Paper:
Language: English:

Narrowing Algorithm for Indoor-Air Pollutants using Gas Sensor Patterns

Takashi Oyabu^*, Takeshi Onodera^, Hidetaka Nambo^ and Haruhiko Kimura^**

^*Kanazawa University of Economics Kanazawa 920-8620, Japan
^**Kanazawa University, Faculty of Engineering Kanazawa 920-8667, Japan

Received: April 8, 1999

Accepted: May 13, 1999

Keywords: Algorithm, Gas sensor, Indoor-air pollutants, Sensor pattern, OPS5

Journal ref: Journal of Advanced Computational Intelligence and Intelligent Informatics, Vol.3, No.6 pp. 519-523, 1999

Abstract

There are many types of gaseous indoor-air pollutants in the domestic environment, generally mixtures of several gases. These gases harm people in houses with sick house syndrome. It is important to identify pollutants and their grades. We narrow many possible pollutants to two or three using output patterns of plural tin-oxide gas sensors. Six types of sensors are used in the system. The algorithm to identify the mixture of gas is made using the characteristics of sensor patterns and has high reliability, especially in detecting alcoholic gas, carbon dioxide, and carbon monoxide gases. It consists of several general steps and sensitivity grade of each sensor in a gas mixture is important to identify polluting gases. In practice, OPS5, an expert system, is used to narrow the types of gas.

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