenzia-delle-entrate/ | Reasoning | Automated reasoning | Machine learning | anomaly detection | 30/11/2023 | |||||||||||||||||||
| PSTW-671 | Consortium completes key stage of autonomous tram depot project | https://www.smartcitiesworld.net/news/news/consortium-completes-key-stage-of-autonomous-tram-depot-project-6831 | The research project aims to develop a digital depot based on self-driving trams and demonstrate autonomous service functions, such as moving a tram through a washing facility to a siding. Siemens Mobility and ViP Verkehrsbetrieb Potsdam has completed a demonstration test of the Autonomous Tram in Depot research project (AStriD). The three-year research and development project is being implemented at the depot operated by Verkehrsbetrieb Potsdam and is supported by the Federal Ministry of Transport and Digital Infrastructure (BMVI) as part of its Modernity Fund (mFund). | Local | Germany | DE | City of Potsdam | Local Government | Economic Affairs | Transport | In development | 2.021 | 2026 | Public services and engagement | Service integration (various) | No | No | Artificial Intelligence | G2C | x | x | https://www.smartcitiesworld.net/news/news/consortium-completes-key-stage-of-autonomous-tram-depot-project-6831 | Integration and Interaction | Connected and Automated vehicles | Machine learning | Automated reasoning | autonomous vehicle | 30/11/2023 | |||||||||||||||||
| PSTW-672 | Manchester uses artificial intelligence to gain more insight into active travel | https://www.smartcitiesworld.net/news/news/manchester-uses-artificial-intelligence-to-gain-more-insight-into-active-travel-6763 | Around 100 sensors from Vivacity Labs will be installed to capture anonymous traffic counts in real-time to find out how segregated cycling and walking routes and priority areas are being used. Transport for Greater Manchester (TfGM) is partnering with Vivacity Labs to install artificial intelligence-powered sensors across the region to capture anonymous data in real-time on cycling and walking, helping to assess trends on key roads and junctions. | Local | United Kingdom | UK | Transport for Greater Manchester | Local Government | Public order and safety | Public order and safety n.e.c. | Planned | 2.021 | Analysis, monitoring and regulatory research | Prediction and planning | No | No | Artificial Intelligence | G2G | x | x | https://www.smartcitiesworld.net/news/news/manchester-uses-artificial-intelligence-to-gain-more-insight-into-active-travel-6763 | Learning | Machine learning | Knowledge representation | internet of things | 30/11/2023 | |||||||||||||||||||
| PSTW-673 | Creating an AI-driven mobile virtual assistant and common public services platform | https://ingov-project.eu/about/pilots-croatia/ | The following solutions were explored/developed during the pilot: Mobile apps for IPS co-delivery; Virtual assistant technology powered by the AI and utilising the NLP; Customised co-creation roadmaps based on inGov co-creation roadmap; Customised co-creation governance model based on inGov co-creation governance model. | Local | Croatia | HR021 | City of Bjelovar | Local Government | General public services | General services. | Pilot | 2.020 | Public services and engagement | Service personalisation (various) | No | No | Artificial Intelligence | G2C | x | x | x | https://ingov-project.eu/ingov-pilots-interim-evaluation/ | Communication | Natural language processing | Machine learning | chatbot | 30/11/2023 | ||||||||||||||||||
| PSTW-676 | Rome conducts smart city trial of intelligent vision sensors | https://www.smartcitiesworld.net/news/rome-conducts-smart-city-trial-of-intelligent-vision-sensors-6466 | Image sensors with artificial intelligence processing functionality are at the core of three trials being run to help cut the city’s transport related pollution and accidents at pedestrian crossings. | Local | Italy | ITI43 | City of Rome | Local Government | Environmental Protection | Environmental protection n.e.c. | Planned | 2.021 | Enforcement | Smart Recognition processes | No | No | Artificial Intelligence | G2G | x | x | https://www.smartcitiesworld.net/news/rome-conducts-smart-city-trial-of-intelligent-vision-sensors-6466 | Perception | Computer vision | Machine learning | internet of things | 30/11/2023 | |||||||||||||||||||
| PSTW-678 | Helsinki trials AI and automation as part of its drive to digital services | https://www.smartcitiesworld.net/news/helsinki-trials-ai-and-automation-as-part-of-its-drive-to-digital-services-6053 | Earlier this year it completed its second campaign of “agile trials” in the City’s Experimentation Accelerator, which tested 10 ideas submitted by city employees for the use of AI and automation. The City’s latest trials focusing on AI and robotic process automation sought answers to a variety of questions, such as the following: can AI help with the management of employment? can AI benefit work shift planning? can AI help gain a more realistic and accurate situational picture of traffic emissions in Helsinki? can AI help with the analysis of performance reviews to enable the development needs of employees to be supported better than before? can robotic process automation be used to facilitate the quality monitoring of student information? can a chatbot guide and advise business travellers? what is the benefit of a neural network-based AI identifying signatures in PDF documents? | Local | Finland | FI | City of Helsinki | Local Government | General public services | General services. | Pilot | 2.021 | Public services and engagement | Service integration (various) | No | No | Artificial Intelligence | G2G | x | x | https://www.smartcitiesworld.net/news/helsinki-trials-ai-and-automation-as-part-of-its-drive-to-digital-services-6053 | Planning | Automated reasoning | AI Services | chatbot | 30/11/2023 | |||||||||||||||||||
| PSTW-679 | Chatbot Comune di Collegno (TO) | https://www.comune.collegno.to.it/home | Chatbot to support citizen in assistance on Citizen Public Registry service and Separate Waste Collection service | Local | Italy | ITC11 | Collegno Municipality | Local Government | General public services | General services. | Implemented | 2.021 | Public services and engagement | Service personalisation (various) | No | No | Artificial Intelligence | G2C | x | x | x | x | x | x | https://www.comune.collegno.to.it/home | Communication | Natural language processing | Machine learning | AI Services | chatbot | 30/11/2023 | ||||||||||||||
| PSTW-682 | Belgian city uses artificial intelligence to tackle noise pollution | https://www.smartcitiesworld.net/news/news/belgian-city-uses-artificial-intelligence-to-tackle-noise-pollution-7243 | The Belgian city of Genk is working with Nokia to quantify the level of noise pollution along one of the city’s high streets. Authorities in the city want to address the health and safety concerns of residents and visitors enduring excessive noise from modified exhaust systems on cars, motorbikes and other vehicles travelling on the Stalenstraat. Nokia is deploying its artificial intelligence (AI)-powered Scene Analytics technology for the proof-of-concept project. The solution utilises data from microphones and installed cameras, used as IoT sensors along the road. If an approaching vehicle exceeds the pre-determined threshold, the street-deployed microphones and cameras begin recording. Nokia Scene Analytics adds intelligence to the event data transmitted from the sensors using a decibel-powered algorithm for audio analysis and automated number plate recognition (ANPR). This information is sent to authorities who receive quantified observations and orientations in order to make informed decisions on ‘if’ and ’how’ they will address the issue. | Local | Belgium | BE22 | City of Genk | Local Government | Public order and safety | Public order and safety n.e.c. | Implemented | 2.021 | Analysis, monitoring and regulatory research | Monitoring policy implementation | No | No | Artificial Intelligence | G2G | x | x | https://www.smartcitiesworld.net/news/news/belgian-city-uses-artificial-intelligence-to-tackle-noise-pollution-7243 | Perception | Audio processing | Machine learning | sound event recognition | 30/11/2023 | |||||||||||||||||||
| PSTW-7 | ILVO - List of multiple AI projects in the agricultural domain | https://ilvo.vlaanderen.be/en/search-results?q=Artificial+intelligence&id=home&l=en | The Institute for Agricultural, Fisheries and Food Research (ILVO) evaluated the possibilities of Artificial Intelligence for agricultural applications. Most applications are still in an initial phase and often in collaboration with other knowledge centers. Some concrete projects are: o Processing of hyperspectral images for early detection of potato diseases o Automatic health monitoring in cattle (e.g. lameness detection) o Automatic health monitoring in fattening pigs o Image analysis for multiple specific applications (e.g. quality food products, sorting fish species, etc.) o Behavior of plants under the influence of external stimuli o Identification of problem insects (eg zip needles) via camera images o Site-specific detection of problem weeds | National | Belgium | BE100 | Instituut voor Landbouw-, Visserij- en Voedingsonderzoek | Central-Government | Economic Affairs | General economic, commercial and labour affair | In development | 2.019 | Public services and engagement | Service integration (various) | No | No | Artificial Intelligence | G2B | x | x | Flemish Parlement Letter: Applications involving Artficial Intelligence. , Pub. L. No. nr. 138 (2017-2018), 2017–2018 2 (2017). and https://www.ilvo.vlaanderen.be/language/en-US/EN/Press-and-Media/All-media/ArticleType/ArticleView/ArticleID/4920.aspx | Perception | Computer vision | Machine learning | 06/10/2023 | ||||||||||||||||||||
| PSTW-70 | FCIS - Machine learning to identify suspicious patterns (trade, financial flows) | http://www.fntt.lt/lt/ivykiai/fntt-kartu-su-partneriais-pradeda-igyvendinti-europos-sajungos-moksliniu-tyrimu-ir-inovaciju-lesomis-remiama-projekta/3768 | Lithuanian Customs 's Financial Crime Investigations Service are using machine learning to identify suspicious patterns (trade, financial flows). This is part of a H2020 project, which, among other things, will explore using AI for better processing and analysis of data. The project will aim to apply Artificial Intelligence, data analysis and data visualization methods over two years, allowing law enforcement professionals to link, prioritize and analyze information gathered from different sources to facilitate decision-making. Several organizational units will be directly involved in the development of a targeted data processing and analysis system. | National | Latvia | LT | Financial Crimes Investigation Service (FNTT) | Central-Government | Public order and safety | Public order and safety n.e.c. | Pilot | 2.021 | Enforcement | Supporting inspection processes | No | No | Artificial Intelligence | G2G | x | x | x | http://www.fntt.lt/lt/ivykiai/fntt-kartu-su-partneriais-pradeda-igyvendinti-europos-sajungos-moksliniu-tyrimu-ir-inovaciju-lesomis-remiama-projekta/3768 | Learning | Machine learning | Automated reasoning | Knowledge representation | 23/10/2023 | ||||||||||||||||||
| PSTW-71 | Amberscript - Automated speech translation for public organisations | https://www.amberscript.com/en/ | Many Dutch municipalities, like the municipality of Staphorst, have implemented speech recognition model through a company product, AmberScript specialized in speech recognition, for providing automated speech translation coming from municipality council and bringing transparency on how decisions are made for the citizens. The product has been specifically trained on data from the public sector meetings. A dataset of more than 1.000 hours of audio with transcriptions was compiled, cleaned and processed into the AI Model. Now the product is capable of transcribing many of the discussions held in the municipal meetings, allowing citizens with hearing imparities to follow political debates online. | National | Netherlands | NL | About 120 different municipalities in the Netherlands | Local Government | General public services | Executive and legislative organs, financial and fiscal affairs, external affairs. | Implemented | 2.020 | Internal management | Internal primary processes | No | No | Artificial Intelligence | G2G | x | x | x | x | x | x | https://www.amberscript.com/en/news/amberscript-makes-council-meetings-of-dutch-municipalities-accessible-to-the-deaf-and-hearing-impaired | Perception | Audio processing | Machine learning | speech recognition | 23/10/2023 | |||||||||||||||
| PSTW-72 | CAS - Crime anticipation system | https://www.researchgate.net/publication/346593158_Predictively_policed_The_Dutch_CAS_case_and_its_forerunners | The Crime Anticipation System (CAS) makes weekly analyzes based on local and current data. External data about neighborhoods and residents, for example, is supplemented by the police's own knowledge about crimes and local situations and information from Statistics Netherlands. The system searches for crimes that show a pattern - for example, bicycle thefts in a certain neighborhood happen most often between the hours of 9:00 p.m. and midnight. Based on that, the police can better deploy available resources to fight these crimes more effectively, according to the news wire. | Local | Netherlands | NL32 | City of Amsterdam | Local Government | Public order and safety | Police Services | Pilot | 2.020 | Enforcement | Predictive enforcement processes | No | No | Artificial Intelligence | G2G | x | x | x | http://ceur-ws.org/Vol-2103/paper_6.pdf | Learning | Machine learning | Planning and Scheduling | 23/10/2023 | |||||||||||||||||||
| PSTW-73 | Xomnia - Law enforcement optimization system | https://www.xomnia.com/law-enforcement-optimization-at-amsterdam/ | For the municipality of Amsterdam, Xomnia built a user-friendly dashboard to optimize law enforcement. Xomnia harvested data from 7 entirely different data sources stored in the municipality’s data silos, such as GPS data from walkie-talkies and text data from fines collected by PDA’s and control room reports. The data was reconstructed and interconnected to enable dynamic data exploring for creating the dashboard. | Local | Netherlands | NL32 | City of Amsterdam | Local Government | Public order and safety | Police Services | Implemented | 2.017 | Enforcement | Predictive enforcement processes | No | No | Artificial Intelligence | G2G | x | x | x | https://www.xomnia.com/law-enforcement-optimization-at-amsterdam/ | Learning | Machine learning | Optimisation | 23/10/2023 | |||||||||||||||||||
| PSTW-75 | Xomnia - The Burglary Predictor | https://www.xomnia.com/burglary-prediction-for-the-municipality-of-utrecht/ | In the municipality of Utrecht, Xomnia has built a model that predicts the occurrence of burglaries in each district of Utrecht for a given week. From the date and time of the burglary, we derived weather conditions, holidays and special events. Sociodemographic statistics of the neighborhoods have been derived, as well as certain points of interest, like street lights, cameras, trees, parks and large garbage containers. The Burglary Predictor built by Xomnia enables the municipality of Utrecht to prevent burglaries by data-driven decision making. | Local | Netherlands | NL | City of Utrecht | Local Government | Public order and safety | Police Services | Implemented | 2.016 | Analysis, monitoring and regulatory research | Monitoring policy implementation | No | No | Artificial Intelligence | G2G | x | x | x | https://www.xomnia.com/burglary-prediction-for-the-municipality-of-utrecht/ | Learning | Machine learning | Automated reasoning | 23/10/2023 | |||||||||||||||||||
| PSTW-77 | Cameras - Detection holding a phone in car | https://www.om.nl/actueel/nieuws/2020/11/12/openbaar-ministerie-start-digitale-handhaving-op-handheld-telefoongebruik-achter-het-stuur | The Dutch Public Prosecution Service will intensify enforcement on the detention of mobile devices. With smart cameras that automatically forward violations to the Central Judicial Collection Agency (CJIB). The camera takes pictures of each passer-by, showing whether the driver is holding his mobile phone or not. Because the pictures are taken downwards, the driver's face is not in the picture. The license plate does, and the photo shows clearly and clearly whether someone is holding a mobile device behind the wheel. Only those photos where the system suspects that a phone is being held will be forwarded to the CJIB. A staff member carries out the final assessment at the CJIB. This can result in a fine of 240 euros. | National | Netherlands | NL | Dutch Public Procesecution Service | Central-Government | Public order and safety | Police Services | Implemented | 2.020 | Enforcement | Smart Recognition processes | No | No | Artificial Intelligence | G2G | x | x | x | https://www.om.nl/actueel/nieuws/2020/11/12/openbaar-ministerie-start-digitale-handhaving-op-handheld-telefoongebruik-achter-het-stuur | Perception | Computer vision | Machine learning | 23/10/2023 | |||||||||||||||||||
| PSTW-79 | SIA - Notifications public space | https://tada.city/en/nieuws/algorithms-for-more-fairness-in-the-city/ | Notifications provided by citizens on problems in the public space are categorized automatically and send to the responsible department. | Local | Netherlands | NL | Municipality of Dordrecht | Local Government | General public services | General public services n.e.c. | Implemented | 2.019 | Internal management | Internal support processes | No | No | Artificial Intelligence | G2C | x | x | x | https://tada.city/en/nieuws/algorithms-for-more-fairness-in-the-city/ | Communication | Optimisation | Machine learning | data categorisation | 23/10/2023 | ||||||||||||||||||
| PSTW-80 | RWS - Machine learning for road accident predictions | https://www.dssgfellowship.org/project/rijkswaterstaat-netherlands/ | The Netherlands Ministry of Water and Infrastructure Management (RWS) operates a 24h incident management service. Traffic managers process real-time data from 15+ screens, with chances of an accident being missed. Traffic inspectors need to ensure they are optimally positioned in their deployment zone to minimize travel time to accident sites. For this, Data Science for Social Good has been working with Rijkswaterstaat to create a machine learning model using data from incidents recorded between 2012 to 2016, road characteristics, speed and flow traffic data and weather data. The model predicts within a given time window and road segment the probability of an accident. Overlaying this on a heatmap we are able to display to traffic managers the road sections with the highest likelihood of accidents and allow them to better allocate inspectors to road sections to patrol. The solution gives a 3 to 4 times improvement on a baseline, where traffic inspectors patrol random road segments. | National | Netherlands | NL329 | Ministry of Infrastructure and Water Management of the Netherlands | Central-Government | Public order and safety | Public order and safety n.e.c. | Implemented | 2.019 | Analysis, monitoring and regulatory research | Prediction and planning | No | No | Artificial Intelligence | G2G | x | x | x | x | http://www.dssgfellowship.org/project/rijkswaterstaat-netherlands/ | Learning | Machine learning | Planning and Scheduling | 23/10/2023 | ||||||||||||||||||
| PSTW-81 | Rotterdam – Improving the usage of rooftops | https://www.youtube.com/watch?v=J3jWxF-HF2I | The Municipality of Rotterdam (Gemeente Rotterdam) manages Rotterdam, one of the most modern and touristic cities in the Netherlands, which is inhabited by 600,000 residents. Rotterdam has a unique roof landscape that was created after World War II, where many buildings with flat roofs were built during the city’s reconstruction. There are approximately 14.5km2 of flat roofs in the city and the Municipality of Rotterdam wants to use data to make informed decisions regarding the sustainable usage of its rooftops. DSSG (Data Science for Social Good) is helping Rotterdam figure out how improved use of its rooftops could help address challenges with water storage, green spaces and energy generation. The principal goal will be to use aerial and satellite images to identify the current usage of rooftops in Rotterdam. | Local | Netherlands | NL | Rotterdam Municipality | Local Government | Housing and community amenities | Housing and community amenities n.e.c. | Pilot | 2.017 | Analysis, monitoring and regulatory research | Prediction and planning | No | No | Artificial Intelligence | G2B | x | x | x | http://www.dssgfellowship.org/project/identifying-rooftop-usage-in-rotterdam/?portfolioID=15901 | Perception | Computer vision | Machine learning | 23/10/2023 | |||||||||||||||||||
| PSTW-82 | Mercé - citizen science for better urban life | https://300000kms.net/case_study/merce/ | A citizen science experiment in the city of Barcelona: citizens training algorithms to make urban environments more livable. The Mercè project is proposed as a new line of work that applies new machine learning techniques (one of the branches of so-called Artificial Intelligence) to the disciplines of urban planning, geography, sociology, economics and science. urban health to build objective knowledge and open data about our urban environments. Thus, Mercè is a citizen science experiment that aims to involve citizens in the training of an algorithm that allows us to design more livable cities. Through this experiment it is possible to translate the individual perceptions of many citizens about the habitability of cities into objective knowledge, reusable in urban planning. The relevance and innovation of the project is based on applying information and communication technologies to different transversal fields of knowledge, which have their common denominator in the city. | Local | Spain | ES51 | City of Barcelona | Local Government | General public services | Executive and legislative organs, financial and fiscal affairs, external affairs. | In development | 2.020 | Public services and engagement | Engagement management | No | No | Artificial Intelligence | G2C | x | x | x | x | x | http://merce.300000.eu/data2/informe_merce.pdf | Learning | Machine learning | Knowledge representation | Planning and Scheduling | data anomalies detection | 23/10/2023 | |||||||||||||||
| PSTW-83 | PRORAIL: Rail trespassers prediction | https://www.iotworldtoday.com/2020/02/06/how-iot-brings-railway-efficiency-to-dutch-rail-network/ | Data generated by IoT sensors enables ProRail to understand conditions it couldn’t previously, with human analysis alone. “What really helps is using data to create different estimates and insights that they didn’t have before, or correlations that they didn’t see earlier, or maybe calculate options that are beyond human possibilities because we have a computer that can do a million type of calculations,” said Thymo van den Brug, manager of development, asset management Information at ProRail, in a recent article on the use of data in the rail system. As a result, IoT sensor data enables ProRail to optimize train schedules and maintain equipment—two serious challenges for railway efficiency. To conduct preventative maintenance, ProRail uses a railway track monitoring system that collects data and monitors the state of the track infrastructure on various routes. Data can secure the physical environs as well. ProRail uses algorithms to determine when and where a trespasser might decide to walk on the track, for example. | National | Netherlands | NL | ProRail B.V | Central-Government | Economic Affairs | Transport | Pilot | 2.020 | 2021 | Enforcement | Smart Recognition processes | No | No | Artificial Intelligence | G2C | x | x | x | https://link.springer.com/article/10.1007/s11116-020-10109-9 | Perception | Computer vision | Machine learning | 23/10/2023 | ||||||||||||||||||
| PSTW-85 | Nancy - Access to National library assets | https://www.youtube.com/watch?v=o_6M_ZL7AuU | The Norwegian national library's solution based on commercially available AI to provide better access and deeper insight into their extensive collection of text, images and video. Production of new catalogue data. Metadata production based on Machine Learning. | National | Norway | NO | National Library of Norway | Central-Government | Education | Education n.e.c. | Implemented | 2.019 | Public services and engagement | Service personalisation (various) | No | No | Artificial Intelligence | G2G | x | x | x | x | https://www.youtube.com/watch?v=o_6M_ZL7AuU | Learning | Machine learning | Searching | 02/11/2023 | ||||||||||||||||||
| PSTW-861 | Smart enforcement: automated detection and handling of prohibited transit in Vojkovice | https://dt4regions.eu/dt-book/dt-stories/smart-enforcement-automated-detection-and-handling-prohibited-transit-vojkovice | The municipality of Vojkovice faces a challenge in enforcing traffic laws, particularly those related to prohibited truck transit. The lack of an efficient monitoring and penalization system has led to increased safety risks and road damage, negatively impacting residents' quality of life. This project presents an opportunity to address these issues and improve the municipality's ability to enforce traffic laws, resulting in safer roads and a more livable environment for the community. By implementing the automated traffic violation detection and connected handling system, the municipality of Vojkovice can achieve significant benefits. The system will provide real-time monitoring of traffic violations, enabling prompt action and ensuring fair and accurate penalization. This will improve road safety, reduced damage and traffic flow. | Local | Czechia | CZ06 | Municipality of Vojkovice | Local Government | Public order and safety | Public order and safety n.e.c. | In development | 2.023 | Enforcement | Supporting inspection processes | No | No | Artificial Intelligence | G2G | x | x | x | https://dt4regions.eu/dt-book/dt-stories/smart-enforcement-automated-detection-and-handling-prohibited-transit-vojkovice | Perception | Computer vision | image processing | 06/07/2023 | |||||||||||||||||||
| PSTW-87 | Lanekassen - Improve control on students with loan payments and identification | https://www.regjeringen.no/contentassets/1febbbb2c4fd4b7d92c67ddd353b6ae8/en-gb/pdfs/ki-strategi_en.pdf | The Norwegian student loan fund (Lånekassen) has for the first time used Artificial Intelligence (AI) to select account controls. It provided twice as many revelations of cheating. The book check is done among students who state that they live away from home, since only students who do not live with their parents can get the loan back from grants. Lånekassen’s book check in 2018 included 25,000 students. 15,000 were picked out by Artificial Intelligence (machine learning), while 10,000 were picked out by random selection (control group). The results showed that Artificial Intelligence made it easier to find those who are not really living away from home, said the Loan Fund. 5.5% in the control group and 11.6% in the machine learning group did not pass the book check. It shows that the machine learning selection has been twice as effective as the random selection in finding students who have given us incorrect information about housing | National | Norway | NO | Norwegian student loan fund (Lånekassen) | Central-Government | General public services | Executive and legislative organs, financial and fiscal affairs, external affairs. | Pilot | 2.019 | Analysis, monitoring and regulatory research | Prediction and planning | No | No | Artificial Intelligence | G2C | x | x | x | https://www.regjeringen.no/contentassets/1febbbb2c4fd4b7d92c67ddd353b6ae8/en-gb/pdfs/ki-strategi_en.pdf | Learning | Machine learning | Optimisation | data risk indicator | 02/11/2023 | ||||||||||||||||||
| PSTW-878 | La Paula i la Rita - the chatbot assistants in the authentication processes in Catalunya | https://www.aoc.cat/blog/2021/la-paula-i-la-rita-les-xatbots-de-laoc-que-ja-han-ajudat-a-mes-de-93-000-persones/ | This first half of 2021, the AOC has launched two pilots of conversational bots with the intention of validating their usefulness and gaining experience. Paula was activated on the VÀLid identification page, where all users who have to validate their identity in a transaction go through; Rita was activated on the idCAT Certificate application and management page. In the months that our chatbots have been active, they have supported more than 93,400 people, with a response rate of 96%, in a total of 96,500 conversations. In comparison with traditional human support, although the complexity of the consultations is not comparable, in 2020 the agents of the AOC's user support centre attended to a total of 63,000 support requests. | Regional | Spain | ES51 | AOC Consorci Administració Oberta de Catalunya | Regional Government | General public services | General public services n.e.c. | Implemented | 2.021 | Public services and engagement | Service personalisation (various) | No | No | Artificial Intelligence | G2C | x | x | x | x | x | x | https://www.aoc.cat/en/blog/2023/assistent-virtual-aoc/ | Communication | Natural language processing | AI Services | chatbot | 05/07/2023 | |||||||||||||||
| PSTW-879 | Process Mining pilot for the support service and case management of the Diputació de Girona | https://www.aoc.cat/blog/2022/aoc-mineria-processos/ | The AOC is piloting process mining at the support and records management service of the Diputació de Girona (Girona Provincial Council). In recent months the AOC has carried out a process mining pilot at the user support service. Process mining is a discipline that aims to discover, monitor and improve processes through the extraction of knowledge from the registry of information systems. In the case of the AOC, it was discovered that its support process, which were apparently linear and simple, had more than 3,400 variants. It is also an open door to simulations with the question "What would happen if...?". For example, "What would happen if the second level of support responded directly to the user instead of passing the response to the first level?", with the answer being up to 16,000 hours of annual processing saved. | Local | Spain | ES51 | Diputació de Girona | Local Government | General public services | General public services n.e.c. | Pilot | 2.021 | 2021 | Internal management | Internal management processes | No | No | Artificial Intelligence | G2G | x | x | x | x | https://www.aoc.cat/blog/2022/aoc-mineria-processos/ | Planning | Optimisation | pattern recognition | 05/07/2023 | |||||||||||||||||
| PSTW-88 | Statnett - Forecast service for weather | https://datascience.statnett.no/2018/04/27/from-idea-to-deployment-a-service-for-estimation-of-failure-probability-on-overhead-lines-based-on-the-current-weather-forecast/ | Forecast service for weather dependent failures on power lines. Combining Tableau, Python, Splunk and open data from met.no to deliver a realtime forecast of the probability of failure due to wind and lightning on overhead lines. | National | Norway | NO | Statnett, the Norwegian electricity transmission system operator | Central-Government | Economic Affairs | Fuel and energy | Implemented | 2.018 | Analysis, monitoring and regulatory research | Prediction and planning | No | No | Artificial Intelligence | G2G | x | x | x | x | https://datascience.statnett.no/2018/04/27/from-idea-to-deployment-a-service-for-estimation-of-failure-probability-on-overhead-lines-based-on-the-current-weather-forecast/ | Learning | Planning and Scheduling | Machine learning | 02/11/2023 | ||||||||||||||||||
| PSTW-880 | Automatic classification of citizens' issues or solecituds | https://www.aoc.cat/blog/2021/laoc-presenta-al-congres-darxivers-les-seves-iniciatives-dintelligencia-artificial-i-gestio-documental/ | Pilot test of how one of the disciplines of artificial intelligence, Machine Learning, can be applied to create a system of automatic classification of all those applications submitted as generic instances (from the EACAT and e-TRAM services) through the application of predictive algorithms. | Regional | Spain | ES51 | AOC Consorci Administració Oberta de Catalunya | Regional Government | General public services | General public services n.e.c. | Pilot | 2.021 | 2021 | Internal management | Internal primary processes | No | No | Artificial Intelligence | G2C | x | x | x | https://www.aoc.cat/wp-content/uploads/2021/05/PPTT_RN_machine_learning_consorciaoc_20210511.pdf | Learning | Machine learning | pattern recognition | 05/07/2023 | ||||||||||||||||||
| PSTW-883 | Lithuanian solution for systematised forecast of the regional labour market demand | https://govtechlab.lt/wp-content/uploads/2022/01/GovTech-Lab-apzvalga-2021-EN.pdf | The solution allows the automatic collection of publicly accessible data and drawing conclusions about the labour market situation and future demands. The labour market is a complex socio-economic system, so it is important to properly select the most representative data sources and to select appropriate deep-learning algorithms for the creation of accurate future forecasts. The owner of the solution is Panevėžys Development Agency, the solution was co-created with company “Neurotechnology”. The solution offers a comprehensive picture of the regional labour market model, its evolution and a forecast based on this data for a long future period, but it also allows for the purposeful organisation of local vocational guidelines and the formulation of training and retraining services. | Local | Lithuania | LT02 | Panevėžys Development Agency | Local Government | Social protection | Unemployment. | Pilot | 2.021 | Analysis, monitoring and regulatory research | Innovating Public Policy | No | Yes | Artificial Intelligence | G2G | x | x | x | https://govtechlab.lt/wp-content/uploads/2022/01/GovTech-Lab-apzvalga-2021-EN.pdf | Reasoning | Knowledge representation | Machine learning | pattern recognition | 05/07/2023 | ||||||||||||||||||
