Environmental odor detection and classification with electronic nose system
Journal
Bulletin of Electrical Engineering and Informatics
ISSN
2089-3191
2302-9285
Publisher
Institute of Advanced Engineering and Science (IAES)
Date Issued
2025-04
Author(s)
Rafal Lizut
Paolo Visconti
Aimé Lay-Ekuakille
Type
Resource Types::text::journal::journal article
Abstract
A prototype of an electronic nose (e-nose) system integrating a set of general-purpose gas sensors, an electronic module, and signal processing and classification methods has been designed and implemented to detect certain environmental odors that might pose a risk to human health. The proposed device explores the filter diagonalization method (FDM), an advanced signal processing technique for accurate spectral estimation, to detect the presence of odors together with random forest (RF), a popular machine learning algorithm, to classify the features of such spectra. Experimental results show that the proposed FDM-RF approach can recognize the targeted odors with an accuracy of 96.4%.
License
Acceso Abierto
How to cite
Macías-Quijas, R., Velázquez, R., Del-Valle-Soto, C., Lizut, R., Visconti, P., & Lay-Ekuakille, A. (2025). Environmental odor detection and classification with electronic nose system. Bulletin Of Electrical Engineering And Informatics, 14(2), 1117-1125. https://doi.org/10.11591/eei.v14i2.9046
Table of contents
Abstract -- 1. Introduction -- 2. Methods -- 2.1.Prototype -- 2.2.Filter diagonalization method -- 2.3.Random forest -- 2.4.Experimentation -- 3. Results and discussion -- Conclusion.