Prediction and Analysis of Air Quality Using Machine Learning

Abstract

Numerous natural issues including air,water contamination and some more. Air contamination has direct effect on human health. With increment in contamination, it is profoundly important to actualizing innovative models that will make an information record about concentration of air pollutants that are available and furthermore anticipate the contamination rate specifically in urban zones. Testimony of this unsafe gases noticeable all around is influencing the individuals wellbeing, particularly in urban territories.It is profoundly basic and key to develop a continuously analysing and prediction system to evaluate and envision the degree of air pollution precisely, and anticipate pollutant fixations accurately. In this paper, we are proposing  air quality checking and prediction structure subject to clear information of earlier years utilizing Machine learning algorithmss like Random Forest, Decision tree learning and SVM(Support Vector Machine)To guarantee accomplishment of this system, data is assembled from different regions and given as training data to Machine Learning models. To accumulate the consistent ongoing real time information, IoT is composed by using sensors.