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An Azure ACES Early Warning System for Air Quality Index Deteriorating

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...

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Detalles Bibliográficos
Autores principales: Shih, Dong-Her, Wu, Ting-Wei, Liu, Wen-Xuan, Shih, Po-Yuan
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2019
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6926579/
https://www.ncbi.nlm.nih.gov/pubmed/31771273
http://dx.doi.org/10.3390/ijerph16234679
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author Shih, Dong-Her
Wu, Ting-Wei
Liu, Wen-Xuan
Shih, Po-Yuan
author_facet Shih, Dong-Her
Wu, Ting-Wei
Liu, Wen-Xuan
Shih, Po-Yuan
author_sort Shih, Dong-Her
collection PubMed
description 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.
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spelling pubmed-69265792019-12-24 An Azure ACES Early Warning System for Air Quality Index Deteriorating Shih, Dong-Her Wu, Ting-Wei Liu, Wen-Xuan Shih, Po-Yuan Int J Environ Res Public Health Article 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. MDPI 2019-11-24 2019-12 /pmc/articles/PMC6926579/ /pubmed/31771273 http://dx.doi.org/10.3390/ijerph16234679 Text en © 2019 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/).
spellingShingle Article
Shih, Dong-Her
Wu, Ting-Wei
Liu, Wen-Xuan
Shih, Po-Yuan
An Azure ACES Early Warning System for Air Quality Index Deteriorating
title An Azure ACES Early Warning System for Air Quality Index Deteriorating
title_full An Azure ACES Early Warning System for Air Quality Index Deteriorating
title_fullStr An Azure ACES Early Warning System for Air Quality Index Deteriorating
title_full_unstemmed An Azure ACES Early Warning System for Air Quality Index Deteriorating
title_short An Azure ACES Early Warning System for Air Quality Index Deteriorating
title_sort azure aces early warning system for air quality index deteriorating
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6926579/
https://www.ncbi.nlm.nih.gov/pubmed/31771273
http://dx.doi.org/10.3390/ijerph16234679
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