Smart building controls learn occupant behavior to reduce energy use
— Occupant behavior, a highly stochastic and complex phenomenon, is unique in each building and remains a challenge for energy-efficient operation of building systems. Current building controls, which rely on the hard-coded expert knowledge, either