文章基本信息

标题：Air Pollution Monitoring and Prediction using IOT and Machine Learning
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作者：Sneha Balasubramanian ; Talapala Sneha ; Vinushiya B 等
期刊名称：International Journal of Computer Science and Information Technologies
电子版ISSN：0975-9646
出版年度：2021
卷号：12
期号：2
页码：60-65
语种：English
出版社：TechScience Publications
摘要：Air pollution is the presence of substances in the atmosphere that are harmful to the health of humans and other living beings or that can cause damage to the climate or to materials. Soot, smoke, mold, pollen, methane, and carbon dioxide are few examples of common pollutants. There is a critical need for systems that not only monitor air pollution levels but can also predict future levels of pollution. Hence, in this paper, a system which monitors the air quality using MiCS6814 sensor, MQ135 sensor, MQ131 sensor and PM2.5 sensor and forecasts the Air Quality Index for next five hours using Linear Regression, Support Vector Regression, SARIMAX, GBDT and Stacked ensemble model is proposed. The proposed Machine Learning models are compared using RMSE as a metric and the model with lower RMSE value is chosen. This project can be used in major cities to monitor the air quality remotely and can in turn help to reduce the air pollution level.
关键词：IOT;Machine Learning;Air Quality;AQI;Forecasting;Stacking model;GBDT model;SARIMAX model;Linear regression model;SVR model;RMSE