AIR QUALITY PREDICTIVE ANALYSIS USING MACHINE LEARNING









Abstract

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.


Modules


Algorithms


Software And Hardware