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Smart city article details

Title	Air Quality Index Prediction Using Various Machine Learning Algorithms
ID_Doc	7157
Authors	Bajpai M.; Jain T.; Bhardwaj A.; Kumar H.; Sharma R.
Year	2023
Published	6G Enabled Fog Computing in IoT: Applications and Opportunities
DOI	http://dx.doi.org/10.1007/978-3-031-30101-8_4
Abstract	One of the most critical factors for human survival is air. The quality of air inhaled by humans affects their health and lives significantly. The continuously rising air pollution is a significant concern as it threatens human health and is an environmental issue in many Indian cities. A proper AQI prediction system will help tackle the problem of air pollution more efficiently and mitigate the health risks it causes. Government agencies use the Air Quality Index, a number to indicate the pollution level of the air to the public. It qualitatively illustrates the current state of the air. Aggregate values of PM2.5, PM10, CO2,NO2, and SO2 have been taken to forecast the AQI for Pune city using the dataset collected by Pune Smart City Development Corporation Limited and IISc in 2019. This study aims to find the machine learning method which forecasts the most accurate AQI and its analysis. © Springer Nature Switzerland AG 2023. All rights reserved.
Author Keywords	Air quality index; KNN; Linear regression; Machine learning; Prediction; Random forest

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