Odor detection using an e-nose with a reduced sensor array
Piotr Borowik , Leszek Adamowicz , Rafał Tarakowski , Krzysztof Siwek , Tomasz Grzywacz
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.
|Journal series||Sensors, [SENSORS-BASEL], ISSN 1424-8220, e-ISSN 1424-3210|
|Publication size in sheets||0.95|
|Keywords in English||electronic nose; features selection; odor classification; sensor array reduction; wine spoilage|
|ASJC Classification||; ; ;|
|License||Journal (articles only); author's original; ; after publication|
|Score||= 100.0, 22-07-2020, ArticleFromJournal|
|Publication indicators||= 0; : 2016 = 1.393; : 2018 = 3.031 (2) - 2018=3.302 (5)|
* presented citation count is obtained through Internet information analysis and it is close to the number calculated by the Publish or Perish system.