Inbound Travel Trends Germany Dashboard
Public sector
Country or Region
GermanySourced From
The German National Tourist Board (GNTB) developed a data-driven solution to analyze visitor trends, improving insights into origin markets, tourist preferences, and marketing performance. The project defined key objectives and indicators to assess the impact of GNTB campaigns, leveraging a specialized data analytics firm for real-time market analysis and reporting. Using Global Distribution Systems (GDS) and flight reservation data, it evaluated campaign success before and after implementation. Machine Learning algorithms predicted trends, helping identify nationality patterns, travel methods, and popular destinations.
Monitoring and Control
Resource Planning
iTwin by Bentley
Public sector
Country or Region
United States of AmericaSourced From
The iTwin platform by Bentley Systems enables the creation of digital twins for infrastructure, providing real-time data and insights to optimize performance and facilitate better decision-making. It integrates various sources like IoT, BIM, and GIS data into one cohesive view for project delivery, operations, and asset management. The platform empowers users to visualize, monitor, and analyze infrastructure throughout its lifecycle, offering collaboration tools that enhance communication and efficiency.
Monitoring and Control
Resource Planning
Mindicity
Public sector
Country or Region
ItalySourced From
Mindicity is an Urban Intelligence platform that uses AI technologies like Computer Vision, Machine Learning, and NLP to optimize city management. It centralizes urban data into a "datalake" to enhance decision-making and urban planning, incorporating scientific models to understand complex urban dynamics. Aimed at improving safety, sustainability, and livability, Mindicity promotes collaboration with open-source components. A notorious example of the platform's usage is its implementation within the "Smart Control Room" in Venice where administrators use real-time city data to enhance safety, optimize mobility, and support crisis management, helping them make informed decisions in critical situations.
Monitoring, Reporting, and Verification (MRV) System for Climate Finance
Public sector
Country or Region
ColombiaSourced From
The Colombian National Planning Department's "Monitoring, Reporting, and Verification" (MRV) system leverages AI algorithms to automate the tracking of climate-related investments by gathering, classifying, and analyzing data from various sources, including public, private, and international databases. It simplifies manual efforts by the Department of Sustainable Development (DADS) in monitoring investments. The system organizes and standardizes information to ensure consistency across time and institutions. It classifies climate financing projects by type (e.g., mitigation or adaptation) and tracks their impact in 12 sectors and 35 subsectors. Data from disparate systems is integrated into a single platform. The AI also estimates investment flows and verifies data accuracy through automated processes. Its core goal is to enhance transparency and inform decision-making on climate financing in Colombia.
Parcel Monitoring Platform Flanders
Public sector
Country or Region
BelgiumSourced From
The Parcel Monitoring Platform Flanders, developed by Digitaal Vlaanderen and VITO, uses AI and geo-imaging to monitor land parcels in real-time. It supports data-driven policy decisions in areas like agriculture, energy, and urban planning. The platform processes Sentinel images and offers a time-series web service called ‘CropSAR’ for easy access to processed data. It combines satellite data with high-resolution imagery and field data for continuous monitoring. This system helps monitor EU Green Deal objectives, providing actionable insights for governmental agencies.
Data Validation
Monitoring and Control
Resource Planning
Signaux Faibles
Public sector
Country or Region
FranceSourced From
Signaux Faibles is an open-source AI tool in France that analyzes public financial and social data to detect early signs of business distress. Using machine learning, it helps government agencies identify at-risk companies up to 18 months in advance, enabling timely intervention. Initially launched in Bourgogne, a region in eastern France, in 2016 and later expanded nationwide, the tool continuously improves through data refinement and transparency. Its open-source nature ensures adaptability, collaboration, and reduced bias in financial risk assessment.
Monitoring and Control
Resource Planning