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Wireless E-Nose Sensors to Detect Volatile Organic Gases through Multivariate Analysis

Gas sensors are critical components when adhering to health safety and environmental policies in various manufacturing industries, such as the petroleum and oil industry; scent and makeup production; food and beverage manufacturing; chemical engineering; pollution monitoring. In recent times, gas se...

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Autores principales: Rahman, Saifur, Alwadie, Abdullah S., Irfan, Muhammed, Nawaz, Rabia, Raza, Mohsin, Javed, Ehtasham, Awais, Muhammad
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7345365/
https://www.ncbi.nlm.nih.gov/pubmed/32570813
http://dx.doi.org/10.3390/mi11060597
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author Rahman, Saifur
Alwadie, Abdullah S.
Irfan, Muhammed
Nawaz, Rabia
Raza, Mohsin
Javed, Ehtasham
Awais, Muhammad
author_facet Rahman, Saifur
Alwadie, Abdullah S.
Irfan, Muhammed
Nawaz, Rabia
Raza, Mohsin
Javed, Ehtasham
Awais, Muhammad
author_sort Rahman, Saifur
collection PubMed
description Gas sensors are critical components when adhering to health safety and environmental policies in various manufacturing industries, such as the petroleum and oil industry; scent and makeup production; food and beverage manufacturing; chemical engineering; pollution monitoring. In recent times, gas sensors have been introduced to medical diagnostics, bioprocesses, and plant disease diagnosis processes. There could be an adverse impact on human health due to the mixture of various gases (e.g., acetone (A), ethanol (E), propane (P)) that vent out from industrial areas. Therefore, it is important to accurately detect and differentiate such gases. Towards this goal, this paper presents a novel electronic nose (e-nose) detection method to classify various explosive gases. To detect explosive gases, metal oxide semiconductor (MOS) sensors are used as reliable tools to detect such volatile gases. The data received from MOS sensors are processed through a multivariate analysis technique to classify different categories of gases. Multivariate analysis was done using three variants—differential, relative, and fractional analyses—in principal components analysis (PCA). The MOS sensors also have three different designs: loading design, notch design, and Bi design. The proposed MOS sensor-based e-nose accurately detects and classifies three different gases, which indicates the reliability and practicality of the developed system. The developed system enables discrimination of these gases from the mixture. Based on the results from the proposed system, authorities can take preventive measures to deal with these gases to avoid their potential adverse impacts on employee health.
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spelling pubmed-73453652020-07-09 Wireless E-Nose Sensors to Detect Volatile Organic Gases through Multivariate Analysis Rahman, Saifur Alwadie, Abdullah S. Irfan, Muhammed Nawaz, Rabia Raza, Mohsin Javed, Ehtasham Awais, Muhammad Micromachines (Basel) Article Gas sensors are critical components when adhering to health safety and environmental policies in various manufacturing industries, such as the petroleum and oil industry; scent and makeup production; food and beverage manufacturing; chemical engineering; pollution monitoring. In recent times, gas sensors have been introduced to medical diagnostics, bioprocesses, and plant disease diagnosis processes. There could be an adverse impact on human health due to the mixture of various gases (e.g., acetone (A), ethanol (E), propane (P)) that vent out from industrial areas. Therefore, it is important to accurately detect and differentiate such gases. Towards this goal, this paper presents a novel electronic nose (e-nose) detection method to classify various explosive gases. To detect explosive gases, metal oxide semiconductor (MOS) sensors are used as reliable tools to detect such volatile gases. The data received from MOS sensors are processed through a multivariate analysis technique to classify different categories of gases. Multivariate analysis was done using three variants—differential, relative, and fractional analyses—in principal components analysis (PCA). The MOS sensors also have three different designs: loading design, notch design, and Bi design. The proposed MOS sensor-based e-nose accurately detects and classifies three different gases, which indicates the reliability and practicality of the developed system. The developed system enables discrimination of these gases from the mixture. Based on the results from the proposed system, authorities can take preventive measures to deal with these gases to avoid their potential adverse impacts on employee health. MDPI 2020-06-18 /pmc/articles/PMC7345365/ /pubmed/32570813 http://dx.doi.org/10.3390/mi11060597 Text en © 2020 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
Rahman, Saifur
Alwadie, Abdullah S.
Irfan, Muhammed
Nawaz, Rabia
Raza, Mohsin
Javed, Ehtasham
Awais, Muhammad
Wireless E-Nose Sensors to Detect Volatile Organic Gases through Multivariate Analysis
title Wireless E-Nose Sensors to Detect Volatile Organic Gases through Multivariate Analysis
title_full Wireless E-Nose Sensors to Detect Volatile Organic Gases through Multivariate Analysis
title_fullStr Wireless E-Nose Sensors to Detect Volatile Organic Gases through Multivariate Analysis
title_full_unstemmed Wireless E-Nose Sensors to Detect Volatile Organic Gases through Multivariate Analysis
title_short Wireless E-Nose Sensors to Detect Volatile Organic Gases through Multivariate Analysis
title_sort wireless e-nose sensors to detect volatile organic gases through multivariate analysis
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7345365/
https://www.ncbi.nlm.nih.gov/pubmed/32570813
http://dx.doi.org/10.3390/mi11060597
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