| PSTW-884 | Lithuania Solution for greening the city of Vilnius using satellite data and AI | https://govtechlab.lt/wp-content/uploads/2022/01/GovTech-Lab-apzvalga-2021-EN.pdf | Prototype for monitoring urban greenery, which will allow to identify problem areas. Such areas include dried plants that are likely to need replacing, Vilnius plant system requiring watering, mowing, removal of illegal greenery, etc. The prototype will depict the greenery of Vilnius that is constantly monitored using radar and optical satellites, machine learning, artificial intelligence, and algorithms. The solution lowers administrative resources for controlling and monitoring the greenery of the entire territory of Vilnius and eases the identification of illegal felling. | Local | Lithuania | LT01 | Vilnius City Municipality | Local Government | Environmental Protection | Protection of biodiversity and landscape. | Pilot | 2.021 | Analysis, monitoring and regulatory research | Innovating Public Policy | No | No | Artificial Intelligence | G2G | x | x | https://govtechlab.lt/wp-content/uploads/2022/01/GovTech-Lab-apzvalga-2021-EN.pdf | Perception | Computer vision | image processing | 05/07/2023 | ||||||||||||||||||||
| PSTW-885 | Lithuania Innovative solution for the assessment of the impact and damage of hydrometeorological phenomena | https://govtechlab.lt/wp-content/uploads/2022/01/GovTech-Lab-apzvalga-2021-EN.pdf | Using modern data processing and retrieval software with machine learning algorithms, the solution will enable the collection of information about hazardous phenomena from a variety of sources, perform climate monitoring and forecasting, assess the impact of dangerous, natural and catastrophic phenomena and ensure that better alerts are delivered to the population and economic entities. The benefits will be better performance of climate monitoring and forecasting, better assessment of the impact of dangerous, natural and catastrophic phenomena and better alerts are delivered to the population and economic entities. | National | Lithuania | LT | Lithuanian Hydrometeorological Service | Central-Government | Environmental Protection | Environmental protection n.e.c. | Pilot | 2.021 | Analysis, monitoring and regulatory research | Information analysis processes | No | No | Artificial Intelligence | G2C | x | x | x | https://govtechlab.lt/wp-content/uploads/2022/01/GovTech-Lab-apzvalga-2021-EN.pdf | Learning | Machine learning | probabilistic model | 05/07/2023 | |||||||||||||||||||
| PSTW-886 | Servizz.Gov Chatbox Pilot in Malta | https://www.servizz.gov.mt/mt/Pages/default.aspx | The Maltese government has recently implemented artificial intelligence (AI) technology to improve its public services. One of the most notable applications of AI in the public sector is the use of chatbots for customer service in government agencies. In this context, the servizz.gov’s Chatbot offers horizontal collaboration with Ministries and economies of scale through delivery of autonomous digital interaction. Powered by a rule-based mechanism with an FAQ source and machine learning incremental process, user ‘intents’ are captured to train the model and improve bot answers through iteration and feedback. servizz.gov will continue developing its current chat infrastructure into a fully-fledged citizen chatbot, extending its knowledge base but also capable of integrating with third party systems. | National | Malta | MT | Public Service Ministry | Central-Government | General public services | General public services n.e.c. | Implemented | 2.020 | Public services and engagement | Service personalisation (various) | No | No | Artificial Intelligence | G2C | x | x | x | x | x | x | https://isp.page/news/ai-in-maltas-public-services-streamlining-government-operations-and-enhancing-citizen-engagement/ | Communication | Natural language processing | AI Services | chatbot | 05/07/2023 | |||||||||||||||
| PSTW-887 | AI tool to spot undeclared swimming pools in France | https://www.economie.gouv.fr/dgfip | This is an AI computer vision system developed by Capgemini. The French tax office has identified 20,356 residential swimming pools that had previously gone undeclared, leading to 10 million euros in additional tax revenue opened, helping the government tax other undeclared architectural features such as annexes or verandas. The software automatically recognizes pools in aerial photographs (by looking for blue rectangles, for instance) and compares the results to records in real estate and tax databases. If it finds that a relevant address doesn't have a pool registered, the owner is in violation of tax law. | National | France | FR | General Directorate of Public Finance | Central-Government | General public services | Executive and legislative organs, financial and fiscal affairs, external affairs. | Implemented | 2.022 | Enforcement | Supporting inspection processes | No | No | Artificial Intelligence | G2G | x | x | x | x | https://www.theverge.com/2022/8/30/23328442/france-ai-swimming-pool-tax-aerial-photos | Perception | Computer vision | Knowledge representation | Automated reasoning | Machine learning | object recognition | 05/07/2023 | |||||||||||||||
| PSTW-888 | VeRa 1.0, the artificial intelligence that tracks tax evaders | https://www.agendadigitale.eu/documenti/vera-lai-al-servizio-dellagenzia-delle-entrate-come-funziona-lalgoritmo-anti-evasione/ | The AI tool developed by Sogei has started processing data and producing lists of taxpayers with anomalous tax profiles. His gaze crosses current account data, real estate and financial profiles, electronic invoices, payments with credit and debit cards, etc. This is done on pseudo-anonymised data and only with the compilation of critical lists do human specialists intervene. At that point, the summonses start and any alleged anomalies are justified. The whole operation, in combination with electronic invoicing, the daily transmission of electronic payments from card and ATM operators to the Internal Revenue Service, and other procedures, is expected to recover some EUR 14.4 billion in 2022, EUR 15.9 billion in 2023, and as much as EUR 16.1 billion in 2024. | National | Italy | IT | Ministry of Finance | Central-Government | General public services | Executive and legislative organs, financial and fiscal affairs, external affairs. | Implemented | 2.022 | Enforcement | Supporting inspection processes | No | No | Artificial Intelligence | G2G | x | x | x | x | https://www.agendadigitale.eu/documenti/vera-lai-al-servizio-dellagenzia-delle-entrate-come-funziona-lalgoritmo-anti-evasione/ | Learning | Machine learning | anomaly detection | 05/07/2023 | ||||||||||||||||||
| PSTW-889 | Estonia crowdsources speech data for the preservation of the Estonian language | https://govinsider.asia/inclusive-gov/estonia-crowdsources-speech-data-for-the-preservation-of-the-estonian-language/ | Estonia’s Ministry of Economic Affairs and Communications (MKM) and the State Information System Agency announced a “Donate Your Speech” campaign, with the goal of preserving the Estonian language and developing language technologies to bolster the delivery of public services for Estonian speakers. By creating an open database of 4,000 hours of spoken language, the nation aims to support companies, public sector institutions and research institutions in creating services and products based on speech technology. Speech technology can be used to record meetings, convert interviews into written form, and generate automatic subtitles to media. The campaign aims to promote the uptake of language technologies in public sector information systems as well as the private sector, including speech recognition technology, real-time subtitling solutions, and text to speech software. This will improve access to services and provide better ways for Estonians to interact with public and private sector services. | National | Estonia | EE | Ministry of Economic Affairs and Communications (MKM) | Central-Government | Recreation, culture and religion | Cultural services. | In development | 2.022 | Analysis, monitoring and regulatory research | Innovating Public Policy | No | Yes | Artificial Intelligence | G2C | x | x | x | https://govinsider.asia/inclusive-gov/estonia-crowdsources-speech-data-for-the-preservation-of-the-estonian-language/ | Perception | Audio processing | Knowledge representation | Machine learning | speech processing | 05/07/2023 | |||||||||||||||||
| PSTW-89 | TrondHeim - Insolvency Prediction | https://norden.diva-portal.org/smash/get/diva2:1375500/FULLTEXT01.pdf | The TrondHeim Municipality has been working on an AI system capable of predicting which companies had a higher chance of become insolvent. This enable the organisation to detect companies at risk at take pre-emptive actions. The predictions were accurate to around 80% a year (an accuracy of 90% would have been much more preferred). | Local | Norway | NO | Trondheim Municipality | Local Government | Economic Affairs | General economic, commercial and labour affair | Implemented | 2.018 | Analysis, monitoring and regulatory research | Prediction and planning | No | No | Artificial Intelligence | G2B | x | x | x | https://norden.diva-portal.org/smash/get/diva2:1375500/FULLTEXT01.pdf | Learning | Machine learning | Planning and Scheduling | 02/11/2023 | |||||||||||||||||||
| PSTW-897 | Advanced Technology for National Topographic Map Updating - Increasing spatial data accuracy with AI in Finland | https://www.gim-international.com/content/article/how-the-national-land-survey-of-finland-is-exploring-ai-technology | The Advanced Technology for topographic Map Updating (ATMU) project employed deep learning technology for object detection and change recognition using convolutional neural network and transfer learning (Building detection and change recognition), convolutional neural network and multitask learning (Road detection and change recognition) and convolutional neural network (Watercourse detection). By the end of the project, building detection achieved an accuracy of 97.9%, and 96% of building and road changes were correctly identified. | National | Finland | FI | National Land Survey of Finland | Central-Government | Economic Affairs | General economic, commercial and labour affair | Implemented | 2.020 | Analysis, monitoring and regulatory research | Information analysis processes | No | No | Artificial Intelligence | G2G | x | x | https://www.gim-international.com/content/article/how-the-national-land-survey-of-finland-is-exploring-ai-technology | Perception | Computer vision | Automated reasoning | Machine learning | Deep learning | 05/07/2023 | ||||||||||||||||||
| PSTW-9 | Verontrustingen - Enabling accurate predictions to detect day-care services inspection | https://www.dialogic.nl/wp-content/uploads/2018/06/VTOM-Small-Kids-Big-Data-Frank-Bongers-mei-2018.pdf | The Flemish Agency for Child and Family (Kind en Gezin) developed an AI system which enables more accurate predictions to detect day-care services which require further inspection. These inspections enable the agencies to keep the quality of the day-care services high and to improve the wellbeing of children. In facts, there is limited capacity available to conduct all the inspections. The use of data had been considered as way to enhance existing inspection practices and optimize the scarce amount of inspectors. The predictive system developed uses a supervised machine learning method (logistic regression and XGBoost) to analyse various internal and external data from the Health Care Inspection Unit. Combining the recommendations of the predictive system with existing staff experience and expertise enables more targeted and data-driven interventions. | National | Belgium | BE | Kind en Gezin, Belgium | Central-Government | Social protection | Family and children. | Implemented | 2.014 | Enforcement | Predictive enforcement processes | No | No | Artificial Intelligence | G2C | x | x | x | x | https://www.dialogic.nl/wp-content/uploads/2018/06/VTOM-Small-Kids-Big-Data-Frank-Bongers-mei-2018.pdf | Learning | Machine learning | Planning and Scheduling | Automated reasoning | 06/10/2023 | |||||||||||||||||
| PSTW-900 | Mapping mangroves with Serverless and Deep Learning | https://www.admiralty.co.uk/news/ukho-unveils-new-admiralty-global-mangrove-data-set-providing-most-accurate-view-worlds-crucial | The UK Hydrographic Office (UKHO) launched the world’s highest resolution, most up-to-date global view of the world’s critical mangrove forests: the ADMIRALTY Global Mangrove Data Set. Mangrove forests are a collection of saltwater tolerant plants that grow in tropical coastal environments. They are a crucial part of coastal ecosystems and act as natural barriers protecting human communities and infrastructure against the impacts associated with rising sea levels.Every six months, the UKHO searches for the latest available satellite images from the European Space Agency's Sentinel-2 mission. From these images, they select examples of coastal scenes that are clear and cloud-free, which will be processed to detect mangrove forests. Once images have been selected, they are analysed using the new mangrove detection model described above, which recognises the presence of mangroves in each individual pixel. | National | United Kingdom | UK | UK Hydrographic Office | Central-Government | Environmental Protection | Environmental protection n.e.c. | Implemented | 2.022 | Analysis, monitoring and regulatory research | Information analysis processes | No | No | Artificial Intelligence | G2G | x | x | x | https://www.admiralty.co.uk/news/ukho-unveils-new-admiralty-global-mangrove-data-set-providing-most-accurate-view-worlds-crucial | Perception | Computer vision | Machine learning | image processing | 05/07/2023 | ||||||||||||||||||
| PSTW-902 | SensusQ, an intelligence-gathering | https://investinestonia.com/defence59-presents-sensusq-an-intelligence-gathering-solution-changing-how-data-becomes-knowledge/?utm_source=twitter&utm_medium=content&utm_campaign=socialmedia&utm_content=defence59-presents-sensusq-an-intelligence-gathering-solution-changing-how-data-becomes-knowledge | Data is often unstructured and processing it all is complicated and ineffective, which makes analysing and extracting valuable insight time-consuming. People in high-pressure scenarios and environments, especially in combat situations, however, lack the luxury of weeks or even days to spend on such analysis. This often results in delayed or ill-informed decisions at the worst possible times. SensusQ is an Estonian DefenceTech company providing a solution that helps transform information into knowledge with the help of automation, integration, and interoperability, promotedby the Estonian Investment Agency. SensusQ’s Verdandi mobile app turns every boot on the ground into a sensor. That, in addition to other integrated sources, feeds into the intelligence management system. Events are mapped, connections formed, and decisions made. Commanders benefit from increased situational understanding for decision-making and analyst specialists from optimised data handling and analytics, while troops get a simple reporting toolset and access to information most relevant to them. | National | Estonia | EE | Estonian Investment Agency | Central-Government | Defence | Military defence. | In development | 2.023 | Analysis, monitoring and regulatory research | Information analysis processes | No | No | Artificial Intelligence | G2G | x | x | x | https://investinestonia.com/defence59-presents-sensusq-an-intelligence-gathering-solution-changing-how-data-becomes-knowledge/?utm_source=twitter&utm_medium=content&utm_campaign=socialmedia&utm_content=defence59-presents-sensusq-an-intelligence-gathering-solution-changing-how-data-becomes-knowledge | Perception | Machine learning | Optimisation | internet of things | 05/07/2023 | ||||||||||||||||||
| PSTW-91 | HAL - classification of documents | https://www.regjeringen.no/en/dokumenter/nasjonal-strategi-for-kunstig-intelligens/id2685594/?ch=4#id0022 | The Ministry of Foreign Affairs (MFA) use ML and NLP to analyse and classify reports from embassies and delegations. Every year, the Ministry of Foreign Affairs (MFA) receives up to 6,000 reports from Norwegian embassies, delegations, etc. Previously it was extremely difficult to navigate all this information. Since the MFA adopted machine learning and NLP to analyse and classify the content of these documents, it has been possible to find almost all relevant information on a given subject matter. The solution is also used to extract key information in reports and prepare summaries. In the work on developing this solution, the MFA cooperated with the University of Oslo, which provided solutions for categorising the Norwegian language. The plan is to gradually expand the solution with information from archives and external research reports. | National | Norway | NO | Ministry of Foreign Affairs | Central-Government | General public services | Foreign economic aid. | In development | 2.017 | Internal management | Internal primary processes | No | No | Artificial Intelligence | G2G | x | x | x | x | x | x | 1st Peer Learning Workshop AI watch | Communication | Natural language processing | Machine learning | text analysis | 02/11/2023 | |||||||||||||||
| PSTW-911 | The AI algorithm that blew up Italy’s school system | https://algorithmwatch.org/en/algorithm-school-system-italy/ | Algorithm that assigns teachers on short-term conctracts to schools automatically. | National | Italy | IT | Ministry of Education | Central-Government | Education | Education not definable by level. | Implemented | 2.020 | Internal management | Internal primary processes | No | No | Artificial Intelligence | G2G | x | x | x | https://algorithmwatch.org/en/algorithm-school-system-italy/ | Planning | Planning and Scheduling | Machine learning | 05/07/2023 | |||||||||||||||||||
| PSTW-912 | Signals -Detection of statistically significant clusters in reported infectious diseases | https://www.rki.de/DE/Content/Infekt/IfSG/Signale/Projekte/Signale_Projekte.html | The Signals project, funded by the Federal Ministry of Health, focuses on developing an early warning system for epidemiological outbreaks. They define a signal as a statistically unlikely accumulation of cases within a week, hinting at a possible outbreak. The project uses a filter combination approach, aggregating reported illness cases based on defined characteristics like pathogen, sex, or reporting location. An estimate is made for expected cases, a limit value is set, and if observed cases exceed the limit, a signal is generated. The initiative collaborates with the ITU and WHO's Focus Group AI for Health (FG-AI4H) to establish AI evaluation standards in the health sector. | National | Germany | DE | Robert Koch Institut (RKI) | Central-Government | Health | Public health services. | Pilot | 2.015 | Analysis, monitoring and regulatory research | Information analysis processes | No | No | Artificial Intelligence | G2G | x | x | x | https://www.rki.de/DE/Content/Infekt/IfSG/Signale/Projekte/Signale_Projekte.html | Learning | Machine learning | pattern recognition | 07/08/2023 | |||||||||||||||||||
| PSTW-92 | Canard - Speed camera system to flag potential traffic rules infringement | https://www.canard.gitd.gov.pl/cms/web/portal/o-projekcie-pois | EU financed system allows speed cameras installed at road junctures to derive information from the photographs and flag potential traffic rules infringement. The decision to fine the driver is not automatic, the system serves rather as an initial sorting mechanism that makes the work of CANARD employees more efficient. | National | Poland | PL | Automated Traffic Supervision Center | Central-Government | Public order and safety | Police Services | Pilot | 2.012 | 2015 | Enforcement | Predictive enforcement processes | No | No | Artificial Intelligence | G2G | x | x | x | https://www.canard.gitd.gov.pl/cms/ | Perception | Computer vision | Machine learning | 02/11/2023 | ||||||||||||||||||
| PSTW-921 | AI to spot counterfeit porducts at customs | https://www.itzbund.de/DE/digitalemission/trendstechnologien/kuenstlicheintelligenz/kuenstlicheintelligenz.html?nn=303798#bodyText3038003 | The ITZBund advises the Central Office for Commercial Legal Protection (ZGR) and the General Directorate of Customs ( GZD ) on AI. The goal is to use artificial intelligence to improve the detection of counterfeit products and thus support the fight against trade mark piracy. Trademark rights can be protected with the help of artificial intelligence.The system is based on image recognition processes and allows goods to be checked for counterfeiting. For this purpose, goods are visually recorded and compared with a comprehensive database using artificial intelligence. As a result, the technology assigns the product to a recognised brand and indicates the probability of success. At the same time, the system constantly learns new impressions and expands the database. However, the decision on whether a fake exists and how to proceed is still up to the customs officers. | National | Germany | DE | General Directorate of Customs (GZD) | Central-Government | General public services | Executive and legislative organs, financial and fiscal affairs, external affairs. | In development | 2.023 | Enforcement | Supporting inspection processes | No | No | Artificial Intelligence | G2G | x | x | Bendszusn, R. (2022). Make-or-buy in the area of Artificial Intelligence: Insights from AI use cases in the German public sector (master's thesis). Hertie School, Berlin. | Perception | Computer vision | anomaly detection | 07/08/2023 | ||||||||||||||||||||
| PSTW-922 | Chatbot LinA: the chatbot that answers general inquiries in the field of motor vehicle tax and customs law | https://lina-zoll.bundesbots.de/ | A live chat has recently been made available to citizens and companies for questions about motor vehicle tax. This is a written online communication in real time with employees of the central information vehicle tax of the customs. The live chat is integrated into the "LinA" chatbot, which is available to you around the clock for digital information on motor vehicle tax. When using the chatbot, you can start the live chat by clicking on the "Start live chat" button during the service hours. | National | Germany | DE | General Customs Directorate | Central-Government | General public services | Executive and legislative organs, financial and fiscal affairs, external affairs. | Implemented | 2.022 | Public services and engagement | Service personalisation (various) | No | No | Artificial Intelligence | G2C | x | x | x | x | x | x | Bendszusn, R. (2022). Make-or-buy in the area of Artificial Intelligence: Insights from AI use cases in the German public sector (master's thesis). Hertie School, Berlin. | Communication | Natural language processing | AI Services | chatbot | 07/08/2023 | |||||||||||||||
| PSTW-925 | Assessment of money laundering activities through AI | https://www.zoll.de/SharedDocs/Downloads/DE/Pressemitteilungen/2022/z89_jahresbericht_fiu_2021.pdf?__blob=publicationFile&v=3 | The Financial Intelligence Unit (FIU) evaluates information to carry out suspicious activity reports for risk analysis. This process is automated through the use of AI, so that new information can be added in the pool and repeated evaluations can be made in a more time-efficient way. | National | Germany | DE | GZD/ Financial Intelligence Unit (FIU) | Central-Government | General public services | Executive and legislative organs, financial and fiscal affairs, external affairs. | Pilot | 2.021 | Internal management | Internal primary processes | No | No | Artificial Intelligence | G2G | x | x | x | x | Bendszusn, R. (2022). Make-or-buy in the area of Artificial Intelligence: Insights from AI use cases in the German public sector (master's thesis). Hertie School, Berlin. | Learning | Machine learning | 07/08/2023 | |||||||||||||||||||
| PSTW-929 | Chatbot ViOlA for the homepage of the german Federal Central Tax Office | https://www.bzst.de/DE/Home/home_node.html | Chatbot ViOlA answers questions of general type and does not advise users on tax matters. | National | Germany | DE | Federal Central Tax Office (BZSt) | Central-Government | General public services | Executive and legislative organs, financial and fiscal affairs, external affairs. | Implemented | 2.022 | Public services and engagement | Service personalisation (various) | No | No | Artificial Intelligence | G2C | x | x | x | x | x | x | Bendszusn, R. (2022). Make-or-buy in the area of Artificial Intelligence: Insights from AI use cases in the German public sector (master's thesis). Hertie School, Berlin. | Communication | Natural language processing | AI Services | chatbot | 07/08/2023 | |||||||||||||||
| PSTW-93 | STIR - System Teleinformatyczny Izby Rozliczeniowej (Clearance Chamber ICT System) | https://crta.rs/en/algovrithms-state-of-play/ | This AI compiles a risk indicator based on collected financial data from financial institutions to determine whether account holders are likely to conduct illegal activities. If the suspicious activity is detected, at the request of the tax authorities the bank will be able to freeze suspicious accounts. The system is run by the State Clearance Chamber, a key entity of the Polish payment system infrastructure, that renders complex clearing services and other bank services. | National | Poland | PL | Krajowa Izba Rozliczeniowa S.A (State Clearance Chamber), Krajowa Izba Rozliczeniowa S.A (State Clearance Chamber) | Central-Government | General public services | Executive and legislative organs, financial and fiscal affairs, external affairs. | In development | 2.017 | Analysis, monitoring and regulatory research | Information analysis processes | No | No | Artificial Intelligence | G2G | x | x | x | x | https://crta.rs/en/algovrithms-state-of-play/ | Reasoning | Automated reasoning | Knowledge representation | data risk indicator | 02/11/2023 | |||||||||||||||||
| PSTW-930 | X-PIDER - an electonic investigative tool in the field of e-commerce used by the German tax authorities | https://taxtech.blog/2020/10/12/x-pider-erfahrungen-mit-dem-web-roboter-der-finanzverwaltung/ | X-PIDER is a German web crawler that has been used by the German tax authorities since 2003 as an electronic investigative tool in the field of e-commerce. X-PIDER is used to automatically collect information on the Internet (e.g. VAT ID information from dealers on Internet platforms such as eBay, AutoScout24), which can be used to identify taxable issues (e.g. determination of VAT entrepreneur status). Precise information about the functioning and effectiveness of X-PIDER is largely withheld by the tax authorities. However, it can be assumed that this special web crawler works in a similar way to "commercially available" web crawlers that search through automated websites, save and index web content and "track" further links. In the field of VAT fraud prevention, it is known that X-PIDER analyzes documents found to determine the extent to which they can be assigned to a business activity in terms of VAT ID. | National | Germany | DE | Federal Central Tax Office (BZSt) | Central-Government | General public services | Executive and legislative organs, financial and fiscal affairs, external affairs. | Implemented | 2.003 | Enforcement | Supporting inspection processes | No | No | Artificial Intelligence | G2G | x | x | x | Bendszusn, R. (2022). Make-or-buy in the area of Artificial Intelligence: Insights from AI use cases in the German public sector (master's thesis). Hertie School, Berlin. | Learning | Searching | Machine learning | Natural language processing | anomaly detection | 07/08/2023 | |||||||||||||||||
| PSTW-937 | Environmental monitoring with AI at the German Environment Agency | https://www.umweltbundesamt.de/en/topics/digitalisation/uba-application-lab-for-ai-big-data | The AI lab at the German Environment Agency (UBA) develops solutions for the energy and resource-saving use as well as the sustainable operation of AI and big data applications for the entire environmental department. In addition to the utilization of established data science technologies and methods, own developments of environmental and sustainability applications in the AI-Labc are implemented and evaluated. The aim is to be able to better utilize heterogeneous, complex and previously difficult to access databases using data science methods and technologies in order to simplify the viewing and cross-scale analysis of complex environmental data and make it operable across disciplines. | National | Germany | DE | German Environment Agency (UBA) | Central-Government | Environmental Protection | R&D environmental protection. | Pilot | 2.023 | Analysis, monitoring and regulatory research | Information analysis processes | No | No | Artificial Intelligence | G2G | x | x | Bendszusn, R. (2022). Make-or-buy in the area of Artificial Intelligence: Insights from AI use cases in the German public sector (master's thesis). Hertie School, Berlin. | Reasoning | Knowledge representation | big data | 07/08/2023 | ||||||||||||||||||||
| PSTW-939 | AI warns german businesses that the documents uploaded to apply for import tax exemptions might be wrong | https://www.bafa.de/SharedDocs/Pressemitteilungen/DE/Energie/2020_08_besar_ki.html | German businesses, in the case of an application to limit the Renewable Energy Sources (EEG) surcharge as part of the special equalization regulation, must submit all relevant documents before the material deadline. If this deadline is missed, the electricity-intensive companies face the irremediable rejection of the application and thus the payment of the full EEG surcharge. In order to minimize this risk for companies, BAFA has fundamentally modernized the application process this year: With the help of artificial intelligence, the uploaded application documents are automatically searched for errors. If it is determined with a certain probability that the wrong documents may have been uploaded, the application portal issues a warning message. | National | Germany | DE | Federal Office for Economic Affairs and Export Control (BAFA) | Central-Government | General public services | Executive and legislative organs, financial and fiscal affairs, external affairs. | Implemented | 2.020 | Enforcement | Supporting inspection processes | No | No | Artificial Intelligence | G2B | x | x | x | Bendszusn, R. (2022). Make-or-buy in the area of Artificial Intelligence: Insights from AI use cases in the German public sector (master's thesis). Hertie School, Berlin. | Learning | Machine learning | 07/08/2023 | ||||||||||||||||||||
| PSTW-941 | Artificial Intelligence helps predict groundwater levels | https://www.bgr.bund.de/DE/Themen/Wasser/Aktuelles/Archiv/2020-10_knn.html | Against the background of climate change, the Federal Institute for Geosciences and Natural Resources (BGR) and the Karlsruhe Institute of Technology (KIT) are developing methods for nationwide prediction of groundwater levels in a joint project. The researchers rely on artificial intelligence (AI).Artificial neural networks (ANN) are used, which have already proven their suitability for modeling and predicting groundwater levels many times over. A reliable prediction of the groundwater level is, among other things, the basis for deriving water availability for drinking water supply and irrigation in agriculture. It is also important for delineating potential land settlement zones caused by extremely low water tables associated with drought and water abstraction, and areas of potential high groundwater levels affecting transport infrastructure, buildings and agricultural land. In this way, suitable avoidance and adaptation strategies can be designed. | National | Germany | DE | Federal Institute for Geosciences and Natural Resources (BGR) | Central-Government | Environmental Protection | R&D environmental protection. | Pilot | 2.020 | 2023 | Analysis, monitoring and regulatory research | Information analysis processes | No | No | Artificial Intelligence | G2G | x | x | x | Bendszusn, R. (2022). Make-or-buy in the area of Artificial Intelligence: Insights from AI use cases in the German public sector (master's thesis). Hertie School, Berlin. | Learning | Machine learning | 07/08/2023 | |||||||||||||||||||
| PSTW-942 | Development of an AI-supported process for the automatic detection of pores in rocks – ITERATOR | https://www.bgr.bund.de/EN/Themen/Geodatenmanagement/Projekte/laufend/Endlagerung/Laufend/ITERATOR_en.html?nn=12929664 | The frequency, distribution, shape and size of pores control almost all of the properties of any solid body. Determining the porosity has therefore been an essential component of petrophysics for a long time. The ITERATOR project now relies on image processing algorithms to semi-automatically detect pores in micrographs derived from scanning electron microscopy. In addition to the porosity, this also determines the distribution of pore sizes and pore shapes. This information can then be used to derive important parameters such as heat flow and fluid flow. In addition, ITERATOR can also be used to reveal possible relationships between specific mineral phases and porosities, as well as stress regimes and pore orientation. | National | Germany | DE | Federal Institute for Geosciences and Natural Resources (BGR) | Central-Government | Environmental Protection | R&D environmental protection. | Pilot | 2.020 | 2022 | Analysis, monitoring and regulatory research | Information analysis processes | No | No | Artificial Intelligence | G2G | x | x | Bendszusn, R. (2022). Make-or-buy in the area of Artificial Intelligence: Insights from AI use cases in the German public sector (master's thesis). Hertie School, Berlin. | Perception | Computer vision | Machine learning | image processing | 07/08/2023 | ||||||||||||||||||
| PSTW-945 | MACRO - Development of methods of machine learning for cross-scale regionalization of hydrogeological area information | https://www.bgr.bund.de/DE/Themen/Wasser/Projekte/laufend/F+E/Macro/macro_projektbeschr.html | In this project, the basis for the use of machine learning for cross-scale regionalization of hydrogeological area information is to be developed and tested using specific use cases. | National | Germany | DE | Federal Institute for Geosciences and Natural Resources (BGR) | Central-Government | Environmental Protection | R&D environmental protection. | Pilot | 2.019 | 2023 | Analysis, monitoring and regulatory research | Information analysis processes | No | No | Artificial Intelligence | G2G | x | x | Bendszusn, R. (2022). Make-or-buy in the area of Artificial Intelligence: Insights from AI use cases in the German public sector (master's thesis). Hertie School, Berlin. | Learning | Machine learning | 07/08/2023 | ||||||||||||||||||||
