Voting Method for AQI Prediction and Monitoring Air Pollution using Real-Time Data

Nowadays Air pollution is of major concern as it deals with environment sustainability. The air pollution is due to the air pollutants like Nitrogen dioxide (NO2), Carbon monoxide (CO3), chlorofluorocarbons, methane and sulfur dioxide, etc. which are very harmful and hazardous. In proposed work, Firstly the best classification algorithm, among Naïve Bayes, J48 Decision tree, Multiclass Label Classifier, Random Forest and SVM, is identified using US pollution data. SVM algorithm delivered more accuracy among all the five algorithms. Then this model should be applied on the real-time data of air pollutants collected from web portal of aqicn.org for Aurangabad city of Maharashtra state. By using the results of this analysis, the notification will be sent on the registered mobiles and the actions will be suggested accordingly to the municipal corporation and the public.