The project involves the implementation of a fast, reliable and cost-efficient system for monitoring air quality, collecting and analyzing data on harmful substances (suspended solids or gaseous substances) in the ambient air, as well as on the pollutants that generate them. Such a system is enabled by the development of a prognostic model of pollutant dispersion based on an artificial neural network, which will provide prediction of the spatial distribution of pollutants in places where no sensors are placed.

University of Belgrade, Faculty of Mechanical Engineering