| PSTW-946 | EnMAP - Environmental Mapping and Analysis Program | https://www.gfz-potsdam.de/sektion/fernerkundung-und-geoinformatik/projekte/enmap/ | EnMAP (Environmental Mapping and Analysis Program) is a German hyperspectral satellite mission that aims to monitor and characterize the Earth's surface worldwide. The main goal of EnMAP is to provide accurate diagnostic information on the state and evolution of terrestrial and aquatic ecosystems. This makes it possible to study environmental changes and the impact of human activities on ecosystems in different areas such as agriculture and forestry, geology and soils, urban areas, coastal and inland waters. | National | Germany | DE | Federal Ministry of Economics and Climate Protection (BMWi) | Central-Government | Environmental Protection | R&D environmental protection. | Pilot | 2.020 | 2023 | Analysis, monitoring and regulatory research | Information analysis processes | No | No | Artificial Intelligence | G2G | x | x | x | Bendszusn, R. (2022). Make-or-buy in the area of Artificial Intelligence: Insights from AI use cases in the German public sector (master's thesis). Hertie School, Berlin. | Perception | Computer vision | Machine learning | 07/08/2023 | ||||||||||||||||||
| PSTW-95 | Predicting long term unemployment in Portugal | https://www.datascienceforsocialgood.org/projects-blank/predicting-long-term-unemployment/ | Institute for Employment and Vocational Training (IEFP) is the Portuguese government employment agency whose mission is to foster quality job creation and combat unemployment. The agency does so by implementing active employment policies, including vocational training. The purpose of the project is to (1) better identify individuals at high risk of long-term unemployment (LTU) and (2) support more efficient allocation of IEFP’s resources to respond to the needs of unemployed individuals. The IEFP’s current model is based on risk categories (high-, medium-, or low-risk) assigned to each applicant when registering at IEFP. This project aims at improving the existing system by creating a model that dynamically updates an individual’s score over time, and better identifies high-risk individuals (as is appropriate to the needs of IEFP and partner institutions). Providing a dynamic score for LTU would enable the IEFP to strategically prioritize which support to provide, and how to optimize the delivery of services to those who need it most. | National | Portugal | PT | Institute for Employment and Vocational Training (IEFP) | Central-Government | Social protection | Unemployment. | Pilot | 2.018 | Analysis, monitoring and regulatory research | Prediction and planning | No | No | Artificial Intelligence | G2G | x | x | https://online.ucpress.edu/gp/article-abstract/1/1/12908/110741 | Reasoning | Planning and Scheduling | Knowledge representation | probabilistic model | 02/11/2023 | |||||||||||||||||||
| PSTW-953 | G@ZIELT: Safe shopping on the internet | https://www.bvl.bund.de/EN/Remit/gezielt_safe_shopping/gezielt_node.html | Consumers in Germany are increasingly purchasing food and cosmetics online, with a rising trend in online purchases of various items including kitchen utensils, toys, clothing, and tobacco products. The Federal Office of Consumer Protection and Food Safety (BVL) hosts a central unit called G@ZIELT, jointly managed by federal states, to regulate internet trade in products covered by the Food and Feed Code and tobacco. The G@ZIELT unit searches the internet to identify risky food offers, misleading labels, and unregistered businesses, reporting findings to appropriate authorities. | National | Germany | DE | Federal Office of Consumer Protection and Food Safety (BVL) | Central-Government | General public services | Executive and legislative organs, financial and fiscal affairs, external affairs. | Implemented | 2.014 | Enforcement | Supporting inspection processes | No | No | Artificial Intelligence | G2G | x | x | x | Bendszusn, R. (2022). Make-or-buy in the area of Artificial Intelligence: Insights from AI use cases in the German public sector (master's thesis). Hertie School, Berlin. | Learning | Machine learning | 07/08/2023 | ||||||||||||||||||||
| PSTW-959 | Automated image recognition for determining the type of wood | https://www.thuenen.de/de/fachinstitute/holzforschung/projekt/automatisierte-bilderkennung-fuer-die-holzartenbestimmung | With the introduction of the European Timber Trade Regulation (EUTR) 2013, the trade is obliged to document, among other things, the type of wood contained in the product to ensure legal origin. As part of the new research project, automated image recognition systems using artificial intelligence (AI) are to be developed in order to be able to check the wood species declaration of the manufacturers over a large area. | National | Germany | DE | Thünen-Institut | Central-Government | Economic Affairs | Agriculture, forestry, fishing and hunting | Pilot | 2.021 | 2024 | Analysis, monitoring and regulatory research | Information analysis processes | No | No | Artificial Intelligence | G2B | x | x | x | Bendszusn, R. (2022). Make-or-buy in the area of Artificial Intelligence: Insights from AI use cases in the German public sector (master's thesis). Hertie School, Berlin. | Perception | Computer vision | 07/08/2023 | |||||||||||||||||||
| PSTW-962 | Monitoring biological diversity in agricultural landscapes with remote sensing | https://www.thuenen.de/en/institutes/farm-economics/projects/monitoring-biological-diversity-in-agricultural-landscapes-with-remote-sensing | The maintenance and increase of biodiversity in agricultural landscapes built a major goal of the “agri-environment-climate measures” (AECM) in the context of the Common Agricultural Policy (CAP) of the EU. Biological diversity is closely related to the existence of habitat features that meet the requirements of different taxonomic groups. Single groups in most cases show individual criteria. Thus, a monitoring of habitat features must be tailored to a distinct set of target groups. Satellite data, today, are not (yet) able to detect single individual plants or insects. But, they are capable of mapping defined habitat features at large spatial scales that provide information about the nature value of single fields or landscapes. The overall goal of the project is the setup of an area-wide, spatially explicit trend monitoring at national level for the quantitative analysis of landscape structure and agricultural land-use intensity within these landscapes. For this, a set of indicators will be established that covers a variety of aspects at landscape (landscape structure, landscape elements) and field level (management intensity) in cropland and grassland areas. The Sentinel earth observation satellites (i.e. Sentinel-1 and -2) of the Copernicus-program from European Space Agency (ESA) provide the basis for this spatial modelling approach in a nation-wide monitoring project. | National | Germany | DE | Thünen-Institut | Central-Government | Environmental Protection | R&D environmental protection. | Pilot | 2.019 | 2024 | Analysis, monitoring and regulatory research | Information analysis processes | No | No | Artificial Intelligence | G2G | x | x | Bendszusn, R. (2022). Make-or-buy in the area of Artificial Intelligence: Insights from AI use cases in the German public sector (master's thesis). Hertie School, Berlin. | Perception | Computer vision | 07/08/2023 | ||||||||||||||||||||
| PSTW-968 | Language skills in the digital age | https://www.bundeswehr.de/de/organisation/personal/sprachkompetenz-im-digitalen-zeitalter-865922 | The Federal Language Office has been testing neural machine translation since mid-July 2020. Algorithms learn from the existing data and try to deliver precise translations. | National | Germany | DE | Federal Language Office | Central-Government | General public services | General services. | Pilot | 2.020 | Internal management | Internal primary processes | No | No | Artificial Intelligence | G2G | x | x | x | Bendszusn, R. (2022). Make-or-buy in the area of Artificial Intelligence: Insights from AI use cases in the German public sector (master's thesis). Hertie School, Berlin. | Communication | Natural language processing | 05/07/2023 | ||||||||||||||||||||
| PSTW-974 | AI is used in many components of numerical weather and climate forecasting | https://www.tagesschau.de/wissen/forschung/wettervorhersage-ki-100.html | The German Weather Service (DWD), together with the LMU in Munich, has already developed an AI-supported process , a so-called neural network. This simplifies the use of satellite images for numerical weather forecasting. The AI thus provides another piece of the puzzle for the overall picture of the weather. Even extreme weather conditions can be predicted at least a little bit better. | National | Germany | DE | German Weather Service (DWD) | Central-Government | Environmental Protection | R&D environmental protection. | In development | 2.023 | Analysis, monitoring and regulatory research | Prediction and planning | No | No | Artificial Intelligence | G2G | x | x | Bendszusn, R. (2022). Make-or-buy in the area of Artificial Intelligence: Insights from AI use cases in the German public sector (master's thesis). Hertie School, Berlin. | Perception | Computer vision | Machine learning | 28/08/2023 | ||||||||||||||||||||
| PSTW-981 | AI-based Integrated identity management for asylum procedures, improving plausability, data quality and security aspects | https://www.bamf.de/SharedDocs/Anlagen/DE/Digitalisierung/broschuere-digitalisierungsagenda-2020.pdf?__blob=publicationFile&v=9 | The software of the “Integrated Identity Management” (IDM) supports the Federal office caseworkers to register asylum seekers and to gather information about their country of origin and their travel history. The system applies a number of tools, such as automated name transcriptions from non-Latin to Latin letters; automated dialect identification to validate the registered country of origin; automated picture checks to prevent doubling files of an asylum-seeker, and sourcing information from smart phones to gather further identity information in case identity documents were lost. | National | Germany | DE | German Federal Office for Migration and Refugees (BAMF) | Central-Government | Public order and safety | Police Services | Implemented | 2.016 | Enforcement | Supporting inspection processes | No | No | Artificial Intelligence | G2G | x | x | x | x | Bendszusn, R. (2022). Make-or-buy in the area of Artificial Intelligence: Insights from AI use cases in the German public sector (master's thesis). Hertie School, Berlin. | Planning | Natural language processing | Computer vision | Audio processing | speech recognition | 01/09/2023 | ||||||||||||||||
| PSTW-983 | Chatbot launched in the occasion of the 2021 Federal Elections | https://www.itzbund.de/SharedDocs/Pressemitteilungen/DE/2021/2021-09-09-_Chatbot_Bundestagswahl_BpB.html | The election bot is an offer from the Fedral Agency for Civic Education (BpB). The chatbot provided information on topics such as the procedure in the polling station, the structure of the electoral system or what needs to be considered before the election. With a quiz, users could test their knowledge of the voting system. The BpB has prepared the diverse information within selected main topics and entered it into the dialogue system. It was also used to promote understanding of political issues in connection with the federal election. | National | Germany | DE | Federal Agency for Civic Education (BPB) | Central-Government | General public services | General services. | Implemented | 2.021 | 2021 | Public services and engagement | Service personalisation (various) | No | No | Artificial Intelligence | G2C | x | x | x | x | x | x | Bendszusn, R. (2022). Make-or-buy in the area of Artificial Intelligence: Insights from AI use cases in the German public sector (master's thesis). Hertie School, Berlin. | Communication | Natural language processing | AI Services | chatbot | 28/08/2023 | ||||||||||||||
| PSTW-987 | Sat4GWR_IF-Bund – Remote sensing & AI for the register census | https://www.destatis.de/EN/Service/EXSTAT/Datensaetze/register-census.html | Under an innovation project of the Federation entitled “Sat4GWR_IF-Bund – Remote sensing & AI for the register census“, algorithms will be developed on the basis of neural networks by means of which buildings can be identified on satellite images or aereal photographs. Then specific characteristics can be derived such as the use and size of the building. Remote sensing data are to support quality assurance as the data of buildings in the register of buildings and dwellings are checked and processed. This complements the establishment of the register and its maintenance. | National | Germany | DE | Federal Statistical Office (StBA) | Central-Government | General public services | General services. | In development | 2.021 | 2024 | Analysis, monitoring and regulatory research | Information analysis processes | No | No | Artificial Intelligence | G2G | x | x | Bendszusn, R. (2022). Make-or-buy in the area of Artificial Intelligence: Insights from AI use cases in the German public sector (master's thesis). Hertie School, Berlin. | Perception | Computer vision | Machine learning | sensor network | 28/08/2023 | ||||||||||||||||||
| PSTW-99 | CCM-SNS - Verification of medical prescriptions | https://automatingsociety.algorithmwatch.org/report2020/portugal/portugal-story/ | In Portugal, the Control and monitoring Center from the Portuguese Public National Health Service (CCM-SNS), uses data from several databases, in order to detect and fight prescription fraud. It follows a paperless prescription program and the electronic medical prescriptions system which were both implemented in 2016 and made mandatory for the public sector. During the first seven years, the central unit detected irregularities amounting to hundreds of millions of euros, and was instrumental in starting many prosecution for fraud in the health system. According to the Ministry of Health, in the first semester of 2017, the Invoice Control Center processed 356.2 million Euros' worth of prescriptions and flagged 21.1 millions euros to the State prosecutor. | National | Portugal | PT | Portuguese Public National Health Service (Centro de Controlo e Monitorização do Sistema Nacional de Saúde) | Central-Government | Health | Health n.e.c. | Implemented | 2.019 | Enforcement | Supporting inspection processes | No | No | Artificial Intelligence | G2G | x | x | x | x | https://algorithmwatch.org/en/story/portugal-automated-verification-prescriptions-medical-fraud/ | Learning | Machine learning | Natural language processing | Automated reasoning | 02/11/2023 | |||||||||||||||||
| PSTW-992 | KISTRA (use of artificial intelligence for the early detection of criminal offenses) - research project | https://www.comm.rwth-aachen.de/cms/COMM/Forschung/Projekte/~jeohm/KISTRA/?lidx=1 | The aim is to research the possibilities and framework conditions for the ethically and legally justifiable use of artificial intelligence by security authorities for the early detection and prevention of hate crime. KISTRA's results will include socio-scientific, ethical and legal expertises as well as technical solutions, for example software demonstrators. | National | Germany | DE | Federal Criminal Police Office (BKA) | Central-Government | Public order and safety | Police Services | Pilot | 2.020 | Enforcement | Predictive enforcement processes | No | No | Artificial Intelligence | G2G | x | x | x | Bendszusn, R. (2022). Make-or-buy in the area of Artificial Intelligence: Insights from AI use cases in the German public sector (master's thesis). Hertie School, Berlin. | Learning | Machine learning | probabilistic model | 28/08/2023 | |||||||||||||||||||
| PSTW-994 | Automated border control via Easypass Registered Traveler Program - biometric face recognition system | https://www.easypass.de/EasyPass/EN/EasyPASS-RTP/rtp_node.html#:~:text=EasyPASS%20Registered%20Traveller%20Programme%20(RTP)%20allows%20EasyPASS%20to%20be%20used,of%20automated%20border%20control%20procedures. | EasyPASS Registered Traveller Programme (RTP) allows EasyPASS to be used as a simple, fast and convenient alternative to traditional border control. This requires an electronic passport from a country that has concluded a declaration of reciprocity for the use of automated border control procedures. | National | Germany | DE | Federal Police | Central-Government | Public order and safety | Public order and safety n.e.c. | Implemented | 2.018 | Enforcement | Smart Recognition processes | No | No | Artificial Intelligence | G2C | x | x | x | x | x | Bendszusn, R. (2022). Make-or-buy in the area of Artificial Intelligence: Insights from AI use cases in the German public sector (master's thesis). Hertie School, Berlin. | Perception | Computer vision | face recognition | 28/08/2023 | |||||||||||||||||
| USAID-2023-1 | Media Early Warning System (MEWS) | https://docs.google.com/spreadsheets/d/1c7YJQGg4kg4ooGphqhOjzW2GRryYvKZt/edit?gid=29635126#gid=29635126 | To detect narratives and trends in social media alterations of images and video in order to find and counteract malign narratives | International | USA | USAID | International development | Public order and safety | Broadcasting and publishing services. | Implemented | 2.021 | Analysis, monitoring and evaluation | Information | Yes | Yes | Artificial Intelligence | G2C | x | x | x | x | x | x | https://docs.google.com/spreadsheets/d/1c7YJQGg4kg4ooGphqhOjzW2GRryYvKZt/edit?gid=29635126#gid=29635126 | Communication | Natural language | Machine learning | classifier | 03/12/2024 | ||||||||||||||||
| USAID-2023-10 | NASA SERVIR - Using artificial intelligence to forecast harmful algae blooms in Lake Atitlán, Guatemala | https://docs.google.com/spreadsheets/d/1c7YJQGg4kg4ooGphqhOjzW2GRryYvKZt/edit?gid=29635126#gid=29635126 | This application uses machine learning with Earth observations and weather-modeled data to forecast daily algal blooms in Lake Atitlán, Guatemala. The forecasting system is being used by Lake Authorities, such as the Authority for Sustainable Management of the Lake Atitlan Basin and its surroundings (AMSCLAE), to inform their Harmful Algal Blooms Alert System. This work is also supported by National Geographic and Microsoft through their Artificial Intelligence (AI) for Innovation grants. | National | Guatemala | USAID | International development | Environmental Protection | Agriculture, forestry, fishing | Implemented | 2.021 | Analysis, monitoring and evaluation | Prediction and planning | No | No | Artificial Intelligence | G2C | x | x | x | x | x | https://docs.google.com/spreadsheets/d/1c7YJQGg4kg4ooGphqhOjzW2GRryYvKZt/edit?gid=29635126#gid=29635126 | Learning | Machine learning | Computer vision | classifier | 03/12/2024 | |||||||||||||||||
| USAID-2023-12 | Serbia: AI predictions for the utilization of hospital beds | https://docs.google.com/spreadsheets/d/1c7YJQGg4kg4ooGphqhOjzW2GRryYvKZt/edit?gid=29635126#gid=29635126 | AI technology was used to predict bed occupancy at hospitals with MoH data from 2019, with an overall median error by department around 20%. This was a proof-of-concept model developed at the request of the Institute of Public Health (IPH) Batut to understand how AI can work and the value add. CHISU was asked to subsequently focus on a different use case (waiting list optimization for scheduled imaging diagnostics services, specifically CT and MRI), which is considered higher priority to demonstrate the implementation of the national AI strategy and the effect of AI in data use for decision making by the government, and will be addressed in the 2023-4. | National | Serbia | USAID | International development | Health | Health services. | Pilot | 2.019 | Analysis, monitoring and evaluation | Prediction and planning | No | No | Artificial Intelligence | G2C | x | x | x | x | x | https://docs.google.com/spreadsheets/d/1c7YJQGg4kg4ooGphqhOjzW2GRryYvKZt/edit?gid=29635126#gid=29635126 | Learning | Machine learning | 03/12/2024 | |||||||||||||||||||
| USAID-2023-13 | Mali: AI predictions for the optimization of the allocation of the distribution of COVID-19 vaccines | https://docs.google.com/spreadsheets/d/1c7YJQGg4kg4ooGphqhOjzW2GRryYvKZt/edit?gid=29635126#gid=29635126 | AI technology was used to develop a pandemic preparedness AI model to support allocation of COVID-19 vaccines based on a multi-tiered strategy for target populations: 1) hotspots for COVID-19 positive cases and 2) pregnant/breastfeeding women using DHIS2 data. This was a proof-of-concept model. | National | Mali | USAID | International development | Health | Health services. | 2.022 | Analysis, monitoring and evaluation | Prediction and planning | No | No | Artificial Intelligence | G2C | x | x | x | x | x | x | https://docs.google.com/spreadsheets/d/1c7YJQGg4kg4ooGphqhOjzW2GRryYvKZt/edit?gid=29635126#gid=29635126 | Learning | Machine learning | 03/12/2024 | |||||||||||||||||||
| USAID-2023-14 | Indonesia: AI predictions for improving forecasts for TB drugs | https://docs.google.com/spreadsheets/d/1c7YJQGg4kg4ooGphqhOjzW2GRryYvKZt/edit?gid=29635126#gid=29635126 | AI technology will be used to develop a forecasting AI model for TB sensitive drugs to inform more accurate annual quantification exercises for the MoH linked to their national data integration platform SatuSehat | National | Indonesia | USAID | International development | Health | Health services. | 2.022 | Analysis, monitoring and evaluation | Prediction and planning | No | No | Artificial Intelligence | G2C | x | x | x | x | x | x | x | x | https://docs.google.com/spreadsheets/d/1c7YJQGg4kg4ooGphqhOjzW2GRryYvKZt/edit?gid=29635126#gid=29635126 | Learning | Machine learning | Planning and scheduling | forecasting | 03/12/2024 | |||||||||||||||
| USAID-2023-3 | Using ML for predicting treatment interruption among PLHIV in Nigeria | https://docs.google.com/spreadsheets/d/1c7YJQGg4kg4ooGphqhOjzW2GRryYvKZt/edit?gid=29635126#gid=29635126 | Using data from USAID funded Strengthening Integrated Delivery of HIV/AIDS Services (SIDHAS) project in Nigeria we trained and tested an algorithm that can be used for predicting the probability that someone newly initiated on ART will interrupt treatment. The algorithm has been successfully integrated into the Lafiya Management Information System (LAMIS), the individual-level client level electronic medical record system. Each week the outputs, for each new patient is shared with staff at the health facilities and those at high risk are provided with more intensive follow up support to reduce the risk of treatment interruption. We also conducted a qualitative assessment among to health care workers at the facilities to determine their perception of ML and determine what additional support are required for institutionalizing ML into their routine work. | National | Nigeria | USAID | International development | Health | R&D health. | Implemented | 2.021 | Analysis, monitoring and evaluation | Yes | No | Artificial Intelligence | G2C | x | x | x | x | x | x | https://docs.google.com/spreadsheets/d/1c7YJQGg4kg4ooGphqhOjzW2GRryYvKZt/edit?gid=29635126#gid=29635126 | Learning | Machine learning | classifier | 03/12/2024 | ||||||||||||||||||
| USAID-2023-5 | Long-term impacts of land-use/land-cover dynamics on surface water quality in Botswana’s reservoirs using satellite data and artificial intelligence methods: Case study of the Botswana’s Limpopo River Basin (1984-2019) | https://docs.google.com/spreadsheets/d/1c7YJQGg4kg4ooGphqhOjzW2GRryYvKZt/edit?gid=29635126#gid=29635126 | For water supply, semi-arid Botswana relies on the reservoirs within the Botswana’s LRB. Reservoirs are particularly susceptible to the negative impacts of land-use and land-cover (LULC) activities and runoff because of their complex dynamics, relatively longer water residence times, and their role as an integrating sink for pollutants from their drainage basins. Despite these interrelationships and significance in regional and global economic stability, land and water (L-W) are often treated in “silosâ€. To understand the complex L-W nexus within the LRB, this study will use data-driven artificial intelligence for quantitative determination of the relationships between LULC change, together with socioeconomic development indicators and climate change, and their impacts on water quality and availability within the basin, both for 1984-2019 and to predict future scenarios (2020-2050). To advance data acquisition for LULC analysis and climate change, the study utilizes optical Earth-observation and meteorological satellite data. To provide near real-time and cost-effective approach for continuous monitoring of reservoir water quality within the basin, the study will develop empirical models for water quality estimation and water quality index mapping using 35-years of in-situ water quality measurements and water spectral observations using drone-borne spectrometer and optical satellite imagery through regression modeling and geospatial methods. | National | Botswana | USAID | International development | Environmental Protection | Agriculture, forestry, fishing | Implemented | 2.021 | Analysis, monitoring and evaluation | Prediction and planning | No | No | Artificial Intelligence | G2C | x | x | x | x | x | https://docs.google.com/spreadsheets/d/1c7YJQGg4kg4ooGphqhOjzW2GRryYvKZt/edit?gid=29635126#gid=29635126 | Learning | Machine learning | Computer vision | satellite images | 03/12/2024 | |||||||||||||||||
| USAID-2023-6 | Morogoro youth empowerment through establishment of social innovation (YEESI) lab for problem-centered training in machine vision | https://docs.google.com/spreadsheets/d/1c7YJQGg4kg4ooGphqhOjzW2GRryYvKZt/edit?gid=29635126#gid=29635126 | The project proposes to establish a social innovation lab for a machine vision program that will be used by youth in the Morogoro region of Tanzania. There are young people in the area who have studied information technologies and allied sciences, and while most of them can write computer programs, they cannot solve machine vision problems. This project aims to increase awareness among the youth of Morogoro and nearby regions to address machine vision problems in agriculture. Machine vision is a new and understudied practice in Tanzania; hence, this project will contribute to efforts in the creation of scientific societies that address the most pressing problems faced by more than 80% of Tanzania’s population who engage in farming. The main agricultural problems can be classified into five categories, as explained below: (1) Disease Detection and Classification: The project will develop experts who will solve problems in disease identification using machine vision for most of the diseases in crops and livestock, which are misdiagnosed by farmers. (2) Weed Classification: The project will develop algorithms that accurately identify weeds and contribute to the growing scientific database for automatic weed detection. (3) Pest Detection and Classification: Appropriate tools using machine vision for Integrated Pest Management (IPM) are needed in Tanzania, as IPM has been hindered due to a lack of extension officers to train farmers on mitigation and identification of pests in agriculture. (4) Crop Seedlings Stand Count and Yield Estimation: Use of machine vision and drones instead of scouting manually to estimate stand counts would provide appropriate mitigation strategies for replanting that would be beneficial to commercial farmers. Also of importance are algorithms to sort and estimate yield by counting the fruits and to estimate the amount of other agricultural products. (5) Crop Vigor Estimation: Most farmers apply inputs evenly across the farm because they cannot predetermine crop vigor. Accurate estimation of crop health would help farmers to mitigate the problems earlier and improve crop performance and avoid failure. Algorithms to determine crop vigor developed in this project will contribute to the improvement of the methods to estimate crop performance earlier. | National | Tanzania | USAID | International development | Environmental Protection | Agriculture, forestry, fishing | Implemented | 2.021 | Analysis, monitoring and evaluation | Prediction and planning | No | No | Artificial Intelligence | G2C | x | x | x | x | x | x | https://docs.google.com/spreadsheets/d/1c7YJQGg4kg4ooGphqhOjzW2GRryYvKZt/edit?gid=29635126#gid=29635126 | Learning | Machine learning | Computer vision | classifier | 03/12/2024 | ||||||||||||||||
| USAID-2023-7 | Breakthrough RESEARCH’s Social Media Listening | https://docs.google.com/spreadsheets/d/1c7YJQGg4kg4ooGphqhOjzW2GRryYvKZt/edit?gid=29635126#gid=29635126 | Social media listening draws on machine learning to synthesize and organize the vast quantities of data shared over social media platforms. Breakthrough RESEARCH carried out social listening on 12,301 social media posts in Nigeria to explore how gender-related online conversations manifest themselves and whether they have changed in the last five years. Using Crimson Hexagon’s machine learning algorithm, “Brightview,†publicly available social media content originating in the countries of interest was scraped by the algorithm, for posts relevant to RH/FP and youth. The resulting social media posts were then classified by topic, using language detected in the content. This provided a dataset categorizing conversations into overarching topics, allowing analyses to uncover key trends in topic specific conversation volume, insights about misinformation, attitudes and social norms, and more. The machine learning algorithm was able to identify relevant social media content. The 12,301 social media posts were qualitatively assessed and categorized, allowing researchers to monitor and track social media conversations far more expansively than allowed by research methods more traditionally used in public health and SBC programs. | National | Nigeria | USAID | International development | Public order and safety | Social exclusion n.e.c. | Implemented | 2.022 | Analysis, monitoring and evaluation | No | Yes | Artificial Intelligence | x | x | https://docs.google.com/spreadsheets/d/1c7YJQGg4kg4ooGphqhOjzW2GRryYvKZt/edit?gid=29635126#gid=29635126 | Communication | Natural language | natural language processing | 03/12/2024 | |||||||||||||||||||||||
| USAID-2023-8 | Project Vikela | https://docs.google.com/spreadsheets/d/1c7YJQGg4kg4ooGphqhOjzW2GRryYvKZt/edit?gid=29635126#gid=29635126 | Use AI to detect illegal rhino horn in airplane luggage X-Ray scanners | National | South Africa | USAID | International development | Public order and safety | Agriculture, forestry, fishing | In development | 2.016 | Analysis, monitoring and evaluation | Supporting inspection | No | No | Artificial Intelligence | G2C | x | x | x | x | x | https://docs.google.com/spreadsheets/d/1c7YJQGg4kg4ooGphqhOjzW2GRryYvKZt/edit?gid=29635126#gid=29635126 | Learning | Machine learning | Computer vision | computer vision | 03/12/2024 | |||||||||||||||||
| PIL-60 | MAPLE (Massachusetts Platform for Legislative Engagement) | http://mapletestimony.org/ | In the United States, the AI-powered tool MAPLE (Massachusetts Platform for Legislative Engagement) allows citizens to better understand the context and objectives of draft legal texts through AI-generated summaries submitting their inputs and comments | State | United States | Code for Boston and NuLawLab | Local Government | General public services | Executive and legislative organs | Implemented | 2.023 | Citizen engagement | No | ||||||||||||||||||||||||||||||||
| PIL-61 | AI-powered MP attendance monitoring and real-time quorum calculation | https://www.ipu.org/ai-use-cases/ai-powered-mp-attendance-monitoring-and-real-time-quorum-calculation-with-advanced-visualizations | An AI-driven system using high-spec cameras to automatically track MP attendance, visualize seating maps, and calculate quorums in real-time to ensure legislative transparency and session legality. | National | Bahrain | Council of Representatives of Bahrain | Central-Government | General public services | Implemented | 2.024 | Parliamentary oversight | ||||||||||||||||||||||||||||||||||
| PIL-62 | Pol.is | https://pol.is/home | Polis is a real-time system for gathering, analyzing and understanding what large groups of people think in their own words, enabled by advanced statistics and machine learning. Polis has been used all over the world by governments, academics, independent media and citizens, and is completely open source. | National | Austria, Uruguay, New Zealand, Philippines, United States, Germany, Taiwan | The Computational Democracy Project | General public services | Executive and legislative organs | Implemented | 2.012 | Citizen engagement | ||||||||||||||||||||||||||||||||||
| PIL-63 | GenAI.mil Platform | https://www.war.gov/News/Releases/Release/Article/4354916/the-war-department-unleashes-ai-on-new-genaimil-platform/ | The War Department has announced the launch of Google Cloud's Gemini for Government as the first of several frontier AI capabilities to be housed on GenAI.mil, the Department's new bespoke AI platform. This initiative cultivates an "AI-first" workforce, leveraging generative AI capabilities to create a more efficient and battle-ready enterprise. Additional world-class AI models will be available to all civilians, contractors, and military personnel, delivering on the White House's AI Action Plan announced earlier this year. | National | United States | U.S Department of War | Central-Government | Military | Implemented | 2.025 | |||||||||||||||||||||||||||||||||||
