Imagine a smart weather app, but instead of rain, it predicts how pollution from factories will affect a person's brain and heart as they age. It uses AI to connect the dots between where someone lives, their job, and their future health risks. This helps cities plan better healthcare before people actually get sick.
Governments and insurers struggle to predict the long-term financial burden of disability in aging populations living in polluted industrial zones. Current tools cannot handle the complex, non-linear relationship between environment, socio-economics, and chronic diseases.
A web-based AI platform (mistralplatform.eu) for dynamic health impact assessment and AIRWINGS indoor air quality monitoring devices.
If you are a provider dealing with unpredictable long-term care costs for aging populations — this project developed an AI predictive toolkit that forecasts trajectories of disability and quality of life reduction. This allows for more accurate risk pricing based on geographical pollution exposure.
If you are a hardware company dealing with the need for validated indoor monitoring — this project developed AIRWINGS devices for indoor air quality monitoring. These are currently being validated in real-world urban settings like Taranto.
If you are a city manager dealing with high rates of non-communicable diseases — this project developed a web-based platform for dynamic health impact assessment. It indicates the trade-offs of different policy choices to better support the health needs of the population.
Based on available project data, no specific commercial pricing or cost model is mentioned; the project is funded by an EU contribution of EUR 3,619,635.
Yes, the platform is designed for scalable adaptation and has already been validated across three different steel-industry exposed areas in Italy, Poland, and Belgium.
Based on available project data, the specific licensing terms are not listed, but the platform is built using open real-world data.
The system uses a federated learning architecture and a virtual infrastructure to provide secure, federated data processing and administration.
The project period runs from 2023-01-01 to 2026-12-31, with the virtual infrastructure already launched and operational.
The consortium is well-balanced for a tech-transfer project, consisting of 12 partners across 7 countries. With a 25% industry ratio (3 industrial partners) and 4 SMEs, there is a strong bridge between the 6 universities and the commercial market, ensuring the AI tools are grounded in industrial reality.
Contact Istituto Superiore di Sanità in Italy
Contact us to explore licensing opportunities for the MISTRAL AI predictive toolkit.
