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Open AccessArticle

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

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Electrical Engineering Department, College of Engineering, Najran University, Najran 61441, Saudi Arabia
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Department of Physics, COMSATS University, Park Road, Chak Shahzad Islamabad 45550, Pakistan
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Department of Computer and Information Sciences, Northumbria University, Newcastle upon Tyne NE1 8ST, UK
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Helsinki Institute for Life Sciences, Neuroscience Center, University of Helsinki, 00014 Helsinki, Finland
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Energy and Environment Institute, Faculty of Science and Engineering, University of Hull, Hull 7RX, UK
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Authors to whom correspondence should be addressed.
Micromachines 2020, 11(6), 597; https://doi.org/10.3390/mi11060597
Received: 16 May 2020 / Revised: 16 June 2020 / Accepted: 16 June 2020 / Published: 18 June 2020
(This article belongs to the Special Issue Future Wearable and Implants)
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. View Full-Text
Keywords: gas sensors; principal components analysis; multivariate analysis; metal oxide semiconductor (MOS) sensors; electronic; detection; electronic nose gas sensors; principal components analysis; multivariate analysis; metal oxide semiconductor (MOS) sensors; electronic; detection; electronic nose
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Rahman, S.; Alwadie, A.S.; Irfan, M.; Nawaz, R.; Raza, M.; Javed, E.; Awais, M. Wireless E-Nose Sensors to Detect Volatile Organic Gases through Multivariate Analysis. Micromachines 2020, 11, 597.

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