In recent years, electronic noses (e-noses) have emerged as innovative tools for environmental monitoring, particularly in detecting air pollutants. This study presents the design and development of a functional, portable, and low-cost e-nose technology capable of identifying gases such as carbon monoxide, methane, and several volatile compounds. Such technology integrates a multi-sensor array and a data acquisition module, along with advanced signal processing algorithms. The Filter Diagonalization Method (FDM) is proposed for spectral feature extraction, combined with Random Forest (RF) for gas classification. Experimental results demonstrate a 96.4 % accuracy in gas identification, validating the effectiveness of the FDM-RF combination. This study contributes to the advancement of accessible air quality monitoring technologies and new gas detection and classification approaches.
Functional Electronic Nose Technology for Monitoring Air Gases
R. De Fazio;P. ViscontiPenultimo
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2025-01-01
Abstract
In recent years, electronic noses (e-noses) have emerged as innovative tools for environmental monitoring, particularly in detecting air pollutants. This study presents the design and development of a functional, portable, and low-cost e-nose technology capable of identifying gases such as carbon monoxide, methane, and several volatile compounds. Such technology integrates a multi-sensor array and a data acquisition module, along with advanced signal processing algorithms. The Filter Diagonalization Method (FDM) is proposed for spectral feature extraction, combined with Random Forest (RF) for gas classification. Experimental results demonstrate a 96.4 % accuracy in gas identification, validating the effectiveness of the FDM-RF combination. This study contributes to the advancement of accessible air quality monitoring technologies and new gas detection and classification approaches.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.
