Abstract
Air pollution is one of the vital problems faced by the world today. Air pollution is an essential cause of global warming and causes various health issues to living organisms. The growing digital technology possibly helps to monitor air pollution and could find a possible solution to prevent air pollution. This paper presents Artificial Intelligence (AI)-based Machine Learning (ML) empowered Internet of Things (IoT) technology for air quality monitoring and forecasting techniques. The proposed technology measures Carbon Monoxide (CO), Sulfur dioxide (SO2), Nitrogen Dioxide (NO2), Ozone element (O3), and Particulate Matter (PM) levels in the air. The proposed technology uses intelligent ML techniques to estimate the air quality index and provides possible fore- casting on the air quality index. Through the forecasted data suitable policies can be framed to reduce air pollution. The air quality index obtained through the proposed technique is displayed in color bar graph, where the color indicates the level of air quality index. The obtained results have been directly fed to the cloud server through IoT and forecasting has been carried out through the ML technique. The results explore the air pollution level and the hazardous level of air pollution and results benefits the human kind to know the level of air pollution and adopt substantial development.
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Gupta, S., Naidu, P.C.B., Kuppan, V., Alagumeenaakshi, M., Niruban, R., Swaminathan, J.N. (2023). Analysis of Various Toxic Gas Levels Using 5G ML-IoT for Air Quality Monitoring and Forecasting. In: Choudrie, J., Mahalle, P., Perumal, T., Joshi, A. (eds) IOT with Smart Systems. Smart Innovation, Systems and Technologies, vol 312. Springer, Singapore. https://doi.org/10.1007/978-981-19-3575-6_75
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DOI: https://doi.org/10.1007/978-981-19-3575-6_75
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