An Artificial Neural Networks-Based on-Line Monitoring Odor Sensing System | Zendy

Yousif Abdullatif Albastaki | Zendy

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An Artificial Neural Networks-Based on-Line Monitoring Odor Sensing System

Author(s) -

Yousif Abdullatif Albastaki

Publication year - 2009

Publication title -

journal of computer science

Language(s) - English

Resource type - Journals

SCImago Journal Rank - 0.161

H-Index - 28

eISSN - 1552-6607

pISSN - 1549-3636

DOI - 10.3844/jcssp.2009.878.882

Subject(s) - computer science , artificial neural network , odor , artificial intelligence , line (geometry) , real time computing , machine learning , data mining , geometry , mathematics , neuroscience , biology

Problem statement: There have been many works for odor recognition using different sensor arrays and pattern recognition techniques in last decades. Approach: Although an odor is usually recorded utilizing language expression, it is too difficult for laymen to associate actual odor with that expression. Results: The odor sensing system should be extended to new areas since its standard style where the output pattern from multiple sensors with partially overlapped specificity is recognized by a neural network or multivariate analysis. Conclusion/Recommendations: In this study, we have developed odor sensing system with the capability of the discrimination among closely similar 20 different odor patterns and proposed an on-line classification method using a handheld odor meter (OMX-GR sensor) and neural network.

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