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Reliable e-nose for air toxicity monitoring by filter diagonalization method

Ricardo Macías-Quijas, Ramiro Velázquez, Roberto De Fazio, Paolo Visconti, Nicola Ivan Giannoccaro, A. Lay-Ekuakille

Year
2022
Citations
4
Access
Open access

Abstract

This paper introduces a compact, affordable electronic nose (e-nose) device devoted to detect the presence of toxic compounds that could affect human health, such as carbon monoxide, combustible gas, hydrogen, methane, and smoke, among others. Such artificial olfaction device consists of an array of six metal oxide semiconductor (MOS) sensors and a computer-based information system for signal acquisition, processing, and visualization. This study further proposes the use of the filter diagonalization method (FDM) to extract the spectral contents of the signals obtained from the sensors. Preliminary results show that the prototype is functional and that the FDM approach is suitable for a later classification stage. Example deployment scenarios of the proposed e-nose include indoor facilities (buildings and warehouses), compromised air quality places (mines and sanitary landfills), public transportation, mobile robots, and wireless sensor networks.

Keywords

Computer scienceElectronic noseSoftware deploymentModular designWireless sensor networkFilter (signal processing)Environmental scienceReal-time computingArtificial intelligenceComputer vision

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