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http://dx.doi.org/10.6109/jkiice.2021.25.1.8

Development of artificial intelligence-based air pollution analysis and prediction system using local environmental variables  

Back, Bong-Hyun (Department of Computer Engineering, Yeungnam University)
Ha, Il-Kyu (Department of Computer Engineering, Kyungil University)
Publication Information
Journal of the Korea Institute of Information and Communication Engineering / v.25, no.1, 2021 , pp. 8-19 More about this Journal
Abstract
The air pollution problem caused by industrialization in recent years is attracting great attention to both the country and the people. Domestic wide-area air pollution information is provided to the public through public data nationally, but regional air pollution information with different environmental variables is very insufficient. Therefore, in this study, we design and implement an air pollution analysis and prediction system based on regional environmental variables that can more accurately analyze and predict regional air pollution phenomena. In particular, the proposed system accurately analyzes and provides regional atmospheric information based on environmental data measured locally and public big data, and predicts and presents future regional atmospheric information using artificial intelligence algorithms. Furthermore, through the proposed system, it is expected that local air pollution can be prevented by accurately identifying the cause of regional air pollution.
Keywords
Air pollution prediction; Air pollution monitoring; Air pollution big data; Artificial intelligence algorithm;
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