Data analysis/detection/prediction tools for the UCLouvain campus

Details

Supervisors

Sadre, Ramin

Faculty

Ecole polytechnique de Louvain

Degree label

Master [120] : ingénieur civil en informatique, à finalité spécialisée

Abstract

For several years, air quality is a data that is much analysed by scientists. Because it has heavy consequences on human health but also on the climate and other living beings. The COVID-19 pandemic has accentuated this air quality analysis. And it is another particule that has interested scientists, the Carbon dioxide concentration. Ventilation is one of the most important solutions to combat aerosol-borne diseases such as COVID-19. But how do you know if a room is sufficiently ventilated? By looking at the CO2 concentration which serves as a ventilation indicator. The Belgian government has issued recommendations for indoor air quality control and ventilation, with the aim of keeping CO2 levels as low as possible. In this master thesis, we will try to create Artificial Intelligence that will allow the prediction of these CO2 values in advance in order to have maximum control over this indoor CO2 concentration. To do this we will base our work on a dataset of 9 rooms, with temperature, humidity, light, and motion data as well as CO2 data.