Feature reduction using support vector machines for binary gas detection

Abstract

Gas sensor (electronic nose) has many different applications, such as fire detection, food quality control or medical application as well as the detection of atmospheric gases. We describe in this paper a signal processing technique using wavelet transform and Support Vector Machines (SVM) for CO and NO2 gas detection and to obtain gas concentration. We propose a low complexity algorithm which can be implemented in a low cost palmtop gas monitor. SVM were used in a twofold way. First, SVM were used to classify the type of gas and then for the estimation of gas concentration. © Springer-Verlag Berlin Heidelberg 2003.