Odor detection using an e-nose with a reduced sensor array

Piotr Borowik , Leszek Adamowicz , Rafał Tarakowski , Krzysztof Siwek , Tomasz Grzywacz

Abstract

Recent advances in the field of electronic noses (e-noses) have led to new developments in both sensors and feature extraction as well as data processing techniques, providing an increased amount of information. Therefore, feature selection has become essential in the development of e-nose applications. Sophisticated computation techniques can be applied for solving the old problem of sensor number optimization and feature selections. In this way, one can find an optimal application-specific sensor array and reduce the potential cost associated with designing new e-nose devices. In this paper, we examine a procedure to extract and select modeling features for optimal e-nose performance. The usefulness of this approach is demonstrated in detail. We calculated the model’s performance using cross-validation with the standard leave-one-group-out and group shuffle validation methods. Our analysis of wine spoilage data from the sensor array shows when a transient sensor response is considered, both from gas adsorption and desorption phases, it is possible to obtain a reasonable level of odor detection even with data coming from a single sensor. This requires adequate extraction of modeling features and then selection of features used in the final model.

Author Piotr Borowik (WUT)
Piotr Borowik,,
- Warsaw University of Technology
, Leszek Adamowicz (FP / SRD)
Leszek Adamowicz,,
- Structural Research Division
, Rafał Tarakowski (FP / SRD)
Rafał Tarakowski,,
- Structural Research Division
, Krzysztof Siwek (FoEE / ITEEMIS)
Krzysztof Siwek,,
- The Institute of the Theory of Electrical Engineering, Measurement and Information Systems
, Tomasz Grzywacz (FoEE / ITEEMIS)
Tomasz Grzywacz,,
- The Institute of the Theory of Electrical Engineering, Measurement and Information Systems
Journal seriesSensors, [SENSORS-BASEL], ISSN 1424-8220, e-ISSN 1424-3210
Issue year2020
Vol20
Pages1-20
Publication size in sheets0.95
Keywords in Englishelectronic nose; features selection; odor classification; sensor array reduction; wine spoilage
ASJC Classification1303 Biochemistry; 1602 Analytical Chemistry; 2208 Electrical and Electronic Engineering; 3107 Atomic and Molecular Physics, and Optics
DOIDOI:10.3390/s20123542
Languageen angielski
LicenseJournal (articles only); author's original; Uznanie Autorstwa (CC-BY); after publication
File
WUT0c424e891d084f4993491075ef73fa9a.pdf 1.56 MB
Score (nominal)100
Score sourcejournalList
ScoreMinisterial score = 100.0, 22-07-2020, ArticleFromJournal
Publication indicators Scopus Citations = 0; Scopus SNIP (Source Normalised Impact per Paper): 2016 = 1.393; WoS Impact Factor: 2018 = 3.031 (2) - 2018=3.302 (5)
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