Detection of Pollutants in Water Using a Wireless Network of Electronic Noses

We present here a network of hand-held wireless electronic noses (e-noses) for the detection of solutions of different chemicals such as ammonia, ethanol, toluene and ethyl acetate in water. The network is formed by two identical e-noses based on resistive microchemical sensors. Data processing techniques are based in Principal Component Analysis for dimensionality reduction for 3D representation and Neural Network for classification of the samples. The proposed system can be used for sensor optimization since different sensors with different temperatures of operation could be tested in several devices in order to select the optimal array for a particular detection or application. Result show that, depending on the parameters of the sensor array, the discrimination of the pollutants can be achieved with different success rate in classification.