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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


Saifur Rahman

Abdullah S. Alwadie

Muhammed Irfan

Rabia Nawaz

Mohsin Raza

Ehtasham Javed

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Dr Muhammad Awais
Post Doctoral Research Fellow in Data Analytics and AI


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.

Journal Article Type Article
Publication Date 2020-06
Journal Micromachines
Publisher MDPI
Peer Reviewed Peer Reviewed
Volume 11
Issue 6
Pages 597
APA6 Citation Rahman, S., Alwadie, A. S., Irfan, M., Nawaz, R., Raza, M., Javed, E., & Awais, M. (2020). Wireless E-Nose Sensors to Detect Volatile Organic Gases through Multivariate Analysis. Micromachines, 11(6), 597.
Keywords Gas sensors; Principal components analysis; Multivariate analysis; Metal oxide semiconductor (MOS) sensors; Electronic; Detection; Electronic nose
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© 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 (

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