An ASIC-based system-in-package MEMS gas sensor with impedance spectroscopy readout and AI-enabled identification capabilities

The main advantages of micromachined metal oxide semiconductor (MOX) gas sensors, in particular their low cost, high sensitivity, miniaturization and low power consumption, are compromised by lack of selectivity and long-term sensor signal drifts, which often hinder their application in real-world sensing applications. To increase the sensor data dimensionality, temperature cycled operation (TCO) and impedance spectroscopy (IS) readout was proposed, enabling the acquisition of large datasets from a single sensor, as suitable to be exploited by machine learning techniques. Furthermore, recent studies have shown how the IS readout minimizes the issues represented by the sensor long-term signal drift. The aim of this work is the development of a smart system-in-package, integrating a state-of-the-art micromachined MOX gas sensor based on a wafer-level nanostructured sensing layer with a novel versatile sensor interface chip, capable of high performance IS readout. We propose a miniaturized sensing device, which is a small, lightweight low power consumption chemical sensing micro-system with fast and accurate classification capabilities, suitable to be deployed in long multi-node sensing cables or on unmanned aerial vehicles. A software suite comprising a sensor training wizard was also developed, enabling users with no technical background to train the sensing system.