Smart sensing technologies play a key role in the core of smart systems, which form the rapidly evolving internet of things. In this context, buildings' occupancy information is an important input that allows smart systems to be seamlessly aware of and responsive to the inhabitants, thus ensuring their comfort. In this paper we present UltraSense, an ultrasound-based room occupancy sensing system that relies on unsupervised learning, to automatically calibrate its parameters according to the room's environment. This ability avoids the need for manual calibration of the sensing system for each new environment. While commonly available occupancy detection technologies are limited to line-of-sight (LOS) conditions, UltraSense also operates in non line-of-sight (NLOS) scenarios. The proposed system was implemented and tested in order to characterize its performance. UltraSense was developed for the European research project SmartHeat in the frame of ambient assisted living.
Hammoud, A., Deriaz, M., & Konstantas, D. (2017). UltraSense: A Self-Calibrating Ultrasound-Based Room Occupancy Sensing System. In Procedia Computer Science (Vol. 109, pp. 75–83). Elsevier B.V. https://doi.org/10.1016/j.procs.2017.05.297