| PIL-64 | Gemini for Government | https://www.fedramp.gov/marketplace/products/FR2604952026/?_gl=1*1ubadum*_ga*NDQwOTg5OTA4LjE3Nzg1MDgzOTI.*_ga_HBYXWFP794*czE3Nzg1MDgzOTIkbzEkZzAkdDE3Nzg1MDgzOTIkajYwJGwwJGgw | Gemini for Government is delivered as a Public Cloud offering utilizing a multi-tenant Artificial Intelligence (AI) and Machine Learning (ML) cloud computing environment, spanning both Platform as a Service (PaaS) and Software as a Service (SaaS) models. It is available to the federal, state, local, and tribal governments, as well as research institutions, federal contractors, and government contractors, to enable secure and responsible application of generative AI for public sector missions. | National | United States | USA Governemnt | Central-Government | Implemented | 2.026 | ||||||||||||||||||||||||||||||||||||
| PIL-65 | USAI | https://www.usai.gov/api-documentation/ | A secure AI platform providing federal agencies access to models, a unified API framework, and a console for tracking usage. USAi API provides programmatic access to AI services for government users and approved partners. It currently supports Chat Completions (model inference) and Embeddings (used for RAG and other applications). | National | United States | USA Governemnt | Central-Government | Implemented | 2.026 | ||||||||||||||||||||||||||||||||||||
| PIL-66 | Habermas Machine | https://www.science.org/doi/10.1126/science.adq2852 | An LLM developed by Google DeepMind, trained to act as an AI mediator for group discussions on divisive policy topics. The model generates draft group statements intended to maximise endorsement across participants with differing views, iterating based on participant feedback. In a peer-reviewed study published in Science, the Habermas Machine produced consensus statements that participants rated as fairer and more representative than those produced by human mediators, across a range of contested issues (e.g. Brexit, national identity, gender pay gap). The tool is presented as a research system rather than a publicly deployed government product at this stage. | International | United Kingdom | Google DeepMind | Private sector | General public services | Executive and legislative organs | Pilot | 2.024 | Citizen engagement | Decision support / deliberation platform | Yes | Large Language Model | G2C | Yes | Yes | Yes | Yes | Yes | https://www.aipolicyperspectives.com/p/stop-shouting-start-policymaking | Large Language Model | AI mediation / consensus generation | deliberation | 22/06/2026 | |||||||||||||||||||
| PIL-67 | Jigsaw Sensemaking | https://jigsaw-code.github.io/sensemaking-tools | Sensemaking is an open-source suite of AI tools built by Jigsaw (a Google technology incubator) to help gather and understand large-scale public opinion input, identifying recurring themes, points of consensus, and areas of disagreement across thousands of free-text contributions. It was a core part of the technology stack behind the Bowling Green, Kentucky 'What Could BG Be?' digital town hall (PIL-68) and the Camden Council 'Waves' project (PIL-69), used alongside the Pol.is platform during the wide-engagement phases and to help facilitators synthesise themes during smaller deliberation sessions. | International | United States | Jigsaw (Google) | Private sector | General public services | Executive and legislative organs | Implemented | 2.024 | Citizen engagement | Text analysis / summarisation | Yes | Large Language Model | G2C | Yes | Yes | Yes | Yes | Yes | https://www.aipolicyperspectives.com/p/stop-shouting-start-policymaking | Large Language Model | Text summarisation / thematic analysis | sensemaking | 22/06/2026 | |||||||||||||||||||
| PIL-68 | What Could BG Be? (Bowling Green, Kentucky digital town hall) | https://www.whatcouldbgbe.com/ | A large-scale AI-assisted digital town hall run by the city of Bowling Green, Kentucky, to engage residents on long-term planning as the city anticipates its population doubling by 2050. Using the Pol.is platform and Jigsaw's Sensemaking tools, in partnership with Google's Jigsaw incubator and the local Innovation Engine non-profit, the month-long campaign engaged roughly 10% of the city's population (nearly 8,000 residents), generating 4,000 distinct proposals and over a million votes. Deliberate efforts were made to reach non-digital and marginalised residents (refugee centres, halfway houses, rehab facilities, senior living centres) and outreach was localised into nine languages. The bridge-based ranking algorithm surfaced overwhelming non-partisan support for several concrete initiatives (e.g. traffic-light synchronisation, eldercare expansion, riverfront development), and 96% of local leaders reported the process gave them a more precise, actionable mandate. | Local | United States | City of Bowling Green, Kentucky | Local Government | General public services | Executive and legislative organs | Implemented | 2.024 | Citizen engagement | Decision support / deliberation platform | No | Machine Learning | G2C | Yes | Yes | Yes | Yes | Yes | Yes | https://www.aipolicyperspectives.com/p/stop-shouting-start-policymaking | Machine Learning | Statistical clustering / opinion mapping | public participation | 22/06/2026 | ||||||||||||||||||
| PIL-69 | Waves / 'Who Cares About Care?' (Camden Council) | https://who-cares.commonplace.is/ | Waves is a structured, multi-phase AI-assisted public consultation model developed by the UK think tank Demos with local UK councils, used by Camden Council (north London) to consult residents on adult social care priorities ('Who Cares About Care?'). The process alternates between 'wide' phases (using Pol.is-style bridge-based ranking to gather input from as many residents as possible) and 'narrow' phases (smaller representative resident panels deliberating in depth, with AI helping facilitators spot themes and synthesise insights across many simultaneous conversations). Phase 1 engaged over 1,500 residents (59% first-time participants in local decision-making); a 41-resident panel then deliberated for 10 hours; a second wide phase reached 550 residents; the panel met again for 12 further hours before producing final recommendations to the council. A second deployment is underway in South Staffordshire on planning/housing policy, with ambitions to scale to other UK councils, charities, and membership organisations. | Local | United Kingdom | Camden Council / Demos | Local Government | Social protection | Social protection | Implemented | 2.025 | Citizen engagement | Decision support / deliberation platform | No | Machine Learning | G2C | Yes | Yes | Yes | Yes | Yes | Yes | Yes | https://www.aipolicyperspectives.com/p/stop-shouting-start-policymaking | Machine Learning | Statistical clustering / thematic synthesis | public consultation | 22/06/2026 | |||||||||||||||||
| PSTW-2876 | mAIGreece - the digital AI assistant for visitors | https://mintour.gov.gr/en/maigreece-en/ | The mAiGreece platform is a digital AI assistant launched by the Greek Ministry of Tourism in collaboration with the Ministry of Digital Governance to enhance services for visitors to Greece. The application provides comprehensive information on hospitals, health centres, embassies and consulates, police stations, Blue Flag beaches, museums, and content from visitgreece.gr, along with frequently asked questions. It is available in 31 languages, including major European, Asian, and Middle Eastern languages, ensuring accessibility for a wide range of international visitors. mAiGreece also includes safety features, such as the ability to send an SMS with the user’s geographical location to the Ministry of Civil Protection’s operations centre via the 112 emergency number for immediate assistance. The platform combines AI-driven query handling and multilingual support to provide tourists with fast, accurate information, improve their experience, and strengthen safety and accessibility across Greece. | National | Greece | EL | Greek Ministry of Tourism | Central-Government | General public services | General public services n.e.c. | Implemented | 2.024 | Public services and engagement | Service personalisation (various) | No | No | Artificial Intelligence | G2C | x | x | x | x | x | x | https://www.gov.gr/en/org/mindigital/tourismos/maigreece | Learning | Machine learning | Natural language processing | AI assistant | 15/12/2025 | |||||||||||||||
| PSTW-2924 | Fasit Dialogstøtte – AI Assistant for Conversation Notes | https://videncenter.kl.dk/viden-og-vaerktoejer/ai/kommunernes-ai-landkort | An AI assistant, integrated into the Fasit case management system, supports caseworkers by automatically transcribing and summarising conversations with citizens, producing draft minutes and journal notes. By handling routine documentation tasks, the assistant frees up time for caseworkers, enabling them to focus on professional decision-making and more complex aspects of their work. The system also helps ensure consistency, accuracy, and completeness in record-keeping, thereby enhancing overall case management quality across the municipality. | Local | Denmark | DK | Kalundborg Kommune | Local government | General public services | General public services n.e.c. | Implemented | 2.025 | Public services and engagement | Service personalisation (various) | No | No | Artificial Intelligence | G2C | x | x | x | x | x | x | https://videncenter.kl.dk/viden-og-vaerktoejer/ai/kommunernes-ai-landkort | Learning | Machine learning | Generative AI | AI assistant | 19/12/2025 | |||||||||||||||
| PSTW-663 | Bebot – Vienna AirportCity Virtual Assistant | https://www.viennaairport.com/ | Airports must provide clear, up-to-date information to diverse users, particularly during disruptions such as public health emergencies, while managing high volumes of enquiries. Vienna AirportCity introduced a digital assistant to support visitors navigating transport, facilities, and Covid-19-related requirements. This use case involves airport operators, travellers, and businesses, with the objective of improving information access and reducing pressure on staff. Bebot is implemented as a web-based chatbot accessible via mobile and desktop through on-site Wi-Fi and the airport website. It delivers structured responses on transport options, directions, facility services, and health regulations, integrated with airport information systems. The service enhances user experience by providing immediate guidance, improves operational efficiency by reducing routine enquiries, and supports consistent communication in a complex, high-traffic environment. | Local | Austria | AT | Vienna AirportCity | Local Government | Economic affairs | Transport | Implemented | 2.020 | Public services and engagement | Service personalisation (various) | No | No | Artificial Intelligence | G2C | x | x | x | x | x | x | https://www.airport-technology.com/news/vienna-airport-ai-chatbot-service-bebot/?cf-view | Communication | Natural language processing | Searching | AI Services | chatbot | 14/12/2025 | ||||||||||||||
| PSTW-1387 | Hubot – University of Helsinki Student Advisory Chatbot | https://studies.helsinki.fi/ohjeet/artikkeli/opiskelijaneuvonta | The University of Helsinki implemented Hubot to support student advisory services and improve access to information regarding applications and studies. Prospective and current students frequently require guidance on admission procedures, course selection and academic regulations. Hubot operates as a conversational interface on the university’s digital platforms, using natural language processing to interpret queries and match them to curated guidance content. The chatbot retrieves instructions from official knowledge bases and directs users to relevant forms and webpages. If unable to resolve an enquiry, Hubot generates a service request to student advisers or transfers the user to a live chat when available. By automating responses to common questions, the system reduces response times and supports continuous access to essential academic information. The deployment enhances efficiency in student services while preserving human interaction for complex or individual cases requiring personalised support. | National | Finland | FI | University of Helsinki | Academic-Research | General public services | General public services n.e.c. | Implemented | 2.023 | Public services and engagement | Service personalisation (various) | No | No | Artificial Intelligence | G2C | x | x | x | x | x | x | https://www.alghoncloud.com/soluzioni/public-administration/ | Communication | Natural language processing | AI Services | chatbot | 25/02/2026 | |||||||||||||||
| PSTW-2665 | DEPUCHAT - chatbot to facilitate citizens' access to MPs' activities | https://comunicazione.camera.it/archivio-prima-pagina/19-51129 | DEPUCHAT is an experimental project developed from an idea presented by Roma Tre University and the University of Florence, in response to a call launched by the Italian Chamber of Deputies. It is an advanced generative AI-based chatbot designed to provide citizens with fast, certified, and transparent information about the activities of Members of Parliament. Using official parliamentary data — including personal details, roles, legislative proposals, oversight acts, speeches, and committee work — DEPUCHAT allows users to search by topic, by individual deputy, or by specific issues (e.g., laws proposed on artificial intelligence). While strictly limited to parliamentary activity (excluding personal questions), the system aims to foster transparency, citizen participation, and data reliability. Currently in testing, it will undergo further data integration, stress testing, and security checks before being made publicly available as a valuable tool for civic engagement. | National | Italy | IT | Roma Tre University and the University of Florence | Academic-Research | General public services | Executive and legislative organs, financial and fiscal affairs, external affairs. | In development | 2.025 | Public services and engagement | Service personalisation (various) | No | No | Artificial Intelligence | G2C | x | x | x | x | x | x | https://comunicazione.camera.it/archivio-prima-pagina/19-51131 | Learning | Machine learning | Generative AI | chatbot | 28/08/2025 | |||||||||||||||
| PSTW-2676 | The Family Hub in Halton Borough Council: Digital front door in family hub services | https://www.local.gov.uk/case-studies/halton-borough-council-digital-front-door-family-hub-services-0 | Halton Borough Council has partnered with Beebot AI to develop a Digital Front Door for its Family Hub Services. This interactive platform provides 24/7 access to children’s and family services, offering personalised support through AI-driven chatbots and automated processes for tasks such as booking appointments. The initiative aims to improve accessibility and streamline service delivery for families. | Local | United Kingdom | UK | Halton Borough Council | Local Government | Social protection | Family and children. | In development | 2.025 | Public services and engagement | Service personalisation (various) | No | No | Artificial Intelligence | G2C | x | x | x | x | x | x | https://www.local.gov.uk/our-support/cyber-digital-and-technology/artificial-intelligence-hub/artificial-intelligence-case | Learning | Machine learning | Generative AI | chatbot | 28/08/2025 | |||||||||||||||
| PSTW-2682 | Peterborough City Council: Hey Geraldine, a personalised AI assistant | https://www.local.gov.uk/case-studies/peterborough-city-council-hey-geraldine-personalised-ai-assistant | Peterborough City Council has introduced “Hey Geraldine,” a personalised AI assistant that provides residents with tailored information and guidance. The assistant uses AI to understand individual needs and preferences, enhancing resident engagement and satisfaction. | Local | United Kingdom | UK | Peterborough City Council | Local Government | General public services | General public services n.e.c. | Implemented | 2.025 | Public services and engagement | Service personalisation (various) | No | No | Artificial Intelligence | G2C | x | x | x | x | x | x | https://www.local.gov.uk/our-support/cyber-digital-and-technology/artificial-intelligence-hub/artificial-intelligence-case | Learning | Machine learning | Generative AI | chatbot | 28/08/2025 | |||||||||||||||
| PSTW-2683 | South Cambridgeshire - Contact centre chatbot to improve resident satisfaction | https://www.local.gov.uk/case-studies/south-cambridgeshire-contact-centre-chatbot-improve-resident-satisfaction | South Cambridgeshire District Council has deployed a chatbot in its contact centre to improve resident satisfaction. The AI-powered chatbot responds to common queries instantly, freeing staff to handle more complex issues and improving overall service efficiency. | Local | United Kingdom | UK | South Cambridgeshire | Local Government | General public services | General public services n.e.c. | In development | 2.025 | Public services and engagement | Service personalisation (various) | No | No | Artificial Intelligence | G2C | x | x | x | x | x | x | https://www.local.gov.uk/our-support/cyber-digital-and-technology/artificial-intelligence-hub/artificial-intelligence-case | Learning | Machine learning | Generative AI | chatbot | 28/08/2025 | |||||||||||||||
| PSTW-2696 | Chatbot for Mental Health and Wellbeing Support | https://www.hlp.city/en-gb/case-studies/mental-health-and-wellbeing-support | Since 2017, facing rising suicide rates in North Lanarkshire, the Hello Lamp Post initiative introduced interactive signage at three strategic public locations and online as part of the council’s “Let’s Talk” campaign; by 2021 it provided the community—including both adults and under-18s—with constant, easy access to tailored mental health advice and resources, and its early impact was notable: within 24 hours of launch in Airdrie, one person self-identified as at-risk, roughly a third of users were directed to critical mental health support and guidance, and 23 % were promptly pointed to emergency services—results deemed significant in light of the region’s upward trend in suicides. | Local | United Kingdom | UK | North Lanarkshire Council | Local Government | Social protection | Social protection n.e.c. | Implemented | 2.017 | Public services and engagement | Service personalisation (various) | No | No | Artificial Intelligence | G2C | x | x | x | x | x | x | https://www.youtube.com/watch?v=1L_btfdalv0 | Learning | Machine learning | chatbot | 02/09/2025 | ||||||||||||||||
| PSTW-2697 | Chatbot for Collecting Patient Feedback | https://www.hlp.city/en-gb/case-studies/collecting-patient-feedback | At the Royal United Hospital (RUH) in Bath, an NHS acute-care facility, Hello Lamp Post deployed its interactive chat platform—rooted in the Friends and Family Test (FFT)—within Urgent Care and Orthopaedic Outpatient wards to ease administrative burdens, automate survey delivery, and reduce nurses’ workload; as a result, feedback completion rates skyrocketed from a mere 2 % to 70 %, each department saved around 300 staff-hours annually (equating to £11 per hour in staffing cost savings), and the hospital gathered detailed insights—58 % of orthopaedic patients rated their care as good, while 5 % highlighted areas for improvement—demonstrating how an engaging digital assistant can transform patient engagement and operational efficiency | Local | United Kingdom | UK | NHS Royal United Hospital Bath | Local Government | Health | Outpatient services. | Implemented | 2.022 | Public services and engagement | Service personalisation (various) | No | No | Artificial Intelligence | G2C | x | x | x | x | x | x | https://www.bathecho.co.uk/news/health/new-feedback-tool-patients-families-ruh-98616/ | Learning | Machine learning | Generative AI | chatbot | 02/09/2025 | |||||||||||||||
| PSTW-2753 | Chatbot for the consultation of the AI Act | https://olympus.uniurb.it/index.php?option=com_content&view=article&id=34260:inail,-comunicato-22-aprile-2025-inail-sperimenta-un-chatbot-per-la-consultazione-dell%E2%80%99ai-act&catid=6&Itemid=137 | INAIL has developed an experimental AI‑based chatbot — built on a large language model — to support consultation of the European AI Act. The chatbot is specialised in answering questions about the regulation, and in particular about its implications for health and safety at work. By using a technique known as Retrieval‑Augmented Generation (RAG), the system combines the model’s linguistic capabilities with a curated legal knowledge base (text of the regulation, summaries, indices) to generate clear, coherent responses to user queries. In tests, this chatbot outperformed other models in terms of clarity, completeness, relevance and accuracy. In future, the tool could be expanded or adapted to address other topics in occupational health & safety or regulatory compliance more broadly. | National | Italy | IT | Italian National Institute for Insurance against Accidents at Work (INAIL) | Central-Government | General public services | General public services n.e.c. | In development | 2.025 | Public services and engagement | Service personalisation (various) | No | No | Artificial Intelligence | G2C | x | x | x | x | x | x | https://www.puntosicuro.it/robotica-intelligenza-artificiale-C-137/inail-sperimenta-un-chatbot-per-la-consultazione-dell-ai-act-AR-25322/ | Learning | Machine learning | Natural language processing | chatbot | 01/12/2025 | |||||||||||||||
| PSTW-2768 | VRK chatbot: AI-powered support during the elections in Lithuania | https://tilde.ai/case-study/ai-chatbot-for-vrk/ | The VRK AI Chatbot is an AI-powered virtual assistant developed by Tilde for the Central Electoral Commission of Lithuania (VRK). Designed to provide reliable and accessible support, the chatbot answers a wide range of election-related questions from voters, candidates, and election staff, operating around the clock to ensure timely assistance. It significantly reduces the workload on human staff by handling thousands of interactions, particularly during high-traffic periods such as presidential elections. The chatbot was carefully trained in close collaboration with the VRK team to ensure accuracy, security, and compliance with official electoral information. Beyond its core functionality of answering inquiries, the VRK AI Chatbot is structured to continuously improve, with potential future enhancements including support for multiple languages, expanded features, and more personalized user interactions. By offering instant access to election guidance, the chatbot plays a key role in enhancing transparency, accessibility, and efficiency in the electoral process. | National | Lithuania | LT | Central Electoral Commission of Lithuania (VRK) | Central-Government | General public services | General public services n.e.c. | Implemented | 2.024 | Public services and engagement | Service personalisation (various) | No | No | Artificial Intelligence | G2C | x | x | x | x | x | x | https://tilde.ai/ | Learning | Machine learning | Natural language processing | chatbot | 12/12/2025 | |||||||||||||||
| PSTW-2769 | Next-level eLearning: AI Chatbot with LLM revolutionises academic communication and learning processes | https://tilde.ai/case-study/next-level-elearning-ai-chatbot-with-llm-revolutionizes-academic-communication-and-learning-processes/ | The Digne eLearning AI Chatbot is an advanced, AI‑powered virtual assistant developed by Tilde to transform academic communication and support within university courses. Integrated directly with the Moodle learning management system and equipped with large language model (LLM) capabilities, Digne provides students with personalised, context‑aware information about their course progress, grades, and study materials, while also helping academic staff streamline communication and administrative tasks. Unlike traditional chatbots with only predefined Q&A, Digne is trained on real course content such as lecture materials, presentations, and videos, enabling it to generate comprehensive responses to open‑ended student queries. By combining guided dialogues with AI‑generated answers, the chatbot enhances learning efficiency, assists with exam preparation, and improves overall interaction between students and educators as part of a broader digitalisation initiative in higher education. | National | Lithuania | LT | University of Latvia | Academic-Research | Education | Education n.e.c. | Implemented | 2.023 | Public services and engagement | Service personalisation (various) | No | No | Artificial Intelligence | G2C | x | x | x | x | x | x | https://tilde.ai/ | Learning | Machine learning | Generative AI | chatbot | 12/12/2025 | |||||||||||||||
| PSTW-2771 | Sector 3 City Hall's AI-powered chat system | https://www.primarie3.ro/index.php/presa/comunicat/primaria-sectorului-3-prima-administratie-publica-din-romania-cu-inteligenta-artificiala/6120?utm_source=chatgpt.com | Since 2023, the City Hall of Sector 3 in Bucharest has implemented an AI‑powered chat system on its official website (www.primarie3.ro), making it one of the first local administrations in Romania to adopt this kind of technology for citizen engagement. The system is designed to assist residents with information and administrative queries 24/7, offering quick responses to typical questions and helping streamline access to municipal services. The AI component is described by the City Hall as being in a learning phase, improving over time based on interactions with users. Sector 3 positioned this initiative as part of its digital modernization efforts to strengthen direct communication between local authorities and citizens. | Local | Romania | RO | City Hall of Sector 3 in Bucharest | Local Government | General public services | General public services n.e.c. | Implemented | 2.023 | Public services and engagement | Service personalisation (various) | No | No | Artificial Intelligence | G2C | x | x | x | x | x | x | https://www.jopafl.com/uploads/issue32/PANA_MICU_ARTIFICIAL_INTELLIGENCE_PUBLIC_SECTOR_CHALLENGES_OPPORTUNITIES_BEST_PRACTICES.pdf | Learning | Machine learning | Natural language processing | chatbot | 16/12/2025 | |||||||||||||||
| PSTW-2772 | Galicea Commune's Chatbot | https://www.jopafl.com/uploads/issue32/PANA_MICU_ARTIFICIAL_INTELLIGENCE_PUBLIC_SECTOR_CHALLENGES_OPPORTUNITIES_BEST_PRACTICES.pdf | In Galicea Commune (Vâlcea County), an “AI Galicea” chatbot has been introduced by the local municipality to support citizens with information and queries related to public services. While the official municipal website does not prominently detail the chatbot itself, research on AI usage in Romanian local governments cites AI Galicea as an example of a chatbot implemented at the commune level, reflecting early adoption of AI technologies by smaller public administrations to improve governance and service delivery. This aligns with broader efforts in Romania to explore AI for enhancing public sector interactions as part of ongoing digital transformation strategies. | Local | Romania | RO | Galicea Commune | Local Government | General public services | General public services o.a.l. | Implemented | 2.024 | Public services and engagement | Service personalisation (various) | No | No | Artificial Intelligence | G2C | x | x | x | x | x | x | https://www.jopafl.com/uploads/issue32/PANA_MICU_ARTIFICIAL_INTELLIGENCE_PUBLIC_SECTOR_CHALLENGES_OPPORTUNITIES_BEST_PRACTICES.pdf | Learning | Machine learning | Natural language processing | chatbot | 16/12/2025 | |||||||||||||||
| PSTW-2775 | AI Chatbot in the City of Athens | https://www.mindseed.gr/en/projects/ai-city-of-athens | The City of Athens implemented an AI-powered search engine and digital agent on its official website to improve access to municipal services. Using Google Gemini, residents and visitors can ask questions about city services and receive instant answers via a 24/7 chatbot, making information more readily available without the need for direct human assistance. All queries, responses, and error logs are anonymised and securely stored in the cloud, allowing the system to continuously learn and improve over time. This initiative aims to make public-service information faster, more efficient, and user-friendly, while enhancing transparency, reducing administrative workload, and improving the overall experience for citizens and visitors alike. | Local | Greece | EL | City of Athens | Local Government | General public services | General public services n.e.c. | Implemented | 2.025 | Public services and engagement | Service personalisation (various) | No | No | Artificial Intelligence | G2C | x | x | x | x | x | x | https://publicpolicy.google/article/driving-public-good-eu/ | Learning | Machine learning | Generative AI | chatbot | 05/12/2025 | |||||||||||||||
| PSTW-2776 | A chatbot to protect the identities of those reporting school bullying | https://www.inria.fr/en/chatbot-protect-identities-reporting-school-bullying-ai | The project, led by Inria’s team Petscraft, aims to develop an AI-based chatbot that allows victims or witnesses of school bullying to report incidents while preserving their anonymity. The chatbot uses privacy-enhancing technologies to rewrite or filter reports so the identity of the reporter cannot be inferred, protecting against the risk that a large language model might deduce personal traits from the text. To ensure data privacy, the approach is first tested on public datasets before applying it to sensitive bullying reports. The long-term goal is to provide a secure, anonymising tool that encourages safe reporting while helping schools detect and address bullying more effectively. | National | France | FR | Inria | Academic-Research | Social protection | Social protection n.e.c. | In development | 2.025 | Public services and engagement | Service personalisation (various) | No | No | Artificial Intelligence | G2C | x | x | x | x | x | x | https://www.inria.fr/en/chatbot-protect-identities-reporting-school-bullying-ai | Learning | Machine learning | Natural language processing | chatbot | 05/12/2025 | |||||||||||||||
| PSTW-2779 | AI Act Chatbot | https://www.digitalaustria.gv.at/themen/kuenstliche-intelligenz/ki-monitor/ai-act-chatbot.html | The AI Act Chatbot by Digital Austria is an online service developed to assist citizens, businesses, and public institutions in understanding and complying with the European AI Act. Launched in 2024, the chatbot provides detailed guidance on the regulations governing AI systems, including the different risk categories, compliance requirements, and the rights and obligations of developers and users under the law. Designed as an interactive and user-friendly tool, it translates complex legislative language into accessible explanations, enabling organisations to implement AI technologies responsibly and in accordance with European legal standards. The service also supports Austria’s broader digital governance strategy, which aims to foster transparency, ethical AI practices, and informed citizen engagement with emerging technologies. By providing immediate, practical advice and references, the AI Act Chatbot helps reduce the barriers to understanding and applying the EU AI regulatory framework, strengthening compliance, trust, and adoption of AI across both public and private sectors. | National | Austria | AT | Digital Austria | Central-Government | General public services | General services | Implemented | 2.024 | Public services and engagement | Service personalisation (various) | No | No | Artificial Intelligence | G2C | x | x | x | x | x | x | https://www.digitalaustria.gv.at/themen/kuenstliche-intelligenz/ki-monitor/ai-act-chatbot.html | Learning | Machine learning | Generative AI | chatbot | 15/12/2025 | |||||||||||||||
| PSTW-2791 | Supportbot for Vejle Municipality | https://clevercall.ai/en/supportbot-for-vejle-municipality/ | Supportbot for Vejle Municipality is an AI-powered voice assistant implemented by CleverCall to help the roughly 8,500 employees of Vejle Municipality with IT issues 24/7. The system answers phone calls outside normal support hours, provides clear guidance, sends links to detailed instructions and video tutorials, and continuously learns from daily queries to improve its responses. This ensures staff can quickly resolve routine IT problems (like forgotten passwords or peripheral malfunctions) at any time, freeing up the human support team to focus on more complex cases and reducing workflow disruptions. | Local | Denmark | DK | Vejle Municipality | Local Government | General public services | General public services n.e.c. | Implemented | 2.025 | Internal management | Internal support processes | No | No | Artificial Intelligence | G2C | x | x | x | x | x | x | https://videncenter.kl.dk/media/fwehh4l0/inspirationskatalog-syv-eksempler-med-generativ-ai-i-den-offentlige-sektor.pdf | Learning | Machine learning | Generative AI | chatbot | 16/12/2025 | |||||||||||||||
| PSTW-2792 | CostAI Kalundborg | https://videncenter.kl.dk/nyheder/2025/tag-til-costai-kalundborg-hvor-de-skarpe-botter-bor | The project CostAI Kalundborg aims to gather and unify the various AI‑tools used by a municipality into a single, user‑friendly platform. The idea arose because staff at Kalundborg Kommune found it increasingly difficult to navigate the growing number of disparate AI solutions — chatbots, specialist assistants, translation tools, meeting‑minute automation and more. To solve this, the municipality partnered with a small Danish tech startup, Promte, to build an app that works on PC, tablet and mobile, serving as a central “AI‑hub” for municipal employees. Through the app staff will be able to access intranet chat, AI‑powered assistants trained on internal policies, automatic meeting transcription and minutes, translation support, and links to other administrative or digital‑service tools. The goal is to make it easier and safer for public‑sector employees to use AI by simplifying access, ensuring data stays within secure municipal boundaries, and giving all features through one consolidated entry point — rather than having multiple separate tools. | Local | Denmark | DK | Kalundborg Kommune | Local government | General public services | General public services n.e.c. | In development | 2.025 | Public services and engagement | Service personalisation (various) | No | No | Artificial Intelligence | G2C | x | x | x | x | x | x | https://videncenter.kl.dk/nyheder/2025/tag-til-costai-kalundborg-hvor-de-skarpe-botter-bor | Services | AI services | chatbot | 09/12/2025 | ||||||||||||||||
