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Multiple Odor Recognition and Source Direction Estimation with an Electronic Nose System
Author(s) -
Hyeong-Joon Kwon,
Dong-Gyu Kim,
KwangSeok Hong
Publication year - 2013
Publication title -
international journal of distributed sensor networks
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.324
H-Index - 53
eISSN - 1550-1477
pISSN - 1550-1329
DOI - 10.1155/2013/361378
Subject(s) - computer science , odor , electronic nose , sensor array , artificial intelligence , computer vision , pattern recognition (psychology) , channel (broadcasting) , signal (programming language) , telecommunications , machine learning , neuroscience , biology , programming language
We propose an electronic nose system that can perform real time direction estimation of an odor source and multiple odors recognition based on a stereo sensor array for extensive use in mobile environments. The proposed system consists of the following: (1) a method to obtain odor signals using a twin-sensor array, which consists of 16-channel metal oxide semiconductor sensors; (2) a method to estimate the direction of an odor source by analyzing the signal amplitude of each channel in the stereo sensor array; and (3) a method to recognize two odors simultaneously using a hierarchical elimination method. We determine the accuracy of the direction estimation of odor sources and the odor recognition rate in order to verify the performance of the multiple odors recognition method. As a result, we confirm the high estimation performance of the model for the front three-way directions, with a recognition rate of approximately two odors simultaneously.

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