The main objective of AMUSENS is to develop a low-power gas sensor platform with adaptable selectivity to different gas environments by combining metal oxide (MO) multi-pixel sensing approach and trained artificial intelligence (AI), and to demonstrate the adaptability to two user case applications chosen in the fields of personal environmental monitoring and health care.
This approach will circumvent most of the current limitations of commercial MO-based gas sensors. (i) Using innovative and sustainable additive manufacturing approaches, AMUSENS aims at demonstrating efficient large-scale production of multi-pixel gas sensors based on a wide variety of MO nanostructures as sensing materials, while drastically reducing material consumptionand waste thanks to localized deposition. (ii) AMUSENS will take the advantage of AI first as a screening method for sensing materials to be used in the muti- pixel sensing platforms upon envisaged gas compositions given by the targeted applications (environmental monitoring and health care). By combining this selection with the local deposition techniques, AMUSENS will demonstrate a methodology to provide a viable way to produce multi-pixel sensors with on-demand material combinations, thus accelerating the time to market of gas sensors with specific properties. (iii) AI will also be used to process signals from the various gas sensing pixels and extract specific patterns characterizing training environments defined by the targeted applications. (iv) At last, advanced data treatment and training will compensate variations between different batches and evolutions of the sensing material within the sensor lifetime.