The microwave gas sensors array driven by a decision tree algorithm for enhanced 3S parameters

In the gas-sensing approach, 3S parameters are known as sensitivity, selectivity, and stability. The better the 3S parameters, the better the detection. Regardless of the detection nature of the gas sensors used to fabricate e-noses, the 3S parameters are universally used. In the case of microwave gas sensors, implementing e-noses is still pending. This paper presents the development of a decision tree algorithm to enhance the 3S parameters of microwave gas sensors based on metal oxides and tested under various conditions. A decision tree algorithm enables the detection of the 2n+2 gases. However, the theoretical analysis suggests that even more gases could be detected when the thickness of the gas-sensitive layer is optimized.