Comparison of direct interfacing and ADC based system for gas identification using E-Nose

This paper presents the design and characterization of a direct interfacing circuit (DIC) for sensor array and its comparison with the built-in analog to digital converter (ADC) of a PIC microcontroller. Before implementing the DIC for the sensor array, we examined its performance on simulated voltages to have a proper understanding of the output characteristics. To explore the DIC for multi-sensory system, an exemplary E-Nose setup was developed for experimentation. The sensor responses from the E-Nose system are concurrently measured by two microcontrollers, one using DIC and the other by the 10-bit internal ADC of the microcontroller. Principal component analysis (PCA) is then performed for visualizing and comparing the class separation for both the methods. To further explore the discriminating capability of the DIC based E-Nose, artificial neural network (ANN) is implemented. Finally, we delve into microcontroller based online gas discrimination by the E-Nose using DIC and its comparison with ADC results. Equivalent results were observed for both the cases with accuracy up to 97 %.