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Rahman, Saifur, Alwadie, Abdullah S., Irfan, Muhammad, Nawaz, Rabia, Raza, Mohsin, Javed, Ehtasham and Awais, Muhammad 
ORCID: https://orcid.org/0000-0001-6421-9245
(2020)
Wireless e-nose sensors to detect volatile organic gases through multivariate analysis.
Micromachines, 11 (6).
ISSN 2072-666X
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Abstract
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.
| Item Type: | Article |
|---|---|
| Additional Information: | Funding Information: Funding: This research was funded by the Deanship of Scientific Research, Najran University, Kingdom of Saudi Arabia, for the award of research fund NU/ESCI/16/046. Funding Information: Acknowledgments: The authors would like to express their gratitude to the Ministry of Education and the Deanship of Scientific Research, Najran University. Kingdom of Saudi Arabia, for their financial and technical support under code number NU/ESCI/16/046. Publisher Copyright: © 2020 by the authors. |
| Uncontrolled Keywords: | detection,electronic,electronic nose,gas sensors,metal oxide semiconductor (mos) sensors,multivariate analysis,principal components analysis,mechanical engineering,electrical and electronic engineering,control and systems engineering,sdg 3 - good health and well-being ,/dk/atira/pure/subjectarea/asjc/2200/2210 |
| Faculty \ School: | Faculty of Science > School of Computing Sciences |
| Related URLs: | |
| Depositing User: | LivePure Connector |
| Date Deposited: | 17 Oct 2023 00:45 |
| Last Modified: | 24 Oct 2023 01:43 |
| URI: | https://ueaeprints.uea.ac.uk/id/eprint/93310 |
| DOI: | 10.3390/mi11060597 |
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