| PSTW-2855 | Florence's First AI-powered chatbot | https://www.florencedailynews.com/2025/09/15/florence-launches-festinalente-its-first-ai-powered-chatbot/ | The City of Florence has launched FestinaLente, its first generative-AI chatbot, to simplify the process of changing one’s official residence and improve access to municipal services. The chatbot provides clear information on requirements, documents and procedures, helping citizens avoid phone calls, emails or in-person visits. FestinaLente understands natural-language questions and responds in 14 languages, making it accessible to both residents and international users. Available 24/7 on the city’s website, it offers first-level assistance based on official municipal documentation validated by demographic-services staff. Built on a modular AI platform that allows the city to choose among different large-language models, it uses ChatGPT as its main engine. The project was developed by the City of Florence with support from its in-house digital services company, Firenze Smart, and a private technology partner. The chatbot does not replace staff but reduces routine workloads, allowing employees to focus on more complex tasks. | Local | Italy | IT | City of Florence | Local government | General public services | General public services n.e.c. | Implemented | 2.025 | Public services and engagement | Service personalisation (various) | No | No | Artificial Intelligence | G2C | x | x | x | x | x | x | https://www.florencedailynews.com/2025/09/15/florence-launches-festinalente-its-first-ai-powered-chatbot/ | Learning | Machine learning | Generative AI | chatbot | 10/12/2025 | |||||||||||||||
| PSTW-2856 | Chatbot to revolutionise tax return analysis | https://en.ilsole24ore.com/art/finance-launches-chatbot-to-revolutionise-tax-return-analysis-AHMYyir | Italy’s Finance Department, through its Economic-Fiscal Studies and Research Directorate, has introduced a new AI-powered chatbot designed to support the analysis of tax returns. The system uses advanced artificial intelligence to process large volumes of fiscal data, enabling faster identification of inconsistencies, patterns, and potential risk indicators across millions of declarations. By automating parts of the review process traditionally carried out manually, the tool aims to reduce processing times, improve accuracy, and allow tax officials to focus on more complex investigative work. This initiative forms part of a broader strategy to modernise tax-administration processes and strengthen data-driven decision-making within Italy’s Ministry of Economy and Finance. | National | Italy | IT | Finance Department's Economic-Fiscal Studies and Research Directorate | Central-Government | General public services | General public services n.e.c. | Implemented | 2.025 | Public services and engagement | Service personalisation (various) | No | No | Artificial Intelligence | G2B | x | x | x | x | x | x | https://en.ilsole24ore.com/art/finance-launches-chatbot-to-revolutionise-tax-return-analysis-AHMYyir | Learning | Machine learning | Generative AI | chatbot | 10/12/2025 | |||||||||||||||
| PSTW-2857 | German government hotline 115: AI-based chatbot for 24/7 support | https://www.ziptone.nl/en/nieuws/duitse-overheidslijn-115-vervangt-chatbot-na-een-jaar-door-ai-versie/ | Germany’s national public-service hotline “115,” which provides citizens with information and guidance on a wide range of administrative procedures, has upgraded its digital support system by replacing its earlier rule-based chatbot with a new AI-driven version. The previous chatbot could only respond to predefined questions and followed rigid decision trees, often leading to limited or unsatisfactory answers. The new system, powered by modern generative AI, is designed to understand natural language queries far more flexibly and provide more accurate, context-aware responses. This upgrade aims to make interactions with public administration faster, clearer and more user-friendly. Citizens contacting the 115 service — whether online or through supported digital channels — can now receive more relevant information about services such as registrations, permits, public benefits or local administrative procedures. The shift reflects a broader German effort to modernise public-sector communication tools and improve accessibility and efficiency in everyday administrative interactions. | National | Germany | DE | German Government | Central-Government | General public services | General public services n.e.c. | Implemented | 2.025 | Public services and engagement | Service personalisation (various) | No | No | Artificial Intelligence | G2C | x | x | x | x | x | x | https://www.ziptone.nl/en/nieuws/duitse-overheidslijn-115-vervangt-chatbot-na-een-jaar-door-ai-versie/ | Learning | Machine learning | Generative AI | chatbot | 10/12/2025 | |||||||||||||||
| PSTW-2919 | Implementation of AI in the knowledge database in Topdesk | https://videncenter.kl.dk/viden-og-vaerktoejer/ai/kommunernes-ai-landkort | Ebbot is an AI chatbot, implemented by Randers Municipality, and integrated into TOPdesk, the municipality’s ITSM system. It is available to municipal employees and can answer questions related to IT, accounting, and procurement. Ebbot searches previous cases and knowledge articles to provide answers, and if it cannot find a solution, it assists the user in creating a support ticket. | Local | Denmark | DK | Randers Municipality | Local government | General public services | General public services n.e.c. | Implemented | 2.025 | Public services and engagement | Service personalisation (various) | No | No | Artificial Intelligence | G2C | x | x | x | x | x | x | https://videncenter.kl.dk/viden-og-vaerktoejer/ai/kommunernes-ai-landkort | Learning | Machine learning | Natural language processing | chatbot | 19/12/2025 | |||||||||||||||
| PSTW-2920 | Roboref - Generative AI in the Randers Municipality | https://videncenter.kl.dk/viden-og-vaerktoejer/ai/kommunernes-ai-landkort | Roboref is an AI tool that automatically records, transcribes, and generates summaries and notes from meetings using generative AI. It is used for both internal and external meetings in the public sector, freeing up time for other work while enhancing the objectivity of documentation. Currently, a select group of employees in Randers Municipality are testing Roboref for internal meetings. | Local | Denmark | DK | Randers Municipality | Local government | General public services | General public services n.e.c. | Implemented | 2.025 | Public services and engagement | Service personalisation (various) | No | No | Artificial Intelligence | G2C | x | x | x | x | x | x | https://videncenter.kl.dk/viden-og-vaerktoejer/ai/kommunernes-ai-landkort | Learning | Machine learning | Generative AI | chatbot | 19/12/2025 | |||||||||||||||
| PSTW-2921 | Copilot in the Randers Municipality | https://algoritmes.overheid.nl/en/algoritme/gm0202/65655913/microsoft-365-copilot?utm_source=chatgpt.com | All employees in Randers Municipality have been given access to use Copilot in Edge, Microsoft’s generative AI assistant integrated into the Edge browser to support everyday work tasks. Copilot helps with generating and summarizing text, drafting communications, and assisting with routine productivity tasks. This deployment in Randers reflects a broader trend in public administration: many municipalities and regional authorities across the Netherlands and other local governments are adopting Microsoft 365 Copilot to support staff in writing texts, creating summaries, preparing for meetings, and improving overall productivity. Examples include implementations in the Municipality of Arnhem, Breda, Almere, Zaanstad, and other regional bodies, where Copilot is already in use as a generative AI tool integrated with Microsoft 365 applications to support employees in their daily work. | Local | Denmark | DK | Randers Municipality | Local government | General public services | General public services n.e.c. | Implemented | 2.025 | Public services and engagement | Service personalisation (various) | No | No | Artificial Intelligence | G2C | x | x | x | x | x | x | https://videncenter.kl.dk/viden-og-vaerktoejer/ai/kommunernes-ai-landkort | Learning | Machine learning | Generative AI | chatbot | 19/12/2025 | |||||||||||||||
| PSTW-2931 | ELLI - Chatbot of the City of Linz | https://ki.linz.at/?mtm_campaign=chatbot&mtm_source=navigation-service&mtm_medium=website&mtm_content=navigation | The City of Linz provides an AI-powered chatbot service called “ELLI” (short for Elektronische Linzerin) to help citizens find information about municipal services quickly and easily. ELLI is available 24/7 online and answers questions about topics like administrative services, opening hours, civic procedures, local information and more, using natural language understanding to interpret queries and point users to relevant details or external resources. The chatbot supports multilingual interaction, is continuously updated with new content, and helps reduce routine inquiries to the City’s Teleservice Center by providing instant responses to common questions. | Local | Austria | AT | Cityf of Linz | Local government | General public services | General public services n.e.c. | Implemented | 2.019 | Internal management | Internal support processes | No | No | Artificial Intelligence | G2C | x | x | x | x | x | x | https://www.linz.at/serviceguide/viewchapter.php?chapter_id=121437 | Learning | Machine learning | Generative AI | chatbot | 20/01/2026 | |||||||||||||||
| PSTW-2754 | Open Source AI Assistant in Polish digital-wallet app mObywatel | https://interoperable-europe.ec.europa.eu/collection/open-source-observatory-osor/news/public-administrative-tasks-facilitated-open-source | Under Open Source Observatory (OSOR), Poland projects to integrate an open-source AI assistant into its national digital-wallet app mObywatel. The assistant, powered by the Polish Large Language Model (PLLuM), is designed to help citizens navigate administrative procedures by answering questions in natural language and guiding them through official processes. By simplifying bureaucracy, improving accessibility for people with limited digital skills or disabilities, and reducing the workload on public administrations, the initiative aims to make public services more user-friendly. Its open-source foundation also supports transparency, digital sovereignty, and long-term public value. | National | Poland | PL | Polish Government | Central-Government | General public services | General public services n.e.c. | In development | 2.025 | Public services and engagement | Service personalisation (various) | No | Yes | Artificial Intelligence | G2C | x | x | x | x | x | x | https://interoperable-europe.ec.europa.eu/collection/open-source-observatory-osor/news/public-administrative-tasks-facilitated-open-source | Learning | Machine learning | Natural language processing | virtual assistant | 01/12/2025 | |||||||||||||||
| PSTW-2756 | AppLI, the Web Coach of the Ministry of Labour and Social Policies | https://appli.lavoro.gov.it/ | AppLI is a virtual assistant launched in September 2025 by the Italian Ministry of Labour and Social Policies in collaboration with INPS, designed to support young people, especially those aged 18–35 who are not in education, employment, or training (NEET), in their journey toward employment. Accessible 24/7 via the Ministry’s portal, AppLI provides a personalised guidance path, helping users assess their interests, skills, and goals, explore job and learning opportunities in their area, and identify relevant training or educational resources to close skills gaps. The system also offers reminders and encouragement to help transform intentions into concrete steps toward employment. AppLI represents the first multi-agent generative AI system deployed by an Italian public administration and was developed through a co-design process involving young people, regional authorities, employment centres, and sector experts to ensure it meets real needs. Its aim is to complement existing public employment services by offering a more accessible, inclusive, and technology-driven support tool to help young people navigate training and the job market more effectively. | National | Italy | IT | Italian Ministry of Labour and Social Policies | Central-Government | Economic affairs | General economic, commercial and labour affair | Implemented | 2.025 | Public services and engagement | Service personalisation (various) | No | No | Artificial Intelligence | G2C | x | x | x | x | x | x | https://www.lavoro.gov.it/notizie/pagine/parte-appli-il-web-coach-del-ministero-del-lavoro-e-delle-politiche-sociali | Learning | Machine learning | Natural language processing | virtual assistant | 01/12/2025 | |||||||||||||||
| PSTW-2783 | Virtual civil servant - Galati City Hall | https://oecd.ai/en/dashboards/policy-initiatives/virtual-civil-servants | The project Virtual Civil Servants explores how AI-powered assistants and digital tools can support public administrations — specifically helping civil servants perform tasks more efficiently, and improving how citizens interact with government services. It aims to automate routine administrative processes (such as handling requests, sorting and verifying documents, providing information), enabling faster, more accessible and responsive public-service delivery. By doing so, it seeks to relieve human civil servants of repetitive, time-consuming tasks so they can focus on more complex or value-adding duties — while making public services more efficient, transparent and user-friendly. Within this project, Galați City Hall also launched a virtual civil servant based on artificial intelligence. The virtual assistant is currently being trained and tested but will soon be able to provide information to citizens on town planning, taxes, fees, and other local revenues. | Local | Romania | RO | Galati City Hall | Local Government | General public services | General public services n.e.c. | In development | 2.025 | Public services and engagement | Service personalisation (various) | No | No | Artificial Intelligence | G2C | x | x | x | x | x | x | https://oecd.ai/en/dashboards/policy-initiatives/virtual-civil-servants | Learning | Machine learning | virtual assistant | 09/12/2025 | ||||||||||||||||
| PSTW-2793 | Digital assistant "Mriya" for learning | https://mriia.gov.ua/en/app | In 2024, Ukraine’s Ministry of Digital Transformation launched Mriya, a digital assistant specifically designed to support education across the country. The platform harnesses the power of artificial intelligence to assist students in their learning, offering personalised educational content tailored to individual needs, helping them to better understand complex subjects and improve their academic performance. In addition to supporting students, Mriya provides teachers and parents with tools to monitor progress, manage assignments, and facilitate more effective learning experiences. The platform was initially piloted in a select number of schools in 2024, allowing the Ministry to test its functionality, gather feedback, and refine its features. Following the successful pilot, Mriya was expanded nationwide in 2025, with thousands of schools across Ukraine integrating the system into their daily educational activities. The initiative forms part of a broader effort by the Ukrainian government to modernise the education system, incorporate digital technologies, and make learning more accessible and interactive for students of all ages. | National | Ukraine | UA | Ukraine's Ministry of Digital Transformation | Central-Government | Education | Education n.e.c. | Implemented | 2.024 | Public services and engagement | Service personalisation (various) | No | No | Artificial Intelligence | G2C | x | x | x | x | x | x | https://www.kmu.gov.ua/en/news/ukrainskyi-osvitnii-proekt-mriia-otrymav-pidtrymku-vid-google | Learning | Machine learning | Natural language processing | virtual assistant | 16/12/2025 | |||||||||||||||
| PSTW-2914 | ChatPat - Virtual assistant | https://chatpat.provincia.tn.it/en/how-it-works | Chat PaT is a virtual assistant developed by the Autonomous Province of Trento to help citizens, businesses, professionals and other users easily navigate and access the Province’s public services through a simple chat interface. It allows users to ask questions in natural language and receive immediate answers and direct links to official information and online forms from the Province’s Service Catalogue, without needing to know technical or bureaucratic terms. The assistant supports multiple languages (Italian, English, German, French, Spanish and Portuguese), is available 24/7, and is designed to complement (not replace) traditional contact channels, reducing search time and improving user experience. The service uses official provincial data, anonymises interactions to protect privacy under GDPR, and is continuously improved using user feedback. Chat PaT was created as part of the Province’s “Digitalisation of the Public Administration – Citizens and Digital Businesses” Flagship Project funded under the National Complementary Plan to the PNRR, with the aim of simplifying access to digital public services and enhancing usability. | Local | Italy | IT | Autonomous Province of Trento | Local government | General public services | General public services n.e.c. | Implemented | 2.025 | Public services and engagement | Service personalisation (various) | No | No | Artificial Intelligence | G2C | x | x | x | x | x | x | https://www.provincia.tn.it/ | Learning | Machine learning | Generative AI | virtual assistant | 18/12/2025 | |||||||||||||||
| PSTW-2926 | InDialog Voicebot – Internal AI Support for ESDH and Topdesk | https://videncenter.kl.dk/viden-og-vaerktoejer/ai/kommunernes-ai-landkort | InDialog Voicebot allows employees to quickly obtain answers and access guidance via voice commands, streamlining internal processes and freeing up time for more complex tasks. The solution is currently in the testing phase and is used internally to support guidance within the municipality’s ESDH system and Topdesk. | Local | Denmark | DK | Hvidovre Municipality | Local government | General public services | General public services n.e.c. | In development | 2.025 | Public services and engagement | Service personalisation (various) | No | No | Artificial Intelligence | G2C | x | x | x | x | x | x | https://videncenter.kl.dk/viden-og-vaerktoejer/ai/kommunernes-ai-landkort | Learning | Machine learning | Natural language processing | voicebot | 19/12/2025 | |||||||||||||||
| PSTW-2685 | Swindon Borough Council: Simply Readable, an AI easy-read solution | https://www.local.gov.uk/case-studies/swindon-borough-council-simply-readable-ai-easy-read-solution | Swindon Borough Council’s Simply Readable project is an innovative AI-powered solution designed to create accessible Easy-Read documents for residents with learning disabilities. By using artificial intelligence, the council dramatically reduced the time and cost of producing these documents—from weeks and hundreds of pounds to just minutes and pennies per page. Developed in collaboration with residents, the tool ensures clear language, larger fonts, and helpful visuals, making vital information easier to understand. It also supports translation into 75 languages, promoting broader inclusivity across the community. | Local | United Kingdom | UK | Swindon Borough Council | Local Government | Social protection | Sickness and disability. | Implemented | 2.025 | Internal management | Internal support processes | No | No | Artificial Intelligence | G2C | x | x | x | x | x | x | https://www.local.gov.uk/our-support/cyber-digital-and-technology/artificial-intelligence-hub/artificial-intelligence-case | Learning | Machine learning | Generative AI | 28/08/2025 | ||||||||||||||||
| PSTW-2692 | PlaceBuilder - Unlocking community-driven development | https://www.thefuturefox.com/hanwood-park | Hanwood Park is set to become one of the UK’s most ambitious new housing developments, comprising 5,500 homes alongside schools, shops, employment hubs, and recreational areas. As the master developer sought planning permission, they recognized the importance of maintaining community involvement throughout the process. To support this, Hanwood Park LLP partnered with The Future Fox and deployed the PlaceBuilder digital engagement platform. The intuitive, mobile-first tool allowed them to rapidly design and launch a branded consultation—in under seven days—with polls on crucial themes like sustainability, wellbeing, and the masterplan. Cost-effective social media promotion ensured diverse community participation, while built-in analytics offered real-time insights and saved weeks of manual analysis. The result was a highly engaging consultation capturing a broad range of voices, enabling the developer to act on meaningful, representative feedback and stay responsive to local needs with clarity and confidence. | Local | United Kingdom | UK | City of Northamptonshire | Local Government | Housing and community amenities | Housing development. | Implemented | 2.024 | Public services and engagement | Service personalisation (various) | No | No | Artificial Intelligence | G2C | x | x | x | x | x | x | https://www.thefuturefox.com/ | Services | 29/08/2025 | ||||||||||||||||||
| PSTW-2782 | Virtual civil servant - Local public administration in Cluj | https://oecd.ai/en/dashboards/policy-initiatives/virtual-civil-servants | The project Virtual Civil Servants explores how AI-powered assistants and digital tools can support public administrations — specifically helping civil servants perform tasks more efficiently, and improving how citizens interact with government services. It aims to automate routine administrative processes (such as handling requests, sorting and verifying documents, providing information), enabling faster, more accessible and responsive public-service delivery. By doing so, it seeks to relieve human civil servants of repetitive, time-consuming tasks so they can focus on more complex or value-adding duties — while making public services more efficient, transparent and user-friendly. The creation of this 'civil servant,' based on artificial intelligence, is part of the digitisation process of procedures in the local public administration in Cluj. | Local | Romania | RO | City of Cluj | Local Government | General public services | General public services n.e.c. | In development | 2.025 | Public services and engagement | Service personalisation (various) | No | No | Artificial Intelligence | G2C | x | x | x | x | x | x | https://oecd.ai/en/dashboards/policy-initiatives/virtual-civil-servants | Learning | Machine learning | 09/12/2025 | |||||||||||||||||
| PSTW-2784 | Digitalised Yellow Book | https://www.google.com/url?sa=t&rct=j&q=&esrc=s&source=web&cd=&cad=rja&uact=8&ved=2ahUKEwinwYSqzdWOAxXKV6QEHVV6FjcQFnoECAkQAQ&url=https%3A%2F%2Fwww.livroamarelo.gov.pt%2Fen%2Fweb%2Fguest%2Fhomee&usg=AOvVaw297djAu2bhosfAn94-058w&opi=89978449 | The Digitalised Yellow Book project aims to modernise and streamline the traditional “Yellow Book,” a paper-based register historically used by citizens to submit complaints, suggestions or feedback to public authorities. By converting this system into a fully digital platform, the project seeks to create a faster, more transparent and more accessible way for citizens to communicate with government services. The digital version improves the processing and evaluation of submissions by replacing manual handling with electronic workflows, which helps reduce delays and ensures greater consistency in how cases are reviewed. It also enhances the overall quality of public-service delivery by making it easier for authorities to track issues, respond more efficiently and analyse trends in citizen feedback. Through this initiative, governments aim to strengthen public trust, increase administrative efficiency and promote more open and responsive governance. | National | Portugal | PT | Agency for Administrative Modernisation | Central-Government | General public services | General public services n.e.c. | In development | 2.025 | Public services and engagement | Service personalisation (various) | No | No | Artificial Intelligence | G2C | x | x | x | x | x | x | https://oecd.ai/en/dashboards/policy-initiatives/digitalised-yellow-book | Learning | Machine learning | 09/12/2025 | |||||||||||||||||
| PSTW-2798 | ChatGPT Edu into Estonia's education system | https://openai.com/index/estonia-schools-and-chatgpt/ | The project plans to introduce ChatGPT Edu – a version of ChatGPT built for educational use – across Estonia’s secondary‑school system. Starting in 2025, students (initially 10th and 11th graders) and their teachers will be granted access to ChatGPT Edu, alongside support for custom AI tools designed for teaching and learning. Through this initiative, the aim is to embed AI into the national education system, helping students with learning and creativity, easing teachers’ workload (e.g. administrative tasks, lesson‑planning), and equipping the next generation with AI literacy and skills for the future. The project is part of Estonia’s AI Leap 2025 initiative to integrate AI capabilities into education, providing free AI tools and a framework for their use in learning, launched by the President of Estonia as a public-private sector collaboration. | National | Estonia | EE | Government of Estonia | Central-Government | Education | Education n.e.c. | In development | 2.025 | Public services and engagement | Service integration (various) | No | No | Artificial Intelligence | G2C | x | x | x | x | x | x | https://e-estonia.com/ai-leap-2025-estonia-sets-ai-standard-in-education/ | Learning | Machine learning | Generative AI | 09/12/2025 | ||||||||||||||||
| PSTW-2860 | OpenAI For Greece - ChatGPT Edu in Secondary Education | https://openai.com/global-affairs/openai-for-greece/ | “OpenAI for Greece” is a newly launched partnership between OpenAI, the government of the Hellenic Republic, Onassis Foundation and Endeavor Greece. The initiative aims to expand access to high‑quality AI tools across two main fronts: education and entrepreneurship. In education, Greece will pilot a version of AI — ChatGPT Edu — in secondary schools, to help teachers integrate AI responsibly, boost productivity, and build AI literacy. In parallel, the programme launches a Greek AI Accelerator to support local AI‑focused start‑ups: selected ventures will receive access to OpenAI technology, credits, mentorship, compliance and scaling guidance, international exposure, and support in sectors aligned with Greece’s national priorities (education, public services, healthcare, climate). The goal is to leverage AI to foster human capital, innovation and economic growth across the country. | National | Greece | EL | Greek Government | Central-Government | Education | Secondary education | In development | 2.025 | Public services and engagement | Service personalisation (various) | No | No | Artificial Intelligence | G2C | x | x | x | x | x | x | https://openai.com/global-affairs/openai-for-greece/ | Learning | Machine learning | Generative AI | 10/12/2025 | ||||||||||||||||
| PSTW-2874 | Compar:IA - the chatbot arena | https://comparia.beta.gouv.fr/ | compar:IA is a French government-led digital platform designed to compare conversational AI models and educate citizens about generative AI. Developed within a state start-up initiative under the Ministry of Culture and integrated into Beta.gouv.fr, the platform allows users to interact with two anonymised AI models, evaluate their responses, and vote on the best output. These votes feed into a public dataset that helps improve AI models for the French language while respecting linguistic and cultural diversity. The platform serves both the general public and AI experts, providing a space to test, measure, and compare AI models, explore their characteristics, and use the data for research or educational purposes. It also helps raise awareness of AI limitations, biases, and ethical considerations, making AI more transparent and accessible. Additionally, the platform is expanding to other European countries, including Lithuania, Sweden, and Denmark, to support multilingual AI development. | National | France | FR | French Ministry of Culture | Central-Government | General public services | General public services n.e.c. | Implemented | 2.024 | Public services and engagement | Service personalisation (various) | No | No | Artificial Intelligence | G2C | x | x | x | x | x | x | https://www.data.gouv.fr/datasets/compar-ia/ | Learning | Machine learning | Generative AI | 15/12/2025 | ||||||||||||||||
| PSTW-2893 | ScreenreaderLB - AI-Powered Luxembourgish Accessibility for the Visually Impaired | https://mindigital.gouvernement.lu/en/dossiers/2024/tech-in-gov/projets-tech.html | The ScreenreaderLB solution, developed by the Government Information and Press Service, addresses the increasing need for accessible content in Luxembourgish for visually impaired users. Currently, the absence of speech synthesis technology for this language requires blind or visually impaired individuals to rely on screen readers in German or other languages. ScreenreaderLB aims to create a screen reader specifically for Luxembourgish, providing smooth and accurate speech synthesis to allow visually impaired users to interact more effectively with digital content, enhancing both their browsing experience and access to information. | National | Luxembourg | LU | Government Information and Press Service | Central-Government | Social protection | Sickness and disability. | Implemented | 2.025 | Public services and engagement | Service personalisation (various) | No | No | Artificial Intelligence | G2C | x | x | x | x | x | x | https://mindigital.gouvernement.lu/en/dossiers/2024/tech-in-gov/projets-tech.html | Learning | Machine learning | Natural language processing | 09/12/2025 | ||||||||||||||||
| PSTW-2904 | Saro: AI-powered educational digital assistant | https://www.romania-insider.com/saro-digital-nation-ro-schools-apr-2025 | Saro is an AI-powered educational assistant being introduced into schools and universities in Romania through a partnership between Digital Nation and the Romanian Ministry of Education and Research. It’s designed to help students, pupils, and teachers by enhancing motivation, reducing bureaucracy, and supporting personalised learning experiences. The initiative is part of a broader effort to integrate artificial intelligence into the national education system, with early pilots showing increased assignment completion and engagement. | National | Romania | RO | Romanian Ministry of Education and Research | Central-Government | Education | Education n.e.c. | In development | 2.025 | Public services and engagement | Service personalisation (various) | No | No | Artificial Intelligence | G2C | x | x | x | x | x | x | https://www.romania-insider.com/saro-digital-nation-ro-schools-apr-2025 | Learning | Machine learning | Generative AI | 12/12/2025 | ||||||||||||||||
| PSTW-2909 | AI Mobility Challenge - Traffic Info | https://mobilities-for.eu/espoo-embraces-ai-and-data-innovation-to-cut-traffic-emissions-startups-take-the-lead/ | Traffic Info introduces a multilingual AI system that delivers traffic updates and announcements in natural language — both spoken and written forms. This enhances communication with residents and visitors from diverse backgrounds, ensuring easier access to real-time mobility information. By supporting multiple languages and intuitive formats, the tool improves user experience and helps individuals make informed travel decisions, contributing to smoother and more efficient traffic flows. | Local | Finland | FI | City of Espoo | Local government | Economic affairs | Transport | Pilot | 2.025 | Public services and engagement | Service personalisation (various) | No | No | Artificial Intelligence | G2C | x | x | x | x | x | x | https://mobilities-for.eu/espoo-embraces-ai-and-data-innovation-to-cut-traffic-emissions-startups-take-the-lead/ | Learning | Machine learning | Generative AI | 17/12/2025 | ||||||||||||||||
| PSTW-2911 | Processing of personal data, AI translation service on the Hello Espoo website | https://www.espoo.fi/en/city-and-decision-making/safety/data-protection/privacy-notices-mayors-office/processing-personal-data-ai-translation-service-on-hello-espoo-website | The City of Espoo is testing an AI-powered text and voice translation service on its Hello Espoo website from September 2025 to August 2026 to make content available in 13 languages and improve multilingual access to public services. The system collects usage data such as time of use, pages visited, and web domain (IP address), but this data cannot be linked to individual users. Data is used to implement, test, develop and improve the service, and feedback submitted via a form helps enhance accessibility. Usage data will be deleted by the end of the trial (no later than 31 August 2026) and feedback form responses are stored for 30 days. The City of Espoo and its service provider Voice Intuitive Oy process the data in compliance with GDPR, and no data is transferred outside the EU/EEA. Users retain their rights under EU data protection law. | Local | Finland | FI | City of Espoo | Local government | General public services | General public services n.e.c. | In development | 2.025 | Public services and engagement | Service personalisation (various) | No | No | Artificial Intelligence | G2C | x | x | x | x | x | x | https://eurocities.eu/latest/cities-lead-the-way-in-building-europes-ai-future/ | Learning | Machine learning | Generative AI | 17/12/2025 | ||||||||||||||||
| PSTW-2913 | Piedmont harnesses AI to bring healthcare to every corner | https://www.regione.piemonte.it/web/pinforma/notizie/torino-piemonte-si-candidano-per-guida-autonoma-citta-intelligenza-artificiale-sanita | Piedmont is seeking to transform healthcare delivery through AI, with a focus on diagnostics, organisational efficiency, and telemedicine. With over 40% of its territory being mountainous, the region is well-suited for remote healthcare solutions, including telemedicine cabins where patients can undergo medical exams with a trained operator present, while doctors connect remotely via video. AI systems would assist in diagnostics, patient monitoring, and optimising healthcare workflows, ensuring that even residents in remote or underserved areas have access to high-quality, timely medical care. This initiative exemplifies the potential of AI to enhance territorial health coverage and bridge gaps in healthcare accessibility. | Regional | Italy | IT | Piedmont Region | Local government | Health | Health n.e.c. | In development | 2.025 | Public services and engagement | Service integration (various) | No | No | Artificial Intelligence | G2C | x | x | x | x | x | x | https://www.riga.lv/en/projects/ai4citizens-supporting-ethical-and-effective-ai-governance-european-cities-and-regions | Learning | Machine learning | 17/12/2025 | |||||||||||||||||
