Design and Construction of an Odour Sensor for Various Biomedical Applications

Kumar, P.Y.; Ganesh, T.S.

doi:10.1109/indcon.2005.1590112

Cited by 3 publications

(1 citation statement)

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“…Recently, gas sensing, as a typical application in intelligent systems, is receiving increasing attention in both industry and academia. Gas sensing technology has become more significant because of its widespread and common applications in the following areas: (1) industrial production (e.g., methane detection in mines) ; (2) automotive industry (e.g., detection of polluting gases from vehicles) [29][30][31][32][33][34][35][36][37][38][39][40][41][42][43]; (3) medical applications (e.g., electronic noses simulating the human olfactory system) [44][45][46][47][48][49][50][51][52][53][54][55][56][57][58][59][60]; (4) indoor air quality supervision (e.g., detection of carbon monoxide) [61][62][63][64][65][66][67][68][69][70][71][...…”

Section: Introductionmentioning

confidence: 99%

A Survey on Gas Sensing Technology

Liu

Cheng

Hong

et al. 2012

Sensors

1,239

688

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Sensing technology has been widely investigated and utilized for gas detection. Due to the different applicability and inherent limitations of different gas sensing technologies, researchers have been working on different scenarios with enhanced gas sensor calibration. This paper reviews the descriptions, evaluation, comparison and recent developments in existing gas sensing technologies. A classification of sensing technologies is given, based on the variation of electrical and other properties. Detailed introduction to sensing methods based on electrical variation is discussed through further classification according to sensing materials, including metal oxide semiconductors, polymers, carbon nanotubes, and moisture absorbing materials. Methods based on other kinds of variations such as optical, calorimetric, acoustic and gas-chromatographic, are presented in a general way. Several suggestions related to future development are also discussed. Furthermore, this paper focuses on sensitivity and selectivity for performance indicators to compare different sensing technologies, analyzes the factors that influence these two indicators, and lists several corresponding improved approaches.

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