Pattern Recognition for Selective Odor Detection with Gas Sensor Arrays

This paper presents a new pattern recognition approach for enhancing the selectivity of gas sensor arrays for clustering intelligent odor detection. The aim of this approach was to accurately classify an odor using pattern recognition in order to enhance the selectivity of gas sensor arrays. This was achieved using an odor monitoring system with a newly developed neural-genetic classification algorithm (NGCA). The system shows the enhancement in the sensitivity of the detected gas. Experiments showed that the proposed NGCA delivered better performance than the previous genetic algorithm (GA) and artificial neural networks (ANN) methods. We also used PCA for data visualization. Our proposed system can enhance the reproducibility, reliability, and selectivity of odor sensor output, so it is expected to be applicable to diverse environmental problems including air pollution, and monitor the air quality of clean-air required buildings such as a kindergartens and hospitals.

[1]  Ramón Huerta,et al.  A unified framework for Volatile Organic Compound classification and regression , 2010, The 2010 International Joint Conference on Neural Networks (IJCNN).

[2]  Shankar Vembu,et al.  On time series features and kernels for machine olfaction , 2012 .

[3]  M. Siegel.  Olfaction metal oxide semiconductor gas sensors and neural networks , 1990 .

[4]  José Pedro Santos,et al.  Analysis of neural networks and analysis of feature selection with genetic algorithm to discriminate among pollutant gas , 2004 .

[5]  Youngjin Choi,et al.  Synthesis of SnO2 nanowires and their gas sensing characteristics , 2006 .

[6]  Francesco Tortorella,et al.  Classification of food, beverages and perfumes by WO3 thin-film sensors array and pattern recognition techniques , 2001 .

[7]  Raktim Pal,et al.  Performance test of portable analyzers for total hydrocarbons (THC) through a cross-calibration against gas chromatograph , 2008 .

[8]  Nikolai F. Rulkov,et al.  Acceleration of chemo-sensory information processing using transient features , 2009 .

[9]  J W Gardner and P N Bartlett,et al.  Electronic Noses: Principles and Applications , 1999 .

[10]  Gian Carlo Cardinali,et al.  An electronic nose based on solid state sensor arrays for low-cost indoor air quality monitoring applications , 2004 .

[11]  Jing Gao,et al.  Applies of Neural Networks to Identify Gases Based on Electronic Nose , 2007, 2007 IEEE International Conference on Control and Automation.

[12]  Joseph R. Stetter,et al.  Detection and discrimination of coliform bacteria with gas sensor arrays , 2000 .

[13]  André Maisonnat,et al.  Nanosized tin oxide sensitive layer on a silicon platform for domestic gas applications , 2001 .

[14]  N. Yamazoe,et al.  Oxide Semiconductor Gas Sensors , 2003 .

[15]  Duk-Dong Lee,et al.  Pattern recognition of gas sensor array using characteristics of impedance , 2001 .

[16]  C. Hagleitner,et al.  Smart single-chip gas sensor microsystem , 2001, Nature.

[17]  Claude Delpha,et al.  An electronic nose for the discrimination of forane 134a and carbon dioxide in a humidity controlled atmosphere , 2001 .

[18]  Anne-Claude Romain,et al.  Erratum to “Monitoring the exhaust air of a compost pile as a process variable with an e-nose” [Sens. Actuators B: Chem., 2005, 106(1), 29–35] , 2006 .

[19]  Kea-Tiong Tang,et al.  A review of sensor-based methods for monitoring hydrogen sulfide , 2012 .

[20]  Anne-Claude Romain,et al.  Monitoring the exhaust air of a compost pile as a process variable with an e-nose , 2005 .

[21]  Shankar Vembu,et al.  Chemical gas sensor drift compensation using classifier ensembles , 2012 .

[22]  Takamichi Nakamoto,et al.  Odor recorder using active odor sensing system , 2001 .

[23]  H. Troy Nagle,et al.  Handbook of Machine Olfaction: Electronic Nose Technology , 2003 .

[24]  Silvia Coradeschi,et al.  Odor Recognition for Intelligent Systems , 2008, IEEE Intelligent Systems.

[25]  Ki-Hyun Kim,et al.  The Relative Performance of NDIR-based Sensors in the Near Real-time Analysis of CO2 in Air , 2007, Sensors.

[26]  Hervé Bourlard,et al.  Hybrid Connectionist Models For Continuous Speech Recognition , 1996 .

[27]  David E. Goldberg,et al.  Genetic Algorithms in Search Optimization and Machine Learning , 1988 .

[28]  John P. Carter,et al.  A neural network model for the uplift capacity of suction caissons , 2001 .

[29]  Gyu-Tae Kim,et al.  Fabrication and atmospheric-pressure-dependent electrical properties of a ZnO nanowire device , 2007 .

[30]  Sang-Woo Ban,et al.  SnO/sub 2/ gas sensing array for combustible and explosive gas leakage recognition , 2002 .

[31]  Udo Weimar,et al.  Hand‐Held and Palm‐Top Chemical Microsensor Systems for Gas Analysis , 2004 .

[32]  Xiao Li,et al.  The study of gas sensor array signal processing with improved BP algorithm , 2000 .

[33]  L. Friberg.  [Air pollution]. , 1984, Svenska lakartidningen.