Title :
An electronic nose for detection pollutant odorant and olfaction classification using neural network
Author :
Rabeb, Faleh ; Souhir, Bedoui ; Abdermaceur, Kachouri ; Mounir, Samet
Author_Institution :
Nat. Eng. Sch. of Sfax, Sfax Univ., Sfax, Tunisia
Abstract :
Degradation of air quality caused by human activity is a problem to be taken seriously because its consequences affect us directly, more or less long term. Electronic nose (e-nose), as a kind of new monitor, combines electronic measurements and intelligent pattern recognition technology and has advantages of real-time detection and easy operation. This paper presents the classification of different sample gases based on the dynamic responses of MOS based gas sensors using artificial neural network. Data classification was performed using supervised neural network classifiers; namely the Multi-Layer Perceptron (MLP) network.
Keywords :
air quality; electronic noses; environmental science computing; multilayer perceptrons; pattern classification; pollution measurement; MLP network; MOS based gas sensors; air quality degradation; artificial neural network; data classification; dynamic responses; e-nose; electronic measurements; electronic nose; intelligent pattern recognition technology; multilayer perceptron network; olfaction classification; pollutant odorant detection; real-time detection; sample gases classification; supervised neural network classifiers; Biological neural networks; Computers; Educational institutions; Electronic noses; Gas detectors; Gases; Neurons; e-nose; neural network; sensor of gas;
Conference_Titel :
Sciences and Techniques of Automatic Control and Computer Engineering (STA), 2013 14th International Conference on
Conference_Location :
Sousse
Print_ISBN :
978-1-4799-2953-5
DOI :
10.1109/STA.2013.6783126