2010
DOI: 10.1016/j.snb.2009.12.027
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Long term stability of metal oxide-based gas sensors for e-nose environmental applications: An overview

Abstract: Abstract. The e-nose technology has enormous potentialities for in site monitoring of malodors. However a number of limitations are associated with the properties of chemical sensors, the performances of the signal processing and the realistic operation conditions of environmental field. From the experience of the research group in the field, the metal oxide based gas sensors (Figaro type) are until now the best chemical sensors for long term application, more than one year of continuous working in the field. … Show more

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Cited by 270 publications
(93 citation statements)
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References 24 publications
(7 reference statements)
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“…For environmental monitoring, the e-nose is able to monitor gas emissions in real time in the field and to link them to the odour concentration expressed in odour units [9].…”
Section: Measurements and Methodsmentioning
confidence: 99%
“…For environmental monitoring, the e-nose is able to monitor gas emissions in real time in the field and to link them to the odour concentration expressed in odour units [9].…”
Section: Measurements and Methodsmentioning
confidence: 99%
“…Using the feature set instead of the original signal allows for fast and compact data analysis. The obtained data is modeled using a simple physical description of the measurement system based on the following assumptions (Rodriguez et al, 2010;RagazzoSancheza et al, 2009;Brudzewski and Ulaczyk, 2009;Men et al, 2010;Romain and Nicolas, 2010;Bahraminejad et al, 2010;Flueckiger et al, 2009;Baha and Dibi, 2009):…”
Section: Discusionmentioning
confidence: 99%
“…Gas sensor baseline drift consists of a random temporal variation of the sensor response when it is exposed to the same analyte under identical conditions. Romain et al 4 tested and observed two identical sensor arrays for a long term, and found that structural and phase transformations, poisoning, interference e®ects, air humidity and temperature variations, surface and bulk properties changes were the main reasons for sensor baseline drift.…”
Section: Introductionmentioning
confidence: 99%