Title: Air Quality Monitoring and Prediction using SVM
Abstract: All countries in the world are facing the major problem of Air Pollution. All countries are coming across with various ways of finding solution to deal with air pollution and reduce the number of pollutants in air over several years. Several types of respiratory problems such as heart diseases and lung cancer are caused by air pollution. So it is the utmost need to find solution to monitor the index of air quality as it is always better to know the level of pollution at the earliest so that preventive measures can be taken. The amount of pollution present in the air is generally termed as Air Quality Index which is abbreviated as AQI. The air quality monitoring system is proposed in this paper which makes use of prediction module for forecasting AQI. The proposed system monitors the air quality over a period and predicts the AQI for upcoming 15 hours. This paper provides Support Vector Machine (SVM) model to forecast the quality of air with AQI for the upcoming 15 hours. The proposed model predicts the amount of pollutants such as PM 2.5, PM10, NO, NO2, NH3 and shows the better performance than linear prediction models when compared in terms of RMSE.
Publication Year: 2022
Publication Date: 2022-08-26
Language: en
Type: article
Indexed In: ['crossref']
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Cited By Count: 4
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