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An Azure ACES Early Warning System for Air Quality Index Deteriorating

Author

Listed:
  • Dong-Her Shih

    (Department of Information Management, National Yunlin University of Science and Technology, 123, Section 3, University Road, Douliu 640, Taiwan)

  • Ting-Wei Wu

    (Department of Information Management, National Yunlin University of Science and Technology, 123, Section 3, University Road, Douliu 640, Taiwan)

  • Wen-Xuan Liu

    (Department of Information Management, National Yunlin University of Science and Technology, 123, Section 3, University Road, Douliu 640, Taiwan)

  • Po-Yuan Shih

    (Department of Finance, National Yunlin University of Science and Technology, 123, Section 3, University Road, Douliu 640, Taiwan)

Abstract

With the development of industrialization and urbanization, air pollution in many countries has become more serious and has affected people’s health. The air quality has been continuously concerned by environmental managers and the public. Therefore, accurate air quality deterioration warning system can avoid health hazards. In this study, an air quality index (AQI) warning system based on Azure cloud computing platform is proposed. The prediction model is based on DFR (Decision Forest Regression), NNR (Neural Network Regression), and LR (Linear Regression) machine learning algorithms. The best algorithm was selected to calculate the 6 pollutants required for the AQI calculation of the air quality monitoring in real time. The experimental results show that the LR algorithm has the best performance, and the method of this study has a good prediction on the AQI index warning for the next one to three hours. Based on the ACES system proposed, it is hoped that it can prevent personal health hazards and help to reduce medical costs in public.

Suggested Citation

  • Dong-Her Shih & Ting-Wei Wu & Wen-Xuan Liu & Po-Yuan Shih, 2019. "An Azure ACES Early Warning System for Air Quality Index Deteriorating," IJERPH, MDPI, vol. 16(23), pages 1-23, November.
    • Handle: RePEc:gam:jijerp:v:16:y:2019:i:23:p:4679-:d:290398
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    References listed on IDEAS

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    1. Lichter, Andreas & Pestel, Nico & Sommer, Eric, 2017. "Productivity effects of air pollution: Evidence from professional soccer," Labour Economics, Elsevier, vol. 48(C), pages 54-66.
    2. Saberian, Soodeh & Heyes, Anthony & Rivers, Nicholas, 2017. "Alerts work! Air quality warnings and cycling," Resource and Energy Economics, Elsevier, vol. 49(C), pages 165-185.
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    Cited by:

    1. Xiaobing Yu & Chenliang Li & Hong Chen & Zhonghui Ji, 2020. "Evaluate Air Pollution by Promethee Ranking in Yangtze River Delta of China," IJERPH, MDPI, vol. 17(2), pages 1-18, January.

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