PIC microcontroller & PC based gas sensing system is presented in this project. The analysis presented here depends on thin film metal oxide gas sensors TGS 822, TGS 813, TGS 2600, MQ6 and MQ7. The differences in the steady state performance among their sensors are used for improving their selectivity and sensitivity, while the combination of gas sensors permits success in gas classification problems. In the presented approach the gas sensors are embedded into a chamber with a heating system. Different types of gases are used, such as, Methane, Carbon monoxide and LPG to pass through this chamber with different concentrations, different operating temperatures and different load resistances. Sets of data collected to detect the gas sensitivity for each sensor depending on the output voltage in relation to temperatures, concentration of gases and variable resistances for each sensor. In this project, novel approach, based on the ANN technique, used for the gas identification. The identification is done directly from the data driven from the microcontroller by using ANN trained model. The results of the ANN are shown to provide gas identification according to variation in different parameters, such as gas concentrations, variation in sensor's resistance and output voltage of sensor at different temperatures and to indicate that the selection of different gases is possible, based on microcontroller, which improves sensitivity and selectivity with high accuracy and reliability.

Gas detection ANN intelligent sensing Gas sensors.