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Reliable e-nose for air toxicity monitoring by filter diagonalization method

International Journal of Electrical and Computer Engineering (IJECE) · Vol. 12 No. 2 (2022)

DOI
10.11591/ijece.v12i2.pp1286-1298
ISSN
2722-2578, 2088-8708
Published
2022-04-01
Publisher
Institute of Advanced Engineering and Science
License
creativecommons.org/licenses/by-sa/4.0

Abstract

This paper introduces a compact, affordable electronic nose (e-nose) device devoted to detect the presence of toxic compounds that could affect human health, such as carbon monoxide, combustible gas, hydrogen, methane, and smoke, among others. Such artificial olfaction device consists of an array of six metal oxide semiconductor (MOS) sensors and a computer-based information system for signal acquisition, processing, and visualization. This study further proposes the use of the filter diagonalization method (FDM) to extract the spectral contents of the signals obtained from the sensors. Preliminary results show that the prototype is functional and that the FDM approach is suitable for a later classification stage. Example deployment scenarios of the proposed e-nose include indoor facilities (buildings and warehouses), compromised air quality places (mines and sanitary landfills), public transportation, mobile robots, and wireless sensor networks.

Collaboration network of the authors

12 authors · 35 co-authorship links · 23 across different organisations

Hover or tap a name to highlight its co-authors. Double-click to open the author's page.

  • University of Salento
  • Universidad Panamericana
  • Hashemite University
  • Isra University
  • Yarmouk University
  • Different organisations
  • Same organisation
  • Affiliation unknown
  • Thicker line = more joint articles · bigger circle = more articles
Show as table
Co-authorOrganisationJoint articles
Stefano CapocciaUniversity of Salento3
Marzia LuceriUniversity of Salento3
Bassam O. Al-NaamiHashemite University2
Yahia Z. RawashHashemite University2
Abdel-Razzak M. Al-hinnawiIsra University2
Awad Al‐ZabenYarmouk University2

Affiliations come from OpenAlex; journal OAI-PMH metadata carries none. Authors without an OpenAlex ID are matched by name, which can merge or split people.

This record comes from Crossref (what the publisher deposited), because the journal's own OAI-PMH endpoint could not be harvested.

Metadata source: Crossref API (cadangan, berdasarkan ISSN) https://api.crossref.org/journals/2088-8708/works, first harvested 27 Okt 2026, last seen 27 Okt 2026.
Metadata as oai_dc, converted from Crossref
<oai_dc:dc xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:oai_dc="http://www.openarchives.org/OAI/2.0/oai_dc/"><dc:title>Reliable e-nose for air toxicity monitoring by filter diagonalization method</dc:title><dc:creator>Macías-Quijas, Ricardo</dc:creator><dc:creator>Velázquez, Ramiro</dc:creator><dc:creator>Fazio, Roberto De</dc:creator><dc:creator>Visconti, Paolo</dc:creator><dc:creator>Giannoccaro, Nicola Ivan</dc:creator><dc:creator>Lay-Ekuakille, Aimé</dc:creator><dc:description>&lt;jats:p&gt;This paper introduces a compact, affordable electronic nose (e-nose) device devoted to detect the presence of toxic compounds that could affect human health, such as carbon monoxide, combustible gas, hydrogen, methane, and smoke, among others. Such artificial olfaction device consists of an array of six metal oxide semiconductor (MOS) sensors and a computer-based information system for signal acquisition, processing, and visualization. This study further proposes the use of the filter diagonalization method (FDM) to extract the spectral contents of the signals obtained from the sensors. Preliminary results show that the prototype is functional and that the FDM approach is suitable for a later classification stage. Example deployment scenarios of the proposed e-nose include indoor facilities (buildings and warehouses), compromised air quality places (mines and sanitary landfills), public transportation, mobile robots, and wireless sensor networks.&lt;/jats:p&gt;</dc:description><dc:publisher>Institute of Advanced Engineering and Science</dc:publisher><dc:date>2022-04-01</dc:date><dc:type>info:eu-repo/semantics/article</dc:type><dc:format>application/pdf</dc:format><dc:identifier>https://doi.org/10.11591/ijece.v12i2.pp1286-1298</dc:identifier><dc:identifier>10.11591/ijece.v12i2.pp1286-1298</dc:identifier><dc:source>International Journal of Electrical and Computer Engineering (IJECE); Vol 12 No 2 (2022); 1286</dc:source><dc:source>2722-2578</dc:source><dc:source>2088-8708</dc:source><dc:relation>http://ijece.iaescore.com/index.php/IJECE/article/viewFile/25951/15471</dc:relation><dc:rights>http://creativecommons.org/licenses/by-sa/4.0</dc:rights></oai_dc:dc>