Simularia AI Solutions

Artificial Intelligence Value Chain

Provided by

Simularia

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.

Provided by

Simularia
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Problem

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.

Solution

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

Consulting

Application Markets

Public Administration

Healthcare / Social Services

Solution Progress

Available on the market