Environmental odor detection and classification with electronic nose system

Ricardo Macías-Quijas, Ramiro Velázquez, Carolina Del-Valle-Soto, Rafal Lizut, Paolo Visconti, Aimé Lay-Ekuakille

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%.


Keywords


Electronic nose; Filter diagonalization method; Odor recognition; Random forest; Spectral footprint

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DOI: https://doi.org/10.11591/eei.v14i2.9046

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Bulletin of EEI Stats

Bulletin of Electrical Engineering and Informatics (BEEI)
ISSN: 2089-3191, e-ISSN: 2302-9285
This journal is published by the Institute of Advanced Engineering and Science (IAES) in collaboration with Intelektual Pustaka Media Utama (IPMU).