A new paper from our group was recently awarded Best Paper at the International Conference on Sensing, Communication and Networking 2021.
The work, titled “Compensating Altered Sensitivity of Duty-Cycled MOX Gas Sensors with Machine Learning“, has been a collaboration with researchers from TU Graz and ETH Zurich. In it, we show that it is possible to recover accurate continuous-sensor measurements from transient responses obtained from a duty cycled sensor and compensate for an altered multi-gas cross-sensitivity profile using machine learning methods.
Author: Andres Gomez
Date: 14. July 2021