| PSTW-2923 | RandersGPT | https://videncenter.kl.dk/viden-og-vaerktoejer/ai/kommunernes-ai-landkort | RandersGPT is an internal GPT for municipal employees, based on OpenAI in Azure. Its purpose is to provide employees with a more secure alternative to Copilot in Edge and ChatGPT. RandersGPT is used to assist with administrative tasks and is accessed through the municipality’s AI portal, where it is set up as an agent that can direct users to specialized assistants also available on the AI portal. | Local | Denmark | DK | Randers Municipality | Local government | General public services | General public services n.e.c. | Implemented | 2.025 | Public services and engagement | Service personalisation (various) | No | No | Artificial Intelligence | G2C | x | x | x | x | x | x | https://videncenter.kl.dk/viden-og-vaerktoejer/ai/kommunernes-ai-landkort | Learning | Machine learning | Generative AI | 19/12/2025 | ||||||||||||||||
| PSTW-2927 | KAILA - AI tool for Danish legislation | https://videncenter.kl.dk/viden-og-vaerktoejer/ai/kommunernes-ai-landkort | KAILA is an AI tool used to assist legal staff in handling complex legal tasks more efficiently. It can help with drafting legal documents, gathering relevant sources and arguments, providing new insights, and preparing for meetings. When used, KAILA always provides answers based on current Danish legislation and includes direct references to sources in Karnov, enabling legal staff to quickly and easily verify the information. | Local | Denmark | DK | Hvidovre Municipality | Local government | General public services | Executive and legislative organs, financial and fiscal affairs, external affairs. | Implemented | 2.025 | Public services and engagement | Service personalisation (various) | No | No | Artificial Intelligence | G2C | x | x | x | x | x | x | https://videncenter.kl.dk/viden-og-vaerktoejer/ai/kommunernes-ai-landkort | Learning | Machine learning | Generative AI | 19/12/2025 | ||||||||||||||||
| PSTW-2862 | Digital Doctor Assistant | https://www.ekathimerini.com/politics/1285299/greece-launches-ai-assistant-for-doctors-in-national-health-system/ | The Greek government has launched an AI‑powered tool known as Digital Doctor Assistant, now available to doctors through the national electronic health record system. Through the platform myHealthDoc, physicians can instantly access patients’ medical data, review histories, medications and test results, request summaries or personalized reports using natural‑language queries, and even use voice interaction. The aim is to reduce administrative burden, cut bureaucracy, speed up access to relevant clinical information, and support medical decision‑making within the public health system. Authorities say this marks the first deployment of AI in the country’s public health sector, as part of a broader digital‑health transformation effort. | National | Greece | EL | Greek Ministry of Health | Central-Government | Health | Hospital services. | In development | 2.025 | Public services and engagement | Service personalisation (various) | No | No | Artificial Intelligence | G2C | x | x | x | x | x | https://www.ekathimerini.com/politics/1285299/greece-launches-ai-assistant-for-doctors-in-national-health-system/ | Learning | Machine learning | Natural language processing | virtual assistant | 10/12/2025 | ||||||||||||||||
| PSTW-2759 | A comprehensive language model specifically trained on Luxembourg legislation | https://gemengen.lu/web/2025/10/27/lintelligence-artificielle-au-service-du-secteur-public-luxembourgeois/?utm_campaign=5cbf040cc07a760001000fda&utm_content=690332b16c0f710001915954&utm_medium=smarpshare&utm_source=linkedin | Luxembourg is developing a large language model trained specifically on national legislation, with the intention of making the country’s legal framework easier to navigate for professionals and more comprehensible for citizens. The model is being adapted to the particularities of Luxembourgish law and is designed to support legal research, improve access to information and reduce the complexity of interacting with official texts. | National | Luxembourg | LU | Government of Luxembourg | Central-Government | General public services | Executive and legislative organs, financial and fiscal affairs, external affairs. | In development | 2.025 | Public services and engagement | Data Sharing Management | No | No | Artificial Intelligence | G2C | x | x | x | x | x | https://gemengen.lu/web/2025/10/27/lintelligence-artificielle-au-service-du-secteur-public-luxembourgeois/?utm_campaign=5cbf040cc07a760001000fda&utm_content=690332b16c0f710001915954&utm_medium=smarpshare&utm_source=linkedin | Learning | Machine learning | 05/12/2025 | ||||||||||||||||||
| PSTW-2760 | AI in Education in Luxembourg | https://gemengen.lu/web/2025/10/27/lintelligence-artificielle-au-service-du-secteur-public-luxembourgeois/?utm_campaign=5cbf040cc07a760001000fda&utm_content=690332b16c0f710001915954&utm_medium=smarpshare&utm_source=linkedin | Luxembourg is deploying artificial intelligence to support personalised learning in the education system, creating tools that help pupils learn more effectively while also teaching them how to use AI responsibly. The initiative seeks to provide tailored guidance to students, accelerate their progress and ensure that all applications respect strict data-protection standards so that children’s personal information remains secure. | National | Luxembourg | LU | Government of Luxembourg | Central-Government | Education | Education n.e.c. | In development | 2.025 | Public services and engagement | Service personalisation (various) | No | No | Artificial Intelligence | G2C | x | x | x | x | x | https://gemengen.lu/web/2025/10/27/lintelligence-artificielle-au-service-du-secteur-public-luxembourgeois/?utm_campaign=5cbf040cc07a760001000fda&utm_content=690332b16c0f710001915954&utm_medium=smarpshare&utm_source=linkedin | Learning | Machine learning | 05/12/2025 | ||||||||||||||||||
| PSTW-2863 | Greek Government and Sword Health team up for AI-driven initiative | https://www.hospitalmanagement.net/news/greek-government-sword-health-initiative/?cf-view | The Greek government has partnered with Sword Health to launch an AI‑driven healthcare initiative that seeks to modernise how citizens access care. The programme will integrate AI into the national health hotline, which is the first point of contact for individuals seeking medical guidance or trying to navigate the healthcare system. By using AI for triage, coordination and user‑support tasks, the system aims to reduce waiting times, relieve pressure on hospitals, increase responsiveness and ensure consistent support across Greece, including rural and remote areas. This project is expected to serve more than 1 million citizens and is part of a broader ambition to build an AI-enhanced national health system, offering a “smart entry” point to care. | National | Greece | EL | Greek Ministry of Health | Central-Government | Health | Hospital services. | In development | 2.025 | Public services and engagement | Service personalisation (various) | No | No | Artificial Intelligence | G2C | x | x | x | x | x | https://www.hospitalmanagement.net/news/greek-government-sword-health-initiative/ | Learning | Machine learning | Generative AI | 10/12/2025 | |||||||||||||||||
| PSTW-1745 | Portugal Ministry of Justice – GPJ Digital Assistant | https://genesis.studio/gpj-a-implementacao-do-chatgpt-para-o-ministerio-da-justica-pela-genesis-studio/ | Citizens and businesses in Portugal often face difficulties understanding legal procedures due to complex language and fragmented information sources. The Ministry of Justice sought to improve access to justice by making procedural information clearer, more accessible, and easier to navigate. This use case involves the Ministry, citizens, companies, and legal professionals, with the objective of simplifying access to information about legal proceedings. The GPJ digital assistant is implemented as a conversational system trained on official justice content and written in plain language. It responds to user questions through natural dialogue, guiding them through procedures, requirements, and next steps. The system is integrated with Ministry information sources and designed to evolve as regulations change. The solution improves comprehension, reduces the need for in-person or phone enquiries, and supports more equal access to justice information. It enhances user experience by lowering language barriers, improves efficiency within the justice system, and delivers public value by making legal information more transparent and accessible. | National | Portugal | PT | Ministry of Justice | Central-Government | Public order and safety | Law courts | Implemented | 2.023 | Public services and engagement | Engagement management | No | Yes | Artificial Intelligence | G2C | x | x | x | x | x | x | https://www.publico.pt/2023/02/17/tecnologia/noticia/ministerio-justica-vai-usar-tecnologia-chatgpt-responder-cidadaos-2039270 | Learning | Machine learning | Generative AI | Natural language processing | 14/12/2025 | |||||||||||||||
| PSTW-2928 | AI-for-Søren: AI for work injuries | https://videncenter.kl.dk/viden-og-vaerktoejer/ai/kommunernes-ai-landkort | AI-for-Søren is an AI assistant that answers questions related to work-related and eye injuries. It communicates the municipality’s procedures for handling such cases and provides guidance on rights and responsibilities, while also linking to supplementary information from Danish state authorities, including the Danish Working Environment Authority and the National Board of Industrial Injuries, as well as other relevant professional sources. The assistant serves as a practical tool for reporting parties and injured employees, while also helping to streamline workflows for those responsible for managing occupational injury cases within the municipality. It is intended for use by managers, working environment representatives, employees who have experienced a work-related injury, and staff within HR, the MED organisation, Gentofte Working Environment, and the municipality’s occupational injury function. The purpose of the project is to help employees and managers more easily access accurate guidance and ensure that work-related and eye injuries are handled correctly and in compliance with applicable rules and procedures. | Local | Denmark | DK | Gentofte Municipality | Local government | Social protection | Sickness and disability. | Implemented | 2.025 | Internal management | Internal support processes | No | No | Artificial Intelligence | G2C | x | x | x | x | x | https://videncenter.kl.dk/viden-og-vaerktoejer/ai/kommunernes-ai-landkort | Learning | Machine learning | Natural language processing | AI assistant | 19/12/2025 | ||||||||||||||||
| PSTW-2687 | Warwickshire County Council: “Access to Food” – exploring LLMs for citizen needs | https://www.local.gov.uk/case-studies/warwickshire-county-council-access-food-exploring-llms-citizen-needs | Warwickshire County Council’s “Access to Food” project explores the use of open-source large language models (LLMs) to better understand how citizens—especially in deprived areas—access healthy and affordable food options. By deploying the Llama 2 model in-house, the council maintained full data sovereignty while experimenting with AI-driven classification of local businesses. Although traditional data science methods outperformed the LLM in accuracy, the project revealed promising potential for automating manual tasks and saving staff time. It also highlighted key challenges around hardware, security, and governance, offering valuable insights for responsible AI adoption in local government. | Local | United Kingdom | UK | Warwickshire County Council | Local Government | General public services | General public services n.e.c. | Implemented | 2.025 | Analysis, monitoring and regulatory research | Prediction and planning | No | No | Artificial Intelligence | G2C | x | x | x | x | x | https://www.local.gov.uk/our-support/cyber-digital-and-technology/artificial-intelligence-hub/artificial-intelligence-case | Learning | Machine learning | Generative AI | chatbot | 28/08/2025 | ||||||||||||||||
| PSTW-2688 | Wigan Council: QuickAction in adult social care | https://www.local.gov.uk/case-studies/wigan-council-quickaction-adult-social-care | Wigan Council’s QuickAction initiative is a transformative AI-powered project developed in partnership with Agilisys Transform to enhance adult social care services. The suite of tools automates key administrative tasks—such as needs assessments, meeting minutes, case audits, and survey analysis—freeing up staff time for direct resident support. By involving social workers in the design process, the tools are tailored to real-world needs and have already saved over 100 staff days. The project also includes an AI chatbot and extends benefits to housing services, while robust governance ensures ethical and secure AI use. | Local | United Kingdom | UK | Wigan Council | Local Government | Social protection | Old age. | Implemented | 2.025 | Internal management | Internal support processes | No | No | Artificial Intelligence | G2C | x | x | x | x | x | https://www.local.gov.uk/our-support/cyber-digital-and-technology/artificial-intelligence-hub/artificial-intelligence-case | Learning | Machine learning | Generative AI | chatbot | 28/08/2025 | ||||||||||||||||
| PSTW-2767 | Mantas – chatbot created by Lithuanian Post together with Tilde | https://tilde.ai/case-study/meet-mantas-chatbot-created-by-lithuanian-post-together-with-tilde/ | Mantas is an intelligent AI‑powered chatbot developed for Lithuanian Post in collaboration with the language technology company Tilde. Launched in April 2023, Mantas was designed to handle a substantial share of customer enquiries, especially around sending and receiving parcels, as part of a broader effort to improve online customer service. The chatbot uses natural language understanding to interpret and respond to freely formulated questions — even with stylistic or grammatical variations — helping to reduce the workload on human consultants by handling hundreds of queries per day (around 300–500) and aiming to take over about 50% of written customer requests. The implementation was reported as straightforward, with Tilde supporting both the technical setup and content adaptation, and the project continues to be developed to keep responses accurate as services and user needs evolve. | National | Lithuania | LT | Lithuanian Post | Central-Government | General public services | General public services n.e.c. | Implemented | 2.023 | Internal management | Internal support processes | No | No | Artificial Intelligence | G2C | x | x | x | x | x | https://tilde.ai/ | Learning | Machine learning | Natural language processing | chatbot | 12/12/2025 | ||||||||||||||||
| PSTW-2774 | Transforming Public Services with AI in the Var Department | https://usecases.ekipa.ai/government-public-sector/var-department-in-southern-france-ai-efficiency | The Var Department in southern France has implemented AI-driven tools to enhance public service efficiency and improve citizen engagement. The project uses chatbots, automated transcription, and AI-assisted workflows to streamline administrative processes, manage citizen requests more quickly, and reduce manual workload for staff. By leveraging AI, the department aims to deliver faster, more accurate, and more responsive public services, while freeing up human resources for complex decision-making and improving overall transparency and accountability in local governance. | Regional | France | FR | Var Department in Southern France | Regional Government | General public services | General public services n.e.c. | Implemented | 2.025 | Public services and engagement | Service integration (various) | No | No | Artificial Intelligence | G2C | x | x | x | x | x | https://cloud.google.com/transform/101-real-world-generative-ai-use-cases-from-industry-leaders | Learning | Machine learning | Generative AI | chatbot | 05/12/2025 | ||||||||||||||||
| PSTW-2883 | ADEM Interact - AI conversational platform for the Employment Agency | https://mindigital.gouvernement.lu/en/dossiers/2024/tech-in-gov/projets-tech.html | ADEM Interact is an AI conversational platform that will assist state agents of the Employment Agency ADEM who receive messages from job seekers, by formulating personalised responses. This is expected to apply to emails and enquiries received via a new Chatbot service integrated into the ADEM website. | National | Luxembourg | LU | Employment Agency ADEM | Central-Government | Economic affairs | General economic, commercial and labour affair | Implemented | 2.025 | Internal management | Internal support processes | No | No | Artificial Intelligence | G2B | x | x | x | x | x | https://mindigital.gouvernement.lu/en/dossiers/2024/tech-in-gov/projets-tech.html | Learning | Machine learning | chatbot | 03/12/2025 | |||||||||||||||||
| PSTW-2902 | AI-powered virtual assistant for payments | https://inno3.it/2025/02/20/pagopa-servizi-di-assistenza-cittadini-migliori-con-lai/ | The PagoPA AI support project is an initiative launched in February 2025 by PagoPA S.p.A., the Italian public company behind the national digital payment platform pagoPA and related citizen services such as the IO app. As part of this effort, PagoPA partnered with Spitch, a leader in conversational AI, to develop an AI-powered virtual assistant designed to improve how citizens receive assistance about the status of payments made through the pagoPA system. The project connects PagoPA’s multiple information sources with Spitch’s orchestration layer to power an omnichannel experience that integrates machine learning modules, natural language understanding systems and large language models, delivering real-time, contextual responses without users needing to wait for a human operator. The solution operates 24/7, scales efficiently during peak times, respects privacy and lays the groundwork for future enhancements like chatbot integration across web and mobile channels. | National | Italy | IT | PagoPA | Central-Government | General public services | General public services n.e.c. | In development | 2.025 | Public services and engagement | Service integration (various) | No | No | Artificial Intelligence | G2C | x | x | x | x | x | https://inno3.it/2025/02/20/pagopa-servizi-di-assistenza-cittadini-migliori-con-lai/ | Learning | Machine learning | Natural language processing | chatbot | 11/12/2025 | ||||||||||||||||
| PSTW-2669 | Decidim - digital and democratic platform for citizen participation | https://www.decidim.barcelona/ | Decidim.Barcelona is an open-source digital platform developed by Barcelona City Council to foster inclusive citizen participation in municipal decision-making. It enables residents to engage in debates, submit proposals, and vote on various initiatives, thereby influencing the city's development. The platform integrates both digital and physical participation methods, ensuring accessibility and transparency in governance processes. Built on open-source software, Decidim.Barcelona allows for continuous improvement and adaptation, promoting democratic engagement and civic empowerment. | Local | Spain | ES | Ajuntament de Barcelona | Local Government | General public services | General public services n.e.c. | Implemented | 2.016 | Public services and engagement | Engagement management | No | No | Artificial Intelligence | G2C | x | x | x | x | x | https://ajuntament.barcelona.cat/digital/en/technology-accessible-everyone/accessible-and-participatory/accessible-and-participatory-5 | Services | 28/08/2025 | |||||||||||||||||||
| PSTW-2684 | St Helens Borough Council – augmenting TEC with AI | https://www.local.gov.uk/case-studies/st-helens-borough-council-augmenting-tec-ai | In 2024, St Helens Council launched its AI-driven Technology Enabled Care (TEC) Hub, a key component of its 2024-2027 Adult Social Care strategy and its "reablement – home first approach," to transform its services. This initiative is focused on shifting from reactive to proactive care, empowering individuals post-hospital stay to confidently resume everyday activities. The council's team utilised Microsoft Copilot Studio to develop in-house AI tools, including predictive analytics. AI-powered predictive analytics were used to match individuals with optimal TEC solutions and develop cost models for care planning. This integration aims to optimise TEC's impact and embed it within the council's next-generation digital strategy. | Local | United Kingdom | UK | St Helens Borough Council | Local Government | Social protection | Outpatient services. | In development | 2.024 | Analysis, monitoring and regulatory research | Prediction and planning | No | No | Artificial Intelligence | G2G | x | x | x | x | x | https://www.local.gov.uk/our-support/cyber-digital-and-technology/artificial-intelligence-hub/artificial-intelligence-case | Learning | Machine learning | 28/08/2025 | ||||||||||||||||||
| PSTW-2693 | Strategic spatial planning: inclusive engagement and AI in strategic spatial planning | https://www.thefuturefox.com/oxcam-arc | In 2020 and 2021, the Ministry of Housing, Communities & Local Government (MHCLG) commissioned The Future Fox to lead a comprehensive digital consultation across the Oxford-Cambridge Arc—a region encompassing five counties and 3.3 million residents. The initiative aimed to inform the development of a Spatial Framework guiding the area’s long-term growth and sustainability. Utilising The Future Fox’s PlaceBuilder platform, the consultation employed a two-phase approach: engaging younger audiences through visually-driven polls and providing a formal consultation site for broader participation. Targeted social media campaigns ensured high engagement, while AI analysis processed over 66,000 responses, creating spatial heatmaps to visualise community sentiment on key themes such as environment, economy, connectivity, and place-making. Notably, the consultation achieved a 28% conversion rate, significantly outperforming traditional survey methods, and successfully engaged underrepresented groups, including individuals under 35 and ethnic minorities. This project exemplifies how digital engagement and AI can facilitate inclusive and data-rich strategic planning. | National | United Kingdom | UK | Ministry of Housing, Communities & Local Government (MHCLG) | Central-Government | General public services | General public services n.e.c. | Implemented | 2.020 | Analysis, monitoring and regulatory research | Prediction and planning | No | No | Artificial Intelligence | G2C | x | x | x | x | x | https://www.thefuturefox.com/ | Planning | Planning and Scheduling | 29/08/2025 | ||||||||||||||||||
| PSTW-2695 | AI traffic system in Pittsburgh | https://www.smartcitiesdive.com/news/this-ai-traffic-system-in-pittsburgh-has-reduced-travel-time-by-25/447494/ | In Pittsburgh, traffic congestion caused by the city’s unique road network of hills, bridges, and irregular layouts led to significant delays for drivers. To address this, researchers at Carnegie Mellon University developed SURTRAC, an AI-based adaptive traffic signal system. Unlike traditional pre-programmed lights, SURTRAC uses sensors and cameras to detect traffic in real time, predicting flows and adjusting signal timings dynamically. The system also enables intersections to communicate with one another, creating a coordinated but decentralised network. First deployed in 2012 across nine intersections in East Liberty, the system quickly proved effective, reducing travel times by about 25%, idling by over 40%, braking by 30%, and emissions by roughly 21%. Its success led to expansion across dozens of intersections, with federal support for further deployment. Beyond vehicle efficiency, adjustments were made to improve pedestrian wait times, and experiments are underway to integrate accessibility features through mobile apps. The project eventually spun off into a company, Rapid Flow Technologies, which has begun deploying SURTRAC in other U.S. and Canadian cities. The Pittsburgh case demonstrates how AI-driven traffic management can significantly improve mobility, reduce environmental impact, and serve as a scalable model for smarter urban infrastructure. | Local | United Kingdom | UK | Carnegie Mellon University | Academic-Research | General public services | General public services n.e.c. | Implemented | 2.012 | Internal management | Internal support processes | No | No | Artificial Intelligence | G2C | x | x | x | x | x | https://www.smartcitiesdive.com/news/this-ai-traffic-system-in-pittsburgh-has-reduced-travel-time-by-25/447494/ | Perception | Computer vision | 02/09/2025 | ||||||||||||||||||
| PSTW-2780 | agrifoodTEF - innovative AI and robotics applications for the Austrian agricultural and food industry | https://www.digitalaustria.gv.at/themen/kuenstliche-intelligenz/ki-monitor/agrifood-tef.html | The AgriFood TEF (Testing and Experimentation Facility) by Digital Austria is a national initiative designed to support the application of artificial intelligence in the agriculture and food sectors. The platform provides AI infrastructure, expert guidance, and testing environments to help farmers, agritech start-ups, researchers, and public institutions experiment with AI technologies responsibly. AgriFood TEF enables users to develop, test, and implement AI solutions for precision agriculture, supply chain optimisation, food quality monitoring, and sustainability practices. It also supports the integration of AI into existing workflows, promoting innovation, efficiency, and compliance with European AI regulations. By providing a practical, hands-on environment, the initiative strengthens Austria’s digital and AI capabilities in agri-food, while fostering collaboration between industry, research, and government stakeholders. | National | Austria | AT | Digital Austria | Central-Government | Economic Affairs | Agriculture, forestry, fishing and hunting | In development | 2.023 | Internal management | Internal support processes | No | No | Artificial Intelligence | G2B | x | x | x | x | x | https://www.digitalaustria.gv.at/themen/kuenstliche-intelligenz/ki-monitor/agrifood-tef.html | Services | AI services | 15/12/2025 | ||||||||||||||||||
| PSTW-2795 | AI helps diagnose tuberculosis and other lung pathologies | https://www.phc.org.ua/news/shtuchniy-intelekt-dopomagae-diagnostuvati-tuberkuloz-ta-inshi-patologii-u-legenyakh-rezultati | The project uses artificial intelligence (AI) to assist in diagnosing Tuberculosis (TB) and other lung diseases by analysing chest X‑rays. Several AI‑powered systems have been installed across Ukrainian phthisiopulmonology clinics and mobile X‑ray units, enabling faster, more accurate and more sensitive detection of lung pathologies — even subtle changes that might be missed by the human eye. In 2024 alone, the AI systems analysed thousands of images with high accuracy (around 92.5%), significantly easing the burden on radiologists, accelerating diagnosis and allowing earlier initiation of treatment. The technology also supports outreach efforts, as mobile teams can scan and screen patients in remote or underserved communities, improving access to crucial diagnostics. | National | Ukraine | UA | Public Health Center of the Ministry of Health of Ukraine (PHC) | Central-Government | Health | Hospital services. | Implemented | 2.025 | Public services and engagement | Service integration (various) | No | No | Artificial Intelligence | G2C | x | x | x | x | x | https://oecd.ai/en/dashboards/policy-initiatives/ai-based-computer-aided-detection-software-product | Learning | Machine learning | 09/12/2025 | ||||||||||||||||||
| PSTW-2797 | New cross-government, AI-powered data management asset | https://defensescoop.com/2025/04/25/estonia-ai-powered-data-management-tool-ambassador-kristjan-prikk/ | The Estonian government is preparing to launch a new cross‑government, AI‑enabled data‑management platform designed to make public‑sector data from different ministries and agencies searchable and accessible to citizens through a single unified interface. The tool aims to break down silos, allowing individuals to retrieve information and access services regardless of which particular agency holds the data — health, social services, veterans affairs, etc. The first components of the system are expected to become operational this year, with further rollout and improvements to follow. The initiative reflects Estonia’s long‑standing commitment to digital governance and seeks to improve transparency, efficiency, and citizen access to government information. | National | Estonia | EE | Government of Estonia | Central-Government | General public services | General public services n.e.c. | In development | 2.025 | Public services and engagement | Service integration (various) | No | No | Artificial Intelligence | G2C | x | x | x | x | x | https://defensescoop.com/2025/04/25/estonia-ai-powered-data-management-tool-ambassador-kristjan-prikk/ | Learning | Machine learning | 09/12/2025 | ||||||||||||||||||
| PSTW-2869 | Microsoft Copilot in Cyprus' Public Administration | https://knews.kathimerini.com.cy/en/news/ai-enters-the-bureaucracy-as-microsoft-co-pilot-rolls-out-in-public-administration | The Government of Cyprus has begun introducing Microsoft 365 Copilot across the public administration as part of its wider digital modernisation efforts. In the initial phase, 350 civil servants will receive licences and dedicated training to ensure the tool is used safely and effectively. Copilot is intended to support officials by automating routine and time-consuming tasks such as drafting documents, analysing large volumes of data, and managing administrative processes. By reducing manual workload, the initiative aims to improve efficiency and allow staff to focus more on providing high-value services to citizens. This rollout forms part of a broader €5 million “AI in Government” programme designed to expand the use of artificial intelligence within the public sector, including applications related to the labour market, climate challenges, and other areas of state activity. | National | Cyprus | CY | Ministry of Research, Innovation and Digital Policy | Central-Government | General public services | General public services n.e.c. | In development | 2.025 | Internal management | Internatl support processes | No | No | Artificial Intelligence | G2B | x | x | x | x | x | https://knews.kathimerini.com.cy/en/news/ai-enters-the-bureaucracy-as-microsoft-co-pilot-rolls-out-in-public-administration | Learning | Machine learning | Generative AI | 10/12/2025 | |||||||||||||||||
| PSTW-2884 | ADEM Profiling | https://mindigital.gouvernement.lu/en/dossiers/2024/tech-in-gov/projets-tech.html | ADEM Profiling will allow through the analysis of existing data at ADEM to develop a support model for their agents to assess which jobseekers need which measures and level of support to access employment. This diagnostic is possible by taking into consideration the characteristics and professional profile of the jobseeker. | National | Luxembourg | LU | Employment Agency ADEM | Central-Government | Economic affairs | General economic, commercial and labour affair | Implemented | 2.025 | Internal management | Internal support processes | No | No | Artificial Intelligence | G2B | x | x | x | x | x | https://mindigital.gouvernement.lu/en/dossiers/2024/tech-in-gov/projets-tech.html | Learning | Machine learning | 09/12/2025 | ||||||||||||||||||
| PSTW-2922 | OS2ai - Open-source AI solution in Danish municipalities | https://videncenter.kl.dk/viden-og-vaerktoejer/ai/kommunernes-ai-landkort | Randers Municipality participates in OS2ai, an open-source AI solution developed collaboratively by Aarhus Municipality and several other Danish municipalities. The solution makes it easy to integrate artificial intelligence into municipal workflows and automate tasks across different areas of responsibility. OS2ai is flexible, scalable, and can be used for both daily tasks and specialized AI applications. The platform is built on the foundation established by Aarhus Municipality and is further developed within the OS2 community. More than 80 municipalities and other public sector actors are already participating. | Local | Denmark | DK | Randers Municipality | Local government | General public services | General public services n.e.c. | Implemented | 2.025 | Internal management | Internal support processes | No | No | Artificial Intelligence | G2C | x | x | x | x | x | https://videncenter.kl.dk/viden-og-vaerktoejer/ai/kommunernes-ai-landkort | Services | AI services | 19/12/2025 | ||||||||||||||||||
| PSTW-2678 | Kent County Council: Using predictive analytics to prevent homelessness in Maidstone and Kent | https://socitm.net/resource-hub/impact-cases/using-predictive-analytics-to-prevent-homelessness-maidstone-borough-council-and-kent-county-council/ | Kent County Council leveraged predictive analytics to identify individuals and households at risk of homelessness in Maidstone and across Kent. By analysing data from multiple sources, the council can proactively intervene, provide targeted support, and allocate resources more effectively, aiming to reduce homelessness and improve community well-being. | Local | United Kingdom | UK | Kent County Council | Local Government | Social protection | Social protection n.e.c. | Implemented | 2.024 | Analysis, monitoring and regulatory research | Prediction and planning | No | No | Artificial Intelligence | G2C | x | x | x | x | https://www.local.gov.uk/our-support/cyber-digital-and-technology/artificial-intelligence-hub/artificial-intelligence-case | Planning | Planning and Scheduling | 09/02/2026 | |||||||||||||||||||
