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Air Quality Monitoring for Vulnerable Groups in Residential Environments Using a Multiple Hazard Gas Detector
This paper presents a smart “e-nose” device to monitor indoor hazardous air. Indoor hazardous odor is a threat for seniors, infants, children, pregnant women, disabled residents, and patients. To overcome the limitations of using existing non-intelligent, slow-responding, deficient gas sensors, we p...
Autores principales: | , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2019
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6359352/ https://www.ncbi.nlm.nih.gov/pubmed/30658412 http://dx.doi.org/10.3390/s19020362 |
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author | Wu, Yujiao Liu, Taoping Ling, Sai Ho Szymanski, Jan Zhang, Wentian Su, Steven Weidong |
author_facet | Wu, Yujiao Liu, Taoping Ling, Sai Ho Szymanski, Jan Zhang, Wentian Su, Steven Weidong |
author_sort | Wu, Yujiao |
collection | PubMed |
description | This paper presents a smart “e-nose” device to monitor indoor hazardous air. Indoor hazardous odor is a threat for seniors, infants, children, pregnant women, disabled residents, and patients. To overcome the limitations of using existing non-intelligent, slow-responding, deficient gas sensors, we propose a novel artificial-intelligent-based multiple hazard gas detector (MHGD) system that is mounted on a motor vehicle-based robot which can be remotely controlled. First, we optimized the sensor array for the classification of three hazardous gases, including cigarette smoke, inflammable ethanol, and off-flavor from spoiled food, using an e-nose with a mixing chamber. The mixing chamber can prevent the impact of environmental changes. We compared the classification results of all combinations of sensors, and selected the one with the highest accuracy (98.88%) as the optimal sensor array for the MHGD. The optimal sensor array was then mounted on the MHGD to detect and classify the target gases without a mixing chamber but in a controlled environment. Finally, we tested the MHGD under these conditions, and achieved an acceptable accuracy (70.00%). |
format | Online Article Text |
id | pubmed-6359352 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2019 |
publisher | MDPI |
record_format | MEDLINE/PubMed |
spelling | pubmed-63593522019-02-06 Air Quality Monitoring for Vulnerable Groups in Residential Environments Using a Multiple Hazard Gas Detector Wu, Yujiao Liu, Taoping Ling, Sai Ho Szymanski, Jan Zhang, Wentian Su, Steven Weidong Sensors (Basel) Article This paper presents a smart “e-nose” device to monitor indoor hazardous air. Indoor hazardous odor is a threat for seniors, infants, children, pregnant women, disabled residents, and patients. To overcome the limitations of using existing non-intelligent, slow-responding, deficient gas sensors, we propose a novel artificial-intelligent-based multiple hazard gas detector (MHGD) system that is mounted on a motor vehicle-based robot which can be remotely controlled. First, we optimized the sensor array for the classification of three hazardous gases, including cigarette smoke, inflammable ethanol, and off-flavor from spoiled food, using an e-nose with a mixing chamber. The mixing chamber can prevent the impact of environmental changes. We compared the classification results of all combinations of sensors, and selected the one with the highest accuracy (98.88%) as the optimal sensor array for the MHGD. The optimal sensor array was then mounted on the MHGD to detect and classify the target gases without a mixing chamber but in a controlled environment. Finally, we tested the MHGD under these conditions, and achieved an acceptable accuracy (70.00%). MDPI 2019-01-17 /pmc/articles/PMC6359352/ /pubmed/30658412 http://dx.doi.org/10.3390/s19020362 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 Wu, Yujiao Liu, Taoping Ling, Sai Ho Szymanski, Jan Zhang, Wentian Su, Steven Weidong Air Quality Monitoring for Vulnerable Groups in Residential Environments Using a Multiple Hazard Gas Detector |
title | Air Quality Monitoring for Vulnerable Groups in Residential Environments Using a Multiple Hazard Gas Detector |
title_full | Air Quality Monitoring for Vulnerable Groups in Residential Environments Using a Multiple Hazard Gas Detector |
title_fullStr | Air Quality Monitoring for Vulnerable Groups in Residential Environments Using a Multiple Hazard Gas Detector |
title_full_unstemmed | Air Quality Monitoring for Vulnerable Groups in Residential Environments Using a Multiple Hazard Gas Detector |
title_short | Air Quality Monitoring for Vulnerable Groups in Residential Environments Using a Multiple Hazard Gas Detector |
title_sort | air quality monitoring for vulnerable groups in residential environments using a multiple hazard gas detector |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6359352/ https://www.ncbi.nlm.nih.gov/pubmed/30658412 http://dx.doi.org/10.3390/s19020362 |
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