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Title	Aqmon: A Fine-Grained Air Quality Monitoring System Based On Uav Images For Smart Cities
ID_Doc	10241
Authors	Xia S.; Xing T.; Chase Q.W.U.; Liu G.; Yang J.; Li K.
Year	2024
Published	ACM Transactions on Sensor Networks, 20, 2
DOI	http://dx.doi.org/10.1145/3638766
Abstract	Air quality monitoring is important to the green development of smart cities. Several technical challenges exist for intelligent, high-precision monitoring, such as computing overhead, area division, and monitoring granularity. In this article, we propose a fine-grained air quality monitoring system based on visual inspection analysis embedded in unmanned aerial vehicle (UAV), referred to as AQMon. This system employs a lightweight neural network to obtain an accurate estimate of atmospheric transmittance in visual information while reducing computation and transmission overhead. Considering that air quality is affected by multiple factors, we design a dynamic fitting approach to model the relationship between scattering coefficients and PM2.5 concentration in real time. The proposed system is evaluated using public datasets and the results show that AQMon outperforms four existing methods with a processing time of 13.8 ms. © 2024 Copyright held by the owner/author(s)
Author Keywords	computer vision; mobile devices; Smart air detection system

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