| PSTW-2691 | ConsultAI: Bath and North East Somerset Council parking charge proposals | https://www.thefuturefox.com/parking-consultation | In 2024, Bath and North East Somerset Council ran a consultation on proposed parking charge changes, receiving over 4,300 responses and more than 18,000 free-text comments. Analysing such a large volume of qualitative feedback would normally take weeks of manual effort, slowing down decision-making and limiting transparency. To address this, the Council partnered with The Future Fox, who deployed their AI-powered platform ConsultAI. Within just three days, the system processed all responses and produced editable reports in Excel and Word formats, complete with thematic summaries, analysis of longer comments, and an overarching synthesis of the issues raised. This saved the council around six weeks of work while also improving the clarity, consistency, and accountability of reporting, enabling faster and more informed decisions. | Local | United Kingdom | UK | Bath and North East Somerset Council | Local Government | General public services | Executive and legislative organs, financial and fiscal affairs, external affairs. | Implemented | 2.024 | Analysis, monitoring and regulatory research | Prediction and planning | No | No | Artificial Intelligence | G2B | x | x | x | x | https://www.thefuturefox.com/parking-consultation | Learning | Machine learning | Generative AI | Natural language processing | 29/08/2025 | |||||||||||||||||
| PSTW-2765 | Dìgital Twin in the City of Vilnius | https://www.esri.com/about/newsroom/blog/vilnius-uses-drones-ai-to-monitor-city-services | Vilnius has deployed an advanced digital twin platform supported by AI, GIS and drone data to optimise city services and planning. The system uses drone imagery and AI algorithms to monitor infrastructure conditions, detect full waste bins, assess street cleanliness after weather events, and evaluate pavement and building conditions. The digital twin integrates multiple data sources, enabling planners to visualise and prioritise municipal services in real time, such as clearing snow quickly or identifying areas in need of maintenance based on AI‑derived maps. It also incorporates anonymised movement data to help with transport planning and uses multi‑layered 3D city models to support long‑term urban development and participatory engagement with residents. Across these functions, Vilnius’s approach illustrates how geospatial intelligence and real‑time digital modelling can improve operational efficiency and transparency in urban governance. | Local | Lithuania | LT | Vilnius City Municipality | Local Government | General public services | General public services n.e.c. | Implemented | 2.024 | Internal management | Internal support processes | No | No | Artificial Intelligence | G2C | x | x | x | x | https://iclei-europe.org/news?Valencia,_Vilnius,_and_Nottingham_show_how_integrated_geospatial_systems_can_be_used_to_build_AI-empowered_cities_&newsID=5WoawfPS | Reasoning | 12/12/2025 | ||||||||||||||||||||
| PSTW-2794 | Brainscan Telemedicine - AI for brain diagnostics | https://rubryka.com/en/2023/09/09/odesa-pershoyu-doluchyla-shtuchnyj-intelekt-dlya-diagnostyky-golovnogo-mozku-yak-pratsyuye-tse-rishennya/ | In Odesa, Ukraine, authorities have launched a pilot telemedicine project called BrainScan that uses artificial intelligence to dramatically speed up the diagnosis of brain diseases and injuries — a critical factor when every minute can save a life. The system, developed under Ukraine’s national telemedicine strategy and supported by USAID, uses a neural network to automatically analyse CT scans of the brain and detect pathological changes. Within about five minutes after scanning, the AI’s results allow doctors to make faster, more accurate treatment decisions, helping reduce medical errors and giving clinicians a valuable “second opinion.” Following its initial success in Odesa, this AI diagnostic approach has also been introduced in frontline Kramatorsk in Donetsk region. | Local | Ukraine | UA | Government of Odesa | Local Government | Health | Health n.e.c. | Pilot | 2.023 | Internal management | Internal support processes | No | No | Artificial Intelligence | G2C | x | x | x | x | https://rubryka.com/en/2023/09/09/odesa-pershoyu-doluchyla-shtuchnyj-intelekt-dlya-diagnostyky-golovnogo-mozku-yak-pratsyuye-tse-rishennya/ | Learning | Machine learning | 16/12/2025 | |||||||||||||||||||
| PSTW-2814 | Valencia shows how integrated geospatial systems can be used to build AI-empowered cities | https://www.lavanguardia.com/sociedad/20251015/11160936/csic-destaca-papel-drones-gestion-emergencias-dana-2024-valencia-agenciaslv20251015.html?utm_source=chatgpt.com | Valencia used geospatial technologies, drones and AI‑driven spatial analysis to support emergency response during and after the October 2024 DANA floods, one of the most severe flood events in recent local history. High‑resolution drone imagery and sensor data were rapidly analysed to locate debris, abandoned vehicles and areas heavily affected by flooding, which helped emergency teams prioritise their response and decision‑making more efficiently. The integration of these technologies also enabled the creation of detailed 3D models to assess infrastructure damage and supported hydrological simulations to better understand flood dynamics. In the wake of the disaster, ongoing initiatives in the region are exploring how AI, digital twins and predictive modelling can improve early warning systems, refine flood‑risk maps and support climate adaptation efforts for future extreme weather events. | Local | Spain | ES | City of Valencia | Local government | Public order and safety | Public order and safety n.e.c. | Implemented | 2.024 | Analysis, monitoring and regulatory research | Prediction and planning | No | No | Artificial Intelligence | G2C | x | x | x | x | https://iclei-europe.org/news?Valencia,_Vilnius,_and_Nottingham_show_how_integrated_geospatial_systems_can_be_used_to_build_AI-empowered_cities_&newsID=5WoawfPS | Perception | Computer vision | 15/12/2025 | |||||||||||||||||||
| PSTW-2705 | AI4Gov - Trusted AI for Transparent Public Governance fostering Democratic Values (Spain) | https://ai4gov-project.eu/home/use-cases/ | Diputación Provincial de Badajoz (DPB) is a local government body coordinating municipalities to promote economic and social development across the province. As part of the AI4Gov project, the DPB pilot focuses on sustainable water cycle management, covering both drinking and wastewater. The council oversees 63 drinking water treatment plants serving 137,910 residents, along with wastewater treatment. The pilot aims to develop intelligent tools that leverage existing water management systems and data to identify inefficiencies—such as leaks, water losses, or off-hour energy use—enabling technicians to implement non-obvious, day-to-day solutions. The insights will also support policymakers in infrastructure planning, budget allocation, and optimising water services by training AI models to detect system malfunctions. | Local | Spain | ES | Diputación Provincial de Badajoz (DPB) is a local government body coordinating municipalities to promote economic and social development across the province. As part of the AI4Gov project, the DPB pilot focuses on sustainable water cycle management, covering both drinking and wastewater. The council oversees 63 drinking water treatment plants serving 137,910 residents, along with wastewater treatment. The pilot aims to develop intelligent tools that leverage existing water management systems and data to identify inefficiencies—such as leaks, water losses, or off-hour energy use—enabling technicians to implement non-obvious, day-to-day solutions. The insights will also support policymakers in infrastructure planning, budget allocation, and optimising water services by training AI models to detect system malfunctions. | Local Government | Environmental protection | Waste water management. | Pilot | 2.023 | 2025 | Internal management | Internal support processes | No | No | Artificial Intelligence | G2B | x | x | x | x | https://ai4gov-project.eu/ | Learning | Machine learning | 02/09/2025 | ||||||||||||||||||
| PSTW-2707 | AI4Gov - Trusted AI for Transparent Public Governance fostering Democratic Values (Slovenia - Pilot2) | https://ai4gov-project.eu/home/use-cases/ | The Jožef Stefan Institute (JSI), in partnership with UNESCO’s International Research Centre in Artificial Intelligence (IRCAI), focuses on advancing AI for societal benefit. Within AI4Gov, JSI is piloting three initiatives. The second pilot, the JSI SDG Observatory, is a web-based toolkit that gathers and visualises indicators to monitor progress toward the Sustainable Development Goals, providing policymakers and researchers with actionable insights. | Local | Slovenia | SI | Jožef Stefan Institute (JSI) | Academic-Research | Environmental protection | Environmental protection n.e.c. | Pilot | 2.023 | 2025 | Analysis, monitoring and regulatory research | Prediction and planning | No | No | Artificial Intelligence | G2B | x | x | x | x | https://ai4gov-project.eu/ | Learning | Machine learning | 02/09/2025 | ||||||||||||||||||
| PSTW-2930 | A Sovereign AI Model: National LLM to Enter Beta in 2026 | https://digitalstate.gov.ua/news/govtech/ukraine-moves-toward-a-sovereign-ai-model-national-llm-to-enter-beta-in-2026 | Ukraine is developing its own sovereign large language model (LLM)—a national artificial intelligence system tailored to the Ukrainian language, culture and public-sector needs. The project has moved from concept to technical planning and is being built in partnership with Kyivstar, with the first beta version due in spring 2026. It uses Google’s open Gemma models as a base, which are being adapted and trained on extensive Ukrainian-language datasets drawn from government, academia, media and other sources. An independent expert panel is shaping quality, safety and linguistic benchmarks, while a legal framework for data use and intellectual-property compliance is under development. Once tested, the model will be made available to public institutions, researchers and developers, and is intended to bolster Ukraine’s digital sovereignty and reduce reliance on foreign AI technologies. | National | Ukraine | UA | Ministry of Digital Transformation | Central-Government | General public services | General public services n.e.c. | In development | 2.026 | Internal management | Internal support processes | No | Yes | Artificial Intelligence | G2C | x | x | x | x | https://digitalstate.gov.ua/ | Learning | Machine learning | Generative AI | 12/01/2026 | ||||||||||||||||||
| PSTW-2680 | Northumberland County Council- FloodAI, using AI to detect flash floods | https://www.local.gov.uk/case-studies/northumberland-county-council-floodai-using-ai-detect-flash-floods | Northumberland County Council is undertaking a pilot project, 'FloodAI', an AI-driven system designed to monitor and detect flash floods in real-time. This project is funded by Defra as part of the £200 million Flood and Coastal Innovation Programmes which is managed by the Environment Agency. The programmes will drive innovation in flood and coastal resilience and adaptation to a changing climate. By analysing environmental data, the system provides early warnings, enabling timely responses to mitigate flood risks and enhance public safety. | Local | United Kingdom | UK | Northumberland County Council | Local Government | Public order and safety | Public order and safety n.e.c. | Pilot | 2.025 | Analysis, monitoring and regulatory research | Prediction and planning | No | No | Artificial Intelligence | G2B | x | x | x | https://www.local.gov.uk/our-support/cyber-digital-and-technology/artificial-intelligence-hub/artificial-intelligence-case | Planning | Planning and Scheduling | 28/08/2025 | ||||||||||||||||||||
| PSTW-2711 | Machine Learning towards a greener grid | https://www.turing.ac.uk/about-us/impact/towards-greener-grid | The “Towards a Greener Grid” project highlights how the Turing Institute collaborated with the National Grid Electricity System Operator to develop advanced data-driven forecasting models for renewable energy, particularly solar and wind power. By applying machine-learning and statistical techniques, the team created a solar-forecasting system that improved the accuracy of day-ahead solar energy predictions by around 33%. These improved forecasts help the grid operator balance electricity supply and demand more effectively, reduce reliance on backup generation, lower costs for consumers, and support the integration of a higher share of renewable energy into the UK grid. | National | United Kingdom | UK | Turing Institute | Academic-Research | Economic affairs | Fuel and energy | Implemented | 2.019 | Analysis, monitoring and regulatory research | Prediction and planning | No | No | Artificial Intelligence | G2B | x | x | x | https://lgcomms.org.uk/wp-content/uploads/2023/02/Future-of-Channels-WP.pdf | Learning | Machine learning | Planning and Scheduling | 27/11/2025 | |||||||||||||||||||
| PSTW-2881 | Outlier detection - a system for detecting aberrant data | https://mindigital.gouvernement.lu/en/dossiers/2024/tech-in-gov/projets-tech.html | The Ministry of Home Affairs aims to set up automated monitoring using a system for detecting aberrant data (outlier detection) in the financial data of the municipal sector. | National | Luxembourg | LU | Ministry of Home Affairs | Central-Government | General public services | Executive and legislative organs, financial and fiscal affairs, external affairs. | Implemented | 2.025 | Internal management | Internal support processes | No | No | Artificial Intelligence | G2B | x | x | x | https://mindigital.gouvernement.lu/en/dossiers/2024/tech-in-gov/projets-tech.html | Integration and Interaction | Robotics and Automation | 03/12/2025 | ||||||||||||||||||||
| PSTW-2882 | Machine learning for statistics | https://mindigital.gouvernement.lu/en/dossiers/2024/tech-in-gov/projets-tech.html | The National Institute of statistics and economic studies (STATEC) will implement a data science and machine learning program to enable the production of statistics on the mobile telephone database. | National | Luxembourg | LU | National Institute of statistics and economic studies (STATEC) | Central-Government | Economic affairs | Economic affairs n.e.c | Implemented | 2.025 | Internal management | Internal support processes | No | No | Artificial Intelligence | G2B | x | x | x | https://mindigital.gouvernement.lu/en/dossiers/2024/tech-in-gov/projets-tech.html | Learning | Machine learning | 03/12/2025 | ||||||||||||||||||||
| PSTW-2879 | AI in Rectruitment Procedures | https://mindigital.gouvernement.lu/en/dossiers/2024/tech-in-gov/projets-tech.html | The State Centre for Human Resources and Organisation Management intends to improve recruitment procedures by using artificial intelligence in order to assist their agents in checking the conditions of admissibility of applications and registrations for the general aptitude test for the Luxembourg civil service. | National | Luxembourg | LU | State Centre for Human Resources and Organisation Management | Central-Government | Economic affairs | General economic, commercial and labour affair | Implemented | 2.025 | Internal management | Internal support processes | No | No | Artificial Intelligence | G2B | x | https://mindigital.gouvernement.lu/en/dossiers/2024/tech-in-gov/projets-tech.html | Learning | Machine learning | 03/12/2025 | ||||||||||||||||||||||
| PSTW-2777 | mAIgov - AI-powered digital assistant of Greece's unified public administration portal | https://www.gov.gr/ | mAigov is an AI-powered digital assistant integrated into Greece's unified public administration portal, gov.gr. Launched in December 2023 by the Ministry of Digital Governance, mAigov aims to streamline citizens' interactions with public services by simplifying access to information and procedures. | National | Greece | EL | Ministry of Digital Governance | Central-Government | General public services | General services | Implemented | 2.023 | Public services and engagement | Service personalisation (various) | No | No | Artificial Intelligence | G2C | x | x | x | x | x | https://www.gov.gr/en/info/politiki-xrisis-maigov | Learning | Machine learning | Generative AI | chatbot | 05/12/2025 | ||||||||||||||||
| PSTW-2778 | Use of AI in Business Intelligence System - Skrinja | https://oecd.ai/en/dashboards/policy-initiatives/use-of-ai-in-business-intelligence-system-skrinja | The government of Slovenia has launched Skrinja, a central data‑warehouse and business‑intelligence (BI) platform for public administration, designed to support data-driven decision making and improve transparency, efficiency, and governance. Skrinja collects data from multiple public-sector sources, pseudonymises personal data to comply with privacy rules, and enables agencies to create dashboards, visualisations, and automated reports on public-sector information. The platform allows authorities to replace manual Excel-based repo rting with real-time analytics, “what-if” scenario simulations, predictive analytics, and more accurate, consistent reporting from a single “source of truth.” AI is used within Skrinja to enhance analytics, providing predictive insights, anomaly detection, and automated scenario simulations, helping authorities forecast trends, detect patterns, and generate actionable insights from large datasets. This allows for more accurate, consistent, and real-time reporting from a single “source of truth.” | National | Slovenia | SI | Government of Slovenia | Central-Government | General public services | Executive and legislative organs, financial and fiscal affairs, external affairs. | Implemented | 2.025 | Analysis, monitoring and regulatory research | Prediction and planning | No | No | Artificial Intelligence | G2G | x | x | x | x | x | https://oecd.ai/en/dashboards/policy-initiatives | Learning | Machine learning | anomaly detection | 05/12/2025 | |||||||||||||||||
| PSTW-2868 | SNCF’s AI Maintenance Scheduler Reduces Train Downtime by 45% | https://digitaldefynd.com/IQ/ways-ai-is-used-in-france/ | France’s national rail operator SNCF struggled with unexpected mechanical failures in its TGV fleet, as traditional time-based maintenance often missed early risks while causing unnecessary servicing. This led to inefficiencies, delays, and higher costs. To improve reliability, SNCF deployed an AI-driven predictive maintenance platform that analyses onboard sensor data and external inputs such as weather conditions. Using Bayesian inference and LSTM forecasting models, the system predicts short-term failure risks, prioritizes interventions through visual dashboards, and automatically aligns maintenance tasks with technician schedules and parts availability. The initiative reduced maintenance-related downtime by 45%, added around 68,000 operational hours annually, and improved punctuality to 94% on major routes. Spare-part wastage fell by 19%, technician stress and overtime dropped by 30%, and operating costs were reduced by €28 million over three years. SNCF is expanding the solution to additional fleets and regional services, with plans to integrate smart-station IoT data, enable network-wide optimization, and test generative AI for simulating rare fault scenarios, while exploring international rollout across Europe. | National | France | FR | SNCF | Central-Government | Economic affairs | Transport | Implemented | 2.025 | Analysis, monitoring and regulatory research | Prediction and planning | No | No | Artificial Intelligence | G2G | x | x | x | x | x | https://digitaldefynd.com/IQ/ways-ai-is-used-in-france/ | Learning | Machine learning | 18/12/2025 | ||||||||||||||||||
| PSTW-2916 | Paris Hospitals Use AI for ICU Bed Allocation and Mortality Prediction | https://digitaldefynd.com/IQ/ways-ai-is-used-in-france/ | ICU coordination in Paris’s public hospitals struggled with outdated availability data, exposed during COVID surges. Hospitals implemented an AI system using federated learning, allowing predictive models without centralising sensitive data. LSTM networks forecast ICU occupancy from lab results, comorbidities, ventilator use, and environmental factors, while a triage module ranks patients by survival probability. Integration with ER software and ambulance dispatch enables coordinated patient transfers. The system cut ICU transfer times by 58%, tripled planning accuracy, and achieved 92% mortality prediction precision, supporting ethical decision-making and improving allocation of beds, staff, and ventilators. Families received clearer prognostic information. Expansion plans cover trauma, cardiology, and surgical recovery units across 40 hospitals, with anonymised model sharing under the EU Health Data Space, real-time equipment monitoring, automated billing, and clinical oversight to override AI when necessary. | Local | France | FR | Assistance Publique – Hôpitaux de Paris (AP-HP) | Local government | Health | Hospital services. | Implemented | 2.025 | Analysis, monitoring and regulatory research | Prediction and planning | No | No | Artificial Intelligence | G2G | x | x | x | x | x | https://digitaldefynd.com/IQ/ways-ai-is-used-in-france/ | Learning | Machine learning | 18/12/2025 | ||||||||||||||||||
| PSTW-2935 | AI solution in Roskilde Municipality helps create minutes of consultation responses | https://videncenter.kl.dk/media/fwehh4l0/inspirationskatalog-syv-eksempler-med-generativ-ai-i-den-offentlige-sektor.pdf | Roskilde Municipality uses generative AI to automatically create summaries of consultation responses from residents regarding planning decisions. When citizens submit feedback on municipal projects, employees manually had to summarize each response—a time-consuming and variable process. The AI solution uses Azure GPT to generate initial drafts of these summaries, which employees then review and refine to ensure accuracy. Testing shows the AI produces summaries of 75-80% quality initially, potentially saving up to one hour per consultation response. This allows staff to redirect time toward other citizen-facing tasks. | Local | Denmark | DK | Roskilde Municipality | Local government | General public services | General services | Implemented | 2.024 | Internal management | Internal support processes | No | No | Artificial Intelligence | G2G | x | x | x | x | x | https://videncenter.kl.dk/media/fwehh4l0/inspirationskatalog-syv-eksempler-med-generativ-ai-i-den-offentlige-sektor.pdf | Learning | Machine learning | Generative AI | 22/01/2026 | |||||||||||||||||
| PSTW-2936 | AI helps the Danish Digital Agency conduct analyses | https://videncenter.kl.dk/media/fwehh4l0/inspirationskatalog-syv-eksempler-med-generativ-ai-i-den-offentlige-sektor.pdf | Since 2021, large Danish companies must address data ethics in their annual reports. The Digital Agency needed to analyze thousands of reports to strengthen national data ethics guidance. The sheer volume—3,673 reports totaling approximately 88,000 pages from 2022-2023—made manual analysis impractical. The agency developed a generative AI solution using ChatGPT API with a custom prompt containing 30 classification categories. This enables systematic analysis of data ethics policies across entire company populations rather than just samples, allowing faster, more comprehensive insights for policy development. | National | Denmark | DK | Danish Digital Agency | Central-Government | General public services | General services | Implemented | 2.024 | Internal management | Internal support processes | No | No | Artificial Intelligence | G2G | x | x | x | x | x | https://videncenter.kl.dk/media/fwehh4l0/inspirationskatalog-syv-eksempler-med-generativ-ai-i-den-offentlige-sektor.pdf | Learning | Machine learning | Generative AI | 22/01/2026 | |||||||||||||||||
| PSTW-2937 | AI solution in ATP writes journal notes of conversations with citizens | https://videncenter.kl.dk/media/fwehh4l0/inspirationskatalog-syv-eksempler-med-generativ-ai-i-den-offentlige-sektor.pdf | ATP, Denmark's labor market fund, receives approximately 2.5 million citizen calls annually, each requiring documentation as journal notes. The automated journaling solution converts call recordings to text, then summarizes conversations using generative AI. Results show the system generates draft notes in 5 seconds, with employees spending under 2 minutes correcting them in 70% of cases. This automation frees employees from time-consuming documentation tasks while maintaining consistent, high-quality records of citizen interactions. | National | Denmark | DK | ATP Livslang Pension | Central-Government | General public services | General services | Implemented | 2.024 | Internal management | Internal support processes | No | No | Artificial Intelligence | G2G | x | x | x | x | x | https://videncenter.kl.dk/media/fwehh4l0/inspirationskatalog-syv-eksempler-med-generativ-ai-i-den-offentlige-sektor.pdf | Learning | Machine learning | Generative AI | 22/01/2026 | |||||||||||||||||
| PSTW-2746 | Diella - World's First Virtual Minister | https://www.politico.eu/article/albania-apppoints-worlds-first-virtual-minister-edi-rama-diella/ | The Albanian government, led by Prime Minister Edi Rama, has appointed Diella, an artificial intelligence system, as a full member of its cabinet, making it the world’s first AI-powered government minister. Diella has been given responsibility for overseeing public procurement, with the aim of making the tendering process fully transparent and eliminating corruption. Previously introduced as a digital assistant on Albania’s national e-government portal, Diella has already helped citizens with thousands of administrative tasks and documents. This appointment positions Albania at the forefront of digital governance by embedding AI directly into governmental decision-making, while also raising questions about accountability, oversight, and public trust in such innovative applications. | National | Albania | AL | Albanian government | Central-Government | General public services | General public services n.e.c. | Implemented | 2.025 | Internal management | Procurement management | No | No | Artificial Intelligence | G2G | x | x | x | x | x | x | https://www.politico.eu/article/albania-apppoints-worlds-first-virtual-minister-edi-rama-diella/ | Learning | Machine learning | Natural language processing | virtual assistant | 01/12/2025 | |||||||||||||||
| PSTW-2885 | Anomaly detection: machine learning to detect water leaks | https://mindigital.gouvernement.lu/en/dossiers/2024/tech-in-gov/projets-tech.html | The 'Anomaly detection' project is designed to enable the local authority association, DEA (Distribution d'Eau des Ardennes), to use machine learning to detect water leaks in the network and identify changes in a set of data with daily and seasonal differences. The aim of this project is to increase the monitoring capabilities of the DEA, who is responsible for producing and distributing water to 29 municipalities in Luxembourg. | National | Luxembourg | LU | DEA (Distribution d'Eau des Ardennes) | Local government | Environmental protection | Waste water management. | Implemented | 2.025 | Internal management | Internal support processes | No | No | Artificial Intelligence | G2G | x | x | x | x | https://mindigital.gouvernement.lu/en/dossiers/2024/tech-in-gov/projets-tech.html | Learning | Machine learning | anomaly detection | 09/12/2025 | ||||||||||||||||||
| PSTW-2864 | City of Częstochowa will become the first in Poland to begin using the Polish Large Language Model (PLLuM) | https://notesfrompoland.com/2025/08/11/city-becomes-first-to-use-polish-ai-model-to-support-local-administration/ | The city of Częstochowa in Poland has become the first municipality to deploy the national Polish language model PLLuM in local administration. Under a pilot programme in collaboration with the Ministry of Digital Affairs, the AI is being used to support city officials in handling routine administrative tasks more efficiently. This includes drafting official letters, summarising long or complex documents, analysing residents’ inquiries, and providing quick guidance for internal workflows. The implementation aims to reduce processing times, improve transparency in local administration, and free up staff to focus on higher-value tasks. By integrating PLLuM into everyday municipal operations, Częstochowa seeks to modernise local government services while exploring the practical benefits and limitations of generative AI in public administration. | Local | Poland | PL | Administration of Częstochowa | Local government | General public services | General public services n.e.c. | Pilot | 2.025 | Internal management | Internal support processes | No | No | Artificial Intelligence | G2G | x | x | x | x | https://notesfrompoland.com/2025/08/11/city-becomes-first-to-use-polish-ai-model-to-support-local-administration/ | Learning | Machine learning | Generative AI | chatbot | 10/12/2025 | |||||||||||||||||
| PSTW-2867 | Mon parquet assistant - My assistant prosecutor | https://beta.gouv.fr/startups/investigation-cour-d-appel-de-paris.html | Mon parquet assistant is a digital-justice solution, developed under the aegis of beta.gouv.fr and the Parquet général de Paris, aimed at speeding up the processing of criminal-case files in courts under the Cour d'appel de Paris. The tool helps magistrates manage, review and analyse judicial documents more efficiently — by uploading full case files (digital or scanned), automatically detecting the types of offenses, enabling quick searches for relevant information, highlighting key passages, and supporting both a rapid overview and a deeper review of records. The goal is to reduce repetitive, low-value tasks and shorten procedural delays, especially in high-volume or “mass-litigation” situations. The service is still under development. | National | France | FR | Ministry of Justice, Paris Public Prosecutor's Office | Central-Government | Public order and safety | Law courts | In development | 2.025 | Internal management | Internal management processes | No | No | Artificial Intelligence | G2G | x | x | x | x | https://ai.gov.uk/blogs/smarter-government-powered-by-ai-what-we-learned-in-france/ | Learning | Machine learning | Generative AI | virtual assistant | 10/12/2025 | |||||||||||||||||
| PSTW-2901 | Provincia IA – AI pilot projects in key public services in the Province of Castellón | https:/www.dipcas.es/es/ia.html__;!!Kz4hg-9TIhMrN2chtpl6!nixrUD8IYjeF0lMUDoUav40IdpJDwa5YvJhLmXsd4BTU54LhJ_NfHTdnJkF8zn7JHdcLs3Oxy40LtVNyttrbMhJYmKAEVSlDwRJJTcxjwhW2EVtciQ$ | The Castellón Provincial Council, consistently attuned to emerging challenges, seeks to position itself as a leader in shaping the legal, technological, and social framework that will support the responsible and orderly use of artificial intelligence as a driver of modernisation across the entire province. Its ambition is to enhance residents’ quality of life and create new opportunities through a technology which, far from belonging to the future, has already become a defining frontier for public administrations. To this end, a structured Roadmap is being developed to identify all the necessary elements for the sequential creation of a comprehensive and sustainable strategy for the deployment of artificial intelligence (AI) in the province of Castellón. This strategy will draw upon the potential of e-government, open government, and public-sector innovation as catalysts for transformation. It also aims to significantly improve public services and increase the efficiency of the Provincial Council as an organisation, making use of the new opportunities enabled by AI while establishing a framework of trust and safeguards against potential risks. To this end, the Roadmap promotes the following AI pilot projects in key public services: Pilot 1: Intelligent virtual assistant for citizen services; Pilot 2: AI system to promote plain language on the Transparency Portal; Pilot 3: AI applied to economic management and tax collection; Pilot 4: AI for predictive analysis in public procurement. | Local | Spain | ES | Castellón Provincial Council | Local government | General public services | General public services n.e.c. | In development | 2.025 | Public services and engagement | Service integration (various) | No | No | Artificial Intelligence | G2G | x | x | x | x | Self-reporting tool | Services | AI services | virtual assistant | 09/12/2025 | ||||||||||||||||||
| PSTW-2801 | Drones and AI to tackle congestion | https://www.euronews.com/next/2025/10/08/finland-is-using-drones-and-ai-to-tackle-congestion-is-it-safe | The Helsinki Drone- and AI-Based Traffic Monitoring Project uses unmanned aerial vehicles and artificial intelligence to analyse real-time mobility patterns in and around the city’s busiest transport areas, including the harbour district. The drones capture video of cars, trams, cyclists, scooters and pedestrians, and AI systems then process this footage into anonymised traffic data. The project creates a detailed digital representation of urban traffic conditions, enabling planners to simulate congestion scenarios, test mobility solutions and design safer, more efficient transport flows. Its overall aim is to reduce congestion, support sustainable mobility choices and improve the management of Helsinki’s urban transport network. | Local | Finland | FI | City of Helsinki | Local government | Economic affairs | Transport | In development | 2.025 | Analysis, monitoring and regulatory research | Prediction and planning | No | No | Artificial Intelligence | G2G | x | x | x | x | https://www.euronews.com/next/2025/10/08/finland-is-using-drones-and-ai-to-tackle-congestion-is-it-safe | Integration and Interaction | Robotics and Automation | 09/12/2025 | |||||||||||||||||||
| PSTW-2804 | TOURISMO Project - Florence | https://tourismo.interreg-euro-med.eu/2025/10/21/innovation-and-tourismo-the-municipality-of-florence-with-smart-technologies-and-thermal-cameras-to-monitor-tourist-flows/ | The Municipality of Florence is piloting new smart technologies, including thermal cameras and “sniffers”, to monitor and manage tourist flows in the historic centre as part of the TOURISMO – TOURism Innovative and Sustainable Management of flOws project funded by Interreg Euro‑MED. Thermal cameras in Piazza Duomo and sensors across key sites such as Ponte Vecchio and Piazza Pitti collect anonymised data using AI algorithms to analyse visitor movements and behaviours. This information is made available to city authorities to improve liveability, address overtourism challenges, and support sustainable tourism planning. The initiative also includes interactive tools like QR codes for real‑time visitor feedback, and aims to produce a replicable operational manual for use in other European contexts | Local | Italy | IT | City of Florence | Local Government | Recreation, culture and religion | Cultural services. | Pilot | 2.024 | Analysis, monitoring and regulatory research | Prediction and planning | No | No | Artificial Intelligence | G2G | x | x | x | x | https://www.intesasanpaoloinnovationcenter.com/it/news-ed-eventi/news/2023/06/smart-city-a-che-punto-siamo-in-italia/ | Perception | Computer vision | 18/12/2025 | |||||||||||||||||||
| PSTW-2805 | TOURISMO Project - Malta | https://tourismo.interreg-euro-med.eu/2025/05/15/beach-monitoring-at-golden-bay-in-malta-kicks-off/ | As part of the TOURISMO – Tourism Innovative and Sustainable Management of flOws programme, a pilot beach monitoring system was launched at Golden Bay to help manage overtourism and protect the area’s natural environment. The initiative, led by the Malta Regional Development and Dialogue Foundation (MRDDf) and Il‑Majjistral Nature and History Park, uses GDPR‑compliant people‑counting CCTV and deep‑learning algorithms to monitor pedestrian and vehicle traffic, providing real‑time data on visitor densities and behaviours. This information supports sustainable tourism planning and conservation of the bay’s unique dune ecosystems, with input from local stakeholders including the Mellieħa Local Council, Environmental Resources Authority, Cleansing Department, and Malta Tourism Authority. | Local | Malta | MT | Malta Regional Development | Regional Government | Environmental protection | Environmental protection n.e.c. | Implemented | 2.025 | Analysis, monitoring and regulatory research | Prediction and planning | No | No | Artificial Intelligence | G2G | x | x | x | x | https://www.intesasanpaoloinnovationcenter.com/it/news-ed-eventi/news/2023/06/smart-city-a-che-punto-siamo-in-italia/ | Perception | Computer vision | 18/12/2025 | |||||||||||||||||||
| PSTW-2813 | Dryads - AI-powered platform to manage forest resilience and mitigate climate change impacts | https://dryads.scanlab.gr/ | Dryads is an AI-powered environmental monitoring platform developed by the SCAN Laboratory at the National and Kapodistrian University of Athens in cooperation with the Hellenic Ministry of Environment and Energy. Launched in 2024, it aims to strengthen forest resilience and mitigate climate change impacts, particularly wildfire risks. The platform uses AI and digital twin technologies to integrate IoT sensors, drone imagery, and environmental data into 3D geospatial models. This enables continuous forest monitoring, early wildfire detection, and fire evolution prediction, helping authorities intervene effectively. Dryads also supports vulnerability assessment and prevention strategies for forests and surrounding communities. | National | Greece | EL | University of Athens | Academic-Research | Environmental protection | Environmental protection n.e.c. | Implemented | 2.024 | Internal management | Internal support processes | No | No | Artificial Intelligence | G2G | x | x | x | x | https://scan.di.uoa.gr/iclei-action-fund-greece-dryads/ | Learning | Machine learning | 16/12/2025 | |||||||||||||||||||
| PSTW-2866 | Introduction of Microsoft 365 Copilot within the public sector | https://mita.gov.mt/2025/07/28/empowering-public-service-the-introduction-of-microsoft-365-copilot-within-the-public-sector/ | The Malta Information Technology Agency (MITA) announced that, starting in 2025, the Maltese government will roll out Microsoft 365 Copilot — an AI-powered assistant integrated into Microsoft 365 applications — across the public sector. With a €4 million investment, over 8,000 public-service employees will receive Copilot on their laptops over the next two years and will be trained through a newly established Centre of Excellence to ensure effective adoption. This initiative is part of the national digital governance strategy Vision Malta 2050, aiming to reduce administrative burdens, enhance productivity, and modernise public-service delivery. A notable feature is that Copilot will support the Maltese language, making the tool more accessible to government staff and reinforcing local identity within public administration. | National | Malta | MT | Malta Information Technology Agency (MITA) | Central-Government | General public services | General public services n.e.c. | In development | 2.025 | Internal management | Internal support processes | No | No | Artificial Intelligence | G2G | x | x | x | x | https://mita.gov.mt/2025/07/28/empowering-public-service-the-introduction-of-microsoft-365-copilot-within-the-public-sector/ | Learning | Machine learning | Generative AI | 10/12/2025 | ||||||||||||||||||
| PSTW-2890 | AI Reader - enhancing the efficiency of data entry processes | https://mindigital.gouvernement.lu/en/dossiers/2024/tech-in-gov/projets-tech.html | The project led by the Commissariat aux affaires maritimes (CAM – Commission for Maritime Affairs) aims to develop a tool capable of automatically extracting predefined data from official documents, such as visas, in PDF (text or image) or JPEG format without human intervention. The tool is designed to enhance the efficiency of data entry processes for the Seafarers’ service by minimising the number of data points required from customers, reducing errors during initial data entry, limiting the need for verification and correction by CAM agents, and enabling automatic integration of the extracted data into the relevant systems. | National | Luxembourg | LU | Commissariat aux affaires maritimes (CAM – Commission for Maritime Affairs) | Central-Government | General public services | General public services n.e.c. | In development | 2.025 | Internal management | Internal support processes | No | No | Artificial Intelligence | G2G | x | x | x | x | https://mindigital.gouvernement.lu/en/dossiers/2024/tech-in-gov/projets-tech.html | Learning | Machine learning | 09/12/2025 | |||||||||||||||||||
| PSTW-2891 | AI4DI - AI-Powered Automation of Information Requests | https://mindigital.gouvernement.lu/en/dossiers/2024/tech-in-gov/projets-tech.html | The National Commission for Data Protection’s (CNPD) "Information Requests" service handles a diverse range of inquiries received through email, mail, and telephone. As the number of questions and responses has grown over time, manual searches by staff have become increasingly time-consuming. This project seeks to automate both the retrieval of relevant information and the creation of preliminary draft responses using the existing database. The proposed solution involves developing an AI-powered tool based on a large language model (LLM) that can efficiently identify pertinent information and generate suitable responses. | National | Luxembourg | LU | National Commission for Data Protection’s (CNPD) | Central-Government | General public services | General public services n.e.c. | In development | 2.025 | Internal management | Internal support processes | No | No | Artificial Intelligence | G2G | x | x | x | x | https://mindigital.gouvernement.lu/en/dossiers/2024/tech-in-gov/projets-tech.html | Learning | Machine learning | 09/12/2025 | |||||||||||||||||||
| PSTW-2892 | Legal and normative text analyser | https://mindigital.gouvernement.lu/en/dossiers/2024/tech-in-gov/projets-tech.html | The Luxembourg Office of Accreditation and Surveillance (OLAS) aims to develop a tool, the ‘Legal and Normative Text Analyser’, designed to analyse documentation from recognised and reliable sources such as Legilux, EUR-Lex, ISO, CEN, EA, ILAC, IAF, as well as locally stored files. The tool will identify and collect relevant documents or information demonstrating compliance with the requirements applicable to the accreditation of specific activities, analyse their content to extract the necessary requirements for accrediting conformity assessment bodies, and generate detailed reports based on the analysis results. | National | Luxembourg | LU | Luxembourg Office of Accreditation and Surveillance (OLAS) | Central-Government | General public services | Executive and legislative organs, financial and fiscal affairs, external affairs. | In development | 2.025 | Internal management | Internal support processes | No | No | Artificial Intelligence | G2G | x | x | x | x | https://mindigital.gouvernement.lu/en/dossiers/2024/tech-in-gov/projets-tech.html | Learning | Machine learning | 09/12/2025 | |||||||||||||||||||
| PSTW-2918 | Gismap AI model for land cover analysis | https://videncenter.kl.dk/viden-og-vaerktoejer/ai/kommunernes-ai-landkort | The Gismap solution, implemented by the Ballerup Municipality in 2025, enables the generation of land cover data using an AI model, editing tools, and integration with various environmental datasets. The solution is applied for purposes such as biodiversity registration, operational optimisation, ESG reporting, strategic planning, and spatial planning. The platform is built on publicly available data sources, including the Danish Climate Data Agency, GeoDanmark, the Danish Environmental Portal, and the Ministry of Environment. | Local | Denmark | DK | Ballerup Municipality | Local government | Environmental protection | Environmental protection n.e.c. | Implemented | 2.025 | Analysis, monitoring and regulatory research | Prediction and planning | No | No | Artificial Intelligence | G2G | x | x | x | x | https://videncenter.kl.dk/viden-og-vaerktoejer/ai/kommunernes-ai-landkort | Learning | Machine learning | 19/12/2025 | |||||||||||||||||||
| PSTW-2925 | Pluto – Road Analysis and Maintenance | https://videncenter.kl.dk/viden-og-vaerktoejer/ai/kommunernes-ai-landkort | Pluto Technologies has developed an AI-based solution that identifies issues with the municipality’s roads using smartphones and GPS, for example, devices installed on municipal refuse trucks. The tool automatically detects damage and wear on road surfaces, eliminating the need for staff to manually collect and record this information. The collected data is visualised on a digital map, enabling more effective and targeted planning of repairs. The solution can help ensure roads are repaired in a timely manner, potentially extending their lifespan by up to 30%. Additionally, the system supports resource prioritisation, provides an overview of heavily used areas, and generates analyses for preventive maintenance. | Local | Denmark | DK | Hvidovre Municipality | Local government | Economic affairs | Transport | Implemented | 2.026 | Analysis, monitoring and regulatory research | Prediction and planning | No | No | Artificial Intelligence | G2G | x | x | x | x | https://videncenter.kl.dk/viden-og-vaerktoejer/ai/kommunernes-ai-landkort | Perception | Computer vision | 19/12/2025 | |||||||||||||||||||
| PSTW-2666 | Lab.ai: the heart of artificial intelligence in public administration | https://www.siag.it/it/news/lab-ai-e-digital-twin-due-iniziative-orientate-al-futuro | Lab.ai is an initiative launched by Informatica Alto Adige (SIAG) under the strategy of introducing artificial intelligence into public administration. The project operates out of NOI Techpark in Bolzano and is responsible for coordinating the research, development, and training efforts related to AI applications in both public sector and local businesses. It was established as part of a structured AI strategy, including partnerships with Microsoft and Eurac Research, and will be supported by a dedicated AI competence center to ensure strategic oversight, ethical compliance, and innovation. | National | Italy | IT | Informatica Alto Adige SpA | Local Government | General public services | General public services n.e.c. | In development | 2.025 | Internal management | Internal support processes | No | Yes | Artificial Intelligence | G2G | x | x | x | x | https://www.siag.it/it/news/lab-ai-e-digital-twin-due-iniziative-orientate-al-futuro | AI services | 28/08/2025 | ||||||||||||||||||||
| PSTW-2886 | Assitance in drafting judgments JUAIDE | https://mindigital.gouvernement.lu/en/dossiers/2024/tech-in-gov/projets-tech.html | This project concerns an artificial intelligence component to assist judges in drafting legal documents. It analyses the context of the text being drafted in real time and automatically suggests relevant legal texts and court decisions. This system shall significantly reduce the time spent on legal research, while improving the accuracy and quality of the references used. By facilitating immediate access to applicable legal information, it will optimise the drafting process and enhance the efficiency of the judicial process. | National | Luxembourg | LU | Ministry of Digitalisation | Central-Government | Public order and safety | Law courts | In development | 2.025 | Internal management | Internal support processes | No | No | Artificial Intelligence | G2G | x | x | x | x | https://mindigital.gouvernement.lu/en/dossiers/2024/tech-in-gov/projets-tech.html | Learning | Machine learning | Natural language processing | 09/12/2025 | ||||||||||||||||||
| PSTW-2880 | Automatic labelisation of documents | https://mindigital.gouvernement.lu/en/dossiers/2024/tech-in-gov/projets-tech.html | The Central legislative service aims to automatically label (categorise/classify) documents based on their content, with a view to coupling a chatbot with the knowledge graph of Luxembourgish legislation. | National | Luxembourg | LU | Central Legislative Service | Central-Government | General public services | Executive and legislative organs, financial and fiscal affairs, external affairs. | Implemented | 2.025 | Internal management | Internal support processes | No | No | Artificial Intelligence | G2G | x | x | x | https://mindigital.gouvernement.lu/en/dossiers/2024/tech-in-gov/projets-tech.html | Learning | Machine learning | chatbot | 03/12/2025 | |||||||||||||||||||
| PSTW-1915 | Auditing a City of Vienna AI solution under IEEE CertifAIEd | https://www.actuia.com/english/vienna-first-city-in-the-world-to-be-certified-by-ieee-ai-ethics-for-its-digital-humanism-strategy/ | Public service providers increasingly deploy automated systems that must align with ethical, legal, and societal values. The City of Vienna sought to ensure that its digital services adhere to principles of transparency, accountability, and human-centric design. This pilot addresses the challenge of systematically assessing automated systems used by a large municipal service provider, Wiener Stadtwerke. Stakeholders include public authorities, service users, regulators, and technology developers. The objective is to validate that deployed systems meet recognised standards for responsible and trustworthy use. The solution applies the IEEE CertifAIEd assessment process to a concrete application, evaluating governance, risk management, transparency, and impact on users. Independent auditors analyse documentation, development processes, and operational practices against established criteria. The impact includes increased organisational awareness of ethical and governance requirements, strengthened trust in public digital services, and international recognition of Vienna’s digital humanism strategy. The pilot provides a reference for other cities seeking structured assurance of responsible technology deployment in public services. | Regional | Austria | AT130 | Wiener Stadtwerke | Local Government | General public services | Executive and legislative organs, financial and fiscal affairs, external affairs. | Pilot | 2.021 | 2022 | Analysis, monitoring and regulatory research | Monitoring policy implementation | No | Yes | Artificial Intelligence | G2G | x | x | x | x | x | https://standards.ieee.org/news/ieee-certifaied/ | Services | AI Services | 28/01/2026 | |||||||||||||||||
| PSTW-2905 | Similis: for the identification of similar and identical amendments | https://github.com/SenatoDellaRepubblica/Similis | The IT Department of the Italian Republic Senate has developed Similis, a system for clustering similar and identical parliamentary amendments, in close collaboration with the Institute of Legal Informatics and Judicial Systems of the National Research Council (CNR-IGSG). Similis is designed to support legislative processes by automatically identifying amendments that share highly similar wording, helping to reduce duplication and improve the efficiency of parliamentary analysis. The system focuses on syntactic similarity rather than semantic interpretation, favouring amendments with closely matching sentence structures and phrasing. It operates without relying on any prior metadata or predefined information about the amendments. Instead, amendments are grouped using hierarchical agglomerative clustering (HAC) with complete linkage. Each amendment is represented as a vector generated through a bag-of-words model with term frequency (TF) weighting and Euclidean normalisation, following standard pre-processing steps such as stemming and stop-word removal. Similarity between amendments is calculated using a cosine similarity metric, with empirically determined thresholds of 0.8 for cosine similarity and 0.2 for dendrogram cut-off. Integrated into a broader suite of digital legislative tools developed by the Senate, Similis complements other AI-supported systems for amendment organisation, classification, and analysis, contributing to more transparent, structured, and efficient law-making processes. | National | Italy | IT | Italian Senate of the Republic | Central-Government | General public services | Executive and legislative organs, financial and fiscal affairs, external affairs. | Implemented | 2.023 | Internal management | Internal support processes | No | No | Artificial Intelligence | G2G | x | x | x | https://www.senato.it/application/xmanager/projects/leg19/attachments/documento/files/000/112/897/DA34_Focus_IA_in_Senato.pdf | Learning | Machine learning | 15/12/2025 | ||||||||||||||||||||
| PSTW-2170 | Data-driven water infrastructure maintenance in Burgas | https://www.datatopolicy.org/use-case/data-driven-water-infrastructure-maintenance-enabled-by-ai | Ageing water infrastructure causes significant water losses, threatening sustainability, service reliability, and public resources. In some regions, leakage rates reach critical levels, requiring proactive detection and maintenance strategies. The Burgas municipality addresses this challenge by modernising water network monitoring to reduce losses and optimise asset management. Stakeholders include municipal utilities, maintenance operators, and residents. The objective is to detect leaks early, improve water supply reliability, and reduce long-term operational costs. The solution deploys vibration sensors along water pipes to continuously monitor acoustic patterns associated with leaks. Large volumes of sensor data are analysed using predictive models that distinguish normal operation from leak signatures in real time. Continuous automated monitoring enables faster detection than manual inspection methods. The project delivers reduced water losses, improved maintenance planning, and more efficient use of public funds. It strengthens resilience of water infrastructure, enhances service continuity, and supports sustainable water management, offering a replicable model for municipalities facing similar challenges across Europe. | Local | Bulgaria | BG | Municipality of Burgas | Local Government | Housing and community amenities | Water supply. | Pilot | 2.021 | 2024 | Internal management | Internal support processes | No | No | Artificial Intelligence | G2G | x | x | x | x | x | Self-reporting tool | Planning | Planning and Scheduling | 28/01/2026 | |||||||||||||||||
| PSTW-1917 | Z-Inspection – Assessment for Responsible Artificial Intelligence | https://oecd.ai/en/catalogue/tools/z-inspection/tool-use-cases/assessment-for-responsible-artificial-intelligence | Governments adopting automated systems face complex ethical, legal, and social considerations that cannot be addressed through technical evaluation alone. The Z-Inspection pilot in the Province of Fryslân addresses the need for holistic assessment methods that support responsible adoption across public administrations. Stakeholders include policymakers, civil servants, citizens, and interdisciplinary experts. The objective is to identify risks, ethical dilemmas, and governance gaps early in the lifecycle of automated systems and to build institutional capacity for responsible use. The solution applies the Z-Inspection methodology, bringing together experts from multiple disciplines to analyse the purpose, design, data use, and societal impact of a concrete system. Structured discussions explore conflicts of interest, accountability, and alignment with public values. The outcomes are documented as lessons learned and shared across government. The impact includes improved understanding of responsible deployment practices, increased digital awareness, and a practical framework for assessing future systems. The pilot supports more confident, transparent, and trustworthy use of advanced technologies in the public sector. | Regional | Netherlands | NL12 | Provincie Fryslân | Regional Government | General public services | Executive and legislative organs, financial and fiscal affairs, external affairs. | Pilot | 2.023 | 2023 | Analysis, monitoring and regulatory research | Monitoring policy implementation | No | Yes | Artificial Intelligence | G2G | x | x | x | x | x | https://z-inspection.org/ | Services | AI Services | 28/01/2026 | |||||||||||||||||
| PSTW-2664 | MSE - assisted text system for parliamentary amendments | https://comunicazione.camera.it/archivio-prima-pagina/19-51129 | MSE (Macchina Scrittura Emendamenti) is an AI-powered, assisted drafting system designed to support deputies in preparing parliamentary amendments. Developed by the inter-university consortium Alma Human AI (involving the Universities of Bologna, LUISS, CNR, University of Verona, and University of Turin), MSE offers a text-editor interface that operates directly on the draft bills under consideration. It transforms modifications into formally correct amendment proposals in real time, conforming to the Chamber’s strict syntactic rules. Additionally, MSE includes an internal chatbot accessible by commissions and parliamentary groups. This chatbot retrieves relevant documentation—such as dossiers, hearing transcripts, and deposited memoranda—and provides links to official sources. A future module (currently in development) will further assist by suggesting refined technical phrasing for amendments, guided by natural-language interaction with the user. Currently in use by parliamentary groups on a trial basis, MSE is expected to be officially rolled out by the end of 2025 | National | Italy | IT | Alma Human AI | Academic-Research | General public services | Executive and legislative organs, financial and fiscal affairs, external affairs. | In development | 2.025 | Analysis, monitoring and regulatory research | Information analysis processes | No | No | Artificial Intelligence | G2G | x | x | x | x | https://comunicazione.camera.it/archivio-prima-pagina/19-51130 | Learning | Machine learning | Generative AI | chatbot | 28/08/2025 | |||||||||||||||||
| PSTW-2663 | NORMA - virtual assistant for the analysis of legislative production | https://comunicazione.camera.it/archivio-prima-pagina/19-51129 | Norma is a prototype developed from the Legislab proposal by the Polytechnic University of Milan and the Einaudi Institute for Economics and Finance. It uses Artificial Intelligence to interact with the Chamber of Deputies’ Legislative Observatory through natural language, making it easier to access data on the legislative process. For example, users can retrieve information on amendments, legislative texts, and the parliamentary progress of laws—data also used for the Chamber’s annual legislation report. Norma can also present results in the form of charts and tables, enhancing clarity and accessibility. By querying certified parliamentary archives, the system ensures accuracy and allows for reliable verification of legislative documentation. This innovation is expected to improve AI research capabilities and the generation of both statistical and analytical data on lawmaking, ultimately serving as a valuable tool for the Chamber’s institutional work. | National | Italy | IT | Polytechnic University of Milan and the Einaudi Institute for Economics and Finance | Academic-Research | General public services | Executive and legislative organs, financial and fiscal affairs, external affairs. | In development | 2.025 | Analysis, monitoring and regulatory research | Information analysis processes | No | No | Artificial Intelligence | G2G | x | x | x | x | https://comunicazione.camera.it/archivio-prima-pagina/19-51129 | Learning | Machine learning | Generative AI | virtual assistant | 28/08/2025 | |||||||||||||||||
| PSTW-2878 | JUANO - app to anonymise court decisions for publication on the justice internet portal | https://mindigital.gouvernement.lu/en/dossiers/2024/tech-in-gov/projets-tech.html | JUANO is an application that helps anonymise court decisions for publication on the justice internet portal. JUANO is based on an artificial intelligence engine that recognises entities to be anonymised and automatically suggests categories based on the text. This application ensures the consistency of the anonymisation of court decisions and facilitates the process of making them available to lawyers and other interested parties in compliance with data protection regulations. | National | Luxembourg | LU | La Justice - Luxembourg | Central-Government | Public order and safety | Law courts | Implemented | 2.025 | Internal management | Data Sharing Management | No | No | Artificial Intelligence | G2G | x | x | x | https://mindigital.gouvernement.lu/en/dossiers/2024/tech-in-gov/projets-tech.html | Learning | Machine learning | 09/12/2025 | ||||||||||||||||||||
| PSTW-2672 | Pioneering Use of Microsoft Copilot - Barnsley Council | https://www.local.gov.uk/case-studies/barnsley-council-pioneering-use-microsoft-copilot | Barnsley Council has pioneered the use of Microsoft Copilot in local government. Starting in late 2023 with 300 licenses, the pilot quickly expanded to 2,000, and by January 2024 Copilot was rolled out across the organisation to automate administrative tasks and boost staff efficiency. The council emphasised stakeholder engagement, training, and governance, including an ethics board and protocols for high-risk areas like children’s social care. Early adoption has improved productivity in finance, business support, and social care, allowing staff to focus on more meaningful work while advancing digital transformation in public services. | Local | United Kingdom | UK | Barnsley Council | Local Government | General public services | General public services n.e.c. | Implemented | 2.023 | 2024 | Internal management | Internal support processes | No | No | Artificial Intelligence | G2G | https://www.local.gov.uk/our-support/cyber-digital-and-technology/artificial-intelligence-hub/artificial-intelligence-case | Learning | Machine learning | Generative AI | 28/08/2025 | |||||||||||||||||||||
| PSTW-2673 | Foundry - Birmingham City | https://www.local.gov.uk/case-studies/birmingham-city-council-foundry | Birmingham City Council launched the Foundry in 2023 to drive digital transformation, address budget challenges, and develop internal capabilities while reducing reliance on external consultants. Operating under "think big, start small, learn and scale quickly," it uses a collaborative, value-driven approach where multi-disciplinary teams co-develop AI solutions with frontline staff, ensuring practical interventions that improve efficiency, reduce costs, and enhance work experiences while fostering a digitally confident workforce committed to data-informed continuous improvement. The Foundry has implemented AI solutions across four critical back-office functions with measurable impact. Microsoft Copilot automates administrative tasks like legal document summaries and Subject Access Requests. A UiPath-powered automated redaction tool tackles overwhelming paperwork volumes from litigation claims, enabling timely compliance and reducing fine risks. A SharePoint translation tool handles simple documents in 30 languages, freeing translators for complex work. Most innovatively, an AI-powered communications mining solution analyzes emails for real-time citizen insights and automatically routes thousands of incoming messages to appropriate teams, transforming manual sorting into efficient automated processes that enable faster responses and improved citizen service. | Local | United Kingdom | UK | Birmingham City | Local Government | General public services | General public services n.e.c. | Implemented | 2.023 | Internal management | Internal support processes | No | No | Artificial Intelligence | G2G | https://www.local.gov.uk/our-support/cyber-digital-and-technology/artificial-intelligence-hub/artificial-intelligence-case | Learning | Machine learning | Generative AI | 28/08/2025 | ||||||||||||||||||||||
| PSTW-2674 | Buckinghamshire Council: Early adoption of Microsoft Copilot | https://www.local.gov.uk/case-studies/buckinghamshire-council-early-adoption-microsoft-copilot | Buckinghamshire Council became one of the first UK local authorities to adopt Microsoft Copilot in October 2023, granting early access to 300 staff across departments such as digital services, business support, and customer service. Their strategic rollout aimed to enhance staff productivity, improve work quality, achieve cost savings, mitigate risks, and promote staff well-being. To engage staff and identify practical use cases, the council hosted a "Dragon's Den"-style event where teams from various departments pitched how Copilot could benefit their work. This initiative not only generated excitement but also fostered cross-departmental collaboration. The council established a governance board, meeting fortnightly, to oversee the implementation, share progress, and address challenges. This proactive approach ensured that the adoption of Copilot was aligned with the council's strategic objectives and that any issues were promptly addressed. | Local | United Kingdom | UK | Buckinghamshire Council | Local Government | General public services | General public services n.e.c. | Implemented | 2.023 | Internal management | Internal support processes | No | No | Artificial Intelligence | G2G | https://www.local.gov.uk/our-support/cyber-digital-and-technology/artificial-intelligence-hub/artificial-intelligence-case | Learning | Machine learning | Generative AI | 28/08/2025 | ||||||||||||||||||||||
| PSTW-2675 | Greater Cambridge Shared Planning: AI-Driven Summarisation for Local Plan Consultations | https://www.local.gov.uk/case-studies/greater-cambridge-shared-planning-ai-driven-summarisation-local-plan-consultations | The Greater Cambridge Shared Planning (GCSP) service, a partnership between South Cambridgeshire District and Cambridge City councils, has integrated artificial intelligence (AI) into its planning consultation processes. Faced with the administrative challenge of processing approximately 9,500 public comments per Local Plan consultation, GCSP sought to reduce the time and resources required for summarising these responses. Through support from the Ministry of Housing, Communities and Local Government’s PropTech Innovation Fund, GCSP developed an AI tool capable of summarising consultation feedback in under an hour, compared to the previous 18.5 hours of officer time. This advancement allows planning officers to focus on higher-value tasks, such as analysing public feedback and engaging with stakeholders, thereby enhancing the efficiency and quality of the planning process | Local | United Kingdom | UK | Cambridge City Council | Local Government | General public services | General public services n.e.c. | Implemented | 2.023 | Public services and engagement | Prediction and planning | No | No | Artificial Intelligence | G2G | https://www.local.gov.uk/our-support/cyber-digital-and-technology/artificial-intelligence-hub/artificial-intelligence-case | Learning | Machine learning | 28/08/2025 | |||||||||||||||||||||||
| PSTW-2690 | DeepMiner: Transforming business support through data integration | https://www.civtech.scot/portfolio | In 2022, the Scottish Government’s Directorate for COVID Business Resilience and Support set a challenge: how could data about businesses be used to improve the design, delivery, and evaluation of business support services across the public sector? Business data in Scotland was found to be fragmented across multiple organisations, limiting efficiency and effective service delivery. DeepMiner responded with the Data Spine, a single point of truth for all businesses in Scotland. By integrating and structuring economic data from diverse sources, the platform enables policymakers to access comprehensive insights, anticipate economic shocks, and design targeted policy responses. Beyond government, the solution offers significant economic and societal value by breaking down data silos and enabling smarter decision-making across organisations. Founded in 2017 through CivTech, DeepMiner pivoted in 2020 to focus on advanced AI-driven data technologies. Today, its team of five continues to innovate, making complex business data more accessible, usable, and impactful for Scotland’s economy. | National | United Kingdom | UK | Scottish Government’s Directorate for Equality, Inclusion & Human Rights | Central-Government | General public services | Executive and legislative organs, financial and fiscal affairs, external affairs. | Implemented | 2.022 | Analysis, monitoring and regulatory research | Prediction and planning | No | No | Artificial Intelligence | G2G | x | x | x | x | https://www.civtech.scot/ | Services | 29/08/2025 |