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Title	Air Quality Hotspot Monitoring With Trajectories Of Iot In Smart City Implementation
ID_Doc	7152
Authors	Bhangale S.C.; Varade H.P.; Thorat S.R.; Roy D.K.; William P.; Verma A.
Year	2023
Published	Proceedings - 2023 3rd International Conference on Pervasive Computing and Social Networking, ICPCSN 2023
DOI	http://dx.doi.org/10.1109/ICPCSN58827.2023.00214
Abstract	In the era of 21st century development in industrialization and timely updating technology increases the people needs. Transportation application especially private transport have also increased. This cause emission of greenhouse gases like CO, CO2, NH3, NO, PM2.5 etc. leads to air pollution. Air pollution is serious environmental challenge in our daily lives. Lowering air quality adversely impacts on public health and environment. Measuring and monitoring air quality with the help of deploying IoT based sensors network at particular regions. In this study, AQMS is implemented for detecting air pollution hotspot and identifying source of trajectories. Real-time air quality monitoring system helps to monitor sudden change in the atmosphere. Machine Learning techniques analyze the collected data which helps us to predict climate change. This model reduces complexity and improves efficiency and feasibility and can provide more reliable and accurate decisions regarding smart city development, industrial and transportation management, public health, the environment. © 2023 IEEE.
Author Keywords	Air pollution; Human health; IoT; Machine Learning; Python; Sensor placement

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