Simularia AI Solutions

Artificial Intelligence Value-Chain

Simularia AI Solutions
Polo ICT

What is it

We implement Machine Learning models to integrate and improve our numerical modelling solutions applied to the study of airborne pollutants. We thus obtain accurate and high resolution ground concentration fields to be used in forecasts, epidemiological studies, etc.

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Accurate and high spatial-temporal resolution concentrations maps of airborne pollutants are required in multiple fields (forecast, epidemiology, etc.) It is therefore required to increase the spatial resolution of traditional chemical transport models beyond the typical 1 km scale.




We apply a combined technique based on chemical transport models and ML models (Random Forest, XGBoost, etc.) The latter are trained with measurements from air quality monitoring stations thus improving both the accuracy and the spatial resolution of the concentration maps.

Additional services


Application Markets

Healthcare / Social Services

Public Administration

Solution Progress

Available on the market