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Neural network calibration of a semiconductor metal oxide micro smell sensor

A Design of a micro smell sensor based on semiconductor metal oxide method is presented. This sensor is able to recognize two different kinds of gas (CO and H2) and will estimate the amount of dominate gas in the environment. The SnO2 is employed as the key module of the sensor. A neural network calibration is applied to the sensor in order to identification of one of the two gases in an environment with complex combination of gases. The results vividly show that the sensor is able to approximate the amount of these two gases in the pool of gases.