E-Nose for gas detection at vehicle exhaust Using supervised learning algorithm

Abstract

Abstract: An electronic nose is an intelligent system used to monitor the gases. The system is designed to detect the pollution at vehicle exhaust. The system informs the user about the concentration of CO and HC. It also displays whether pollution is under control or not. Commercial gas sensors having low power consumption are used in the design. For data acquisition, a micro-controller is used. Data processing is done using supervised learning of Artificial Neural Network (ANN). The results of ANN training are given, which is obtained using MATLAB. The system is calibrated using the actual field readings of PUC machines available. Five Different ANN training methods are also compared based on errors. GUI developed displays concentrations of CO and HC, a conclusive message and bars indicating present gas level