Wireless electronic nose system for real-time quantitative analysis of gas mixtures using micro-gas sensor array and neuro-fuzzy network

This paper presents a gas sensor array designed to be an electronic nose system characterized for the detection of different aromas (grape, apple, and strawberry).

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Development of polyaniline nanocomposite thin film micro-gas sensor array for the qualitative analysis of inorganic vapor

2009 International Conference on Apperceiving Computing and Intelligence Analysis ◽

10.1109/icacia.2009.5361166 ◽

2009 ◽

Author(s):

Hui-Ling Tai ◽

Ya-Dong Jiang ◽

Guang-Zhong Xie

Keyword(s):

Thin Film ◽

Qualitative Analysis ◽

Gas Sensor ◽

Sensor Array ◽

Nanocomposite Thin Film ◽

Gas Sensor Array ◽

Micro Gas Sensor ◽

Polyaniline Nanocomposite

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Room temperature ionic-liquid electrochemical gas sensor array system for real-time mine safety monitoring

2013 IEEE SENSORS ◽

10.1109/icsens.2013.6688143 ◽

2013 ◽

Cited By ~ 3

Author(s):

Haitao Li ◽

Xiaoyi Mu ◽

Zhe Wang ◽

Min Guo ◽

Xiangqun Zeng ◽

...

Keyword(s):

Ionic Liquid ◽

Real Time ◽

Gas Sensor ◽

Room Temperature ◽

Sensor Array ◽

Safety Monitoring ◽

Room Temperature Ionic Liquid ◽

Mine Safety ◽

Gas Sensor Array

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Application of Electronic Nose for Evaluation of Wastewater Treatment Process Effects at Full-Scale WWTP

Processes ◽

10.3390/pr7050251 ◽

2019 ◽

Vol 7 (5) ◽

pp. 251 ◽

Cited By ~ 8

Author(s):

Grzegorz Łagód ◽

Sylwia M. Duda ◽

Dariusz Majerek ◽

Adriana Szutt ◽

Agnieszka Dołhańczuk-Śródka

Keyword(s):

Wastewater Treatment ◽

Gas Sensor ◽

Electronic Nose ◽

Sensor Array ◽

Treatment Plant ◽

Full Scale ◽

Oxide Semiconductor ◽

Pollution Level ◽

Gas Sensor Array

This paper presents the results of studies aiming at the assessment and classification of wastewater using an electronic nose. During the experiment, an attempt was made to classify the medium based on an analysis of signals from a gas sensor array, the intensity of which depended on the levels of volatile compounds in the headspace gas mixture above the wastewater table. The research involved samples collected from the mechanical and biological treatment devices of a full-scale wastewater treatment plant (WWTP), as well as wastewater analysis. The measurements were carried out with a metal-oxide-semiconductor (MOS) gas sensor array, when coupled with a computing unit (e.g., a computer with suitable software for the analysis of signals and their interpretation), it formed an e-nose—that is, an imitation of the mammalian olfactory sense. While conducting the research it was observed that the intensity of signals sent by sensors changed with drops in the level of wastewater pollution; thus, the samples could be classified in terms of their similarity and the analyzed gas-fingerprint could be related to the pollution level expressed by physical and biochemical indicators. Principal component analysis was employed for dimensionality reduction, and cluster analysis for grouping observation purposes. Supervised learning techniques confirmed that the obtained data were applicable for the classification of wastewater at different stages of the purification process.

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