Examining and protecting the air quality has become one of the most essential activities for the government in
many industrial and urban areas today. With the rapid development of various industries and motorized
transportation, large amounts of harmful substances such as sulfur dioxides, nitrogen oxides, carbon monoxides,
and hydrocarbons are released into the atmosphere, lasting a long time and in concentrations exceeding tolerable
environmental limits. As a result of this, people’s respiratory and cardiovascular systems will get affected.
Therefore, we need to develop models that will record the information about the concentrations of air pollutants
(SO2, NO2, CO etc). In this paper, we are using two machine learning algorithms (Linear Regression and Decision
Tree) are used to predict the concentration of air pollutants in the environment. The results are promising and
the implementation of these algorithms could be very efficient in predicting air pollutants.
Software And Hardware