Analysis of Pandemic Atmosphere Pollution Data Using Virtual Sensors in Sao Paulo City

ABSTRACT

Virtual sensing models have been used to generate synthetic data and provide complementary information. However, with the increase in cases related to COVID-19 and the lockdown, a problematic factor is that virtual sensing models may produce different results than they should since the environment has become better with the decrease in traffic conditions and industrial production. Therefore, this article will evaluate virtual sensing models for the city of Sao Paulo, using pre-pandemic and pandemic data in a lockdown scenario. As a result, we analyzed that even with these behavioral changes in the city, the pre-pandemic model produced similar results to the lockdown period model.