IOT BASED AIR QUALITY MONITORING USING DENSENET IN URBAN AREAS
Journal Title: International Journal of Data Science and Artificial Intelligence - Year 2024, Vol 2, Issue 04
Abstract
– Internet of Things is being used more and more in the control and monitoring of air quality. Real-time data regarding air pollutants and other environmental parameters can be gathered by deploying IoT devices with sensors and connectivity capabilities. Rapid urbanization and industry cause increasingly serious problems with air quality. A significant challenge in the current air quality monitoring system is its limited spatial coverage and accuracy. In this paper, a novel air quality monitoring using IoT is proposed to monitor the quality of the air efficiently in real time. Sensors are placed in the various traffic system to collect environmental data and processed it in Real Time Data Analytics Module (RTDM). DenseNet is used to predict the quality of air and classified into three classes namely pure, impure, and normal. The efficacy of the proposed technique has been evaluated using assessment actions such as accuracy, time efficiency, precision, F1 score, RMSE, MAPE, and MAE. By the comparison analysis, the proposed technique’s accuracy rate is 10.08%, 17.64%, and 34.34% higher than the existing Ide Air, SMOTEDNN, and ETAPM-AIT techniques respectively.
Authors and Affiliations
M. Devaki, Jeyaraman Sathiamoorthy and M. Usha
Keywords
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- EP ID EP744942
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IOT BASED AIR QUALITY MONITORING USING DENSENET IN URBAN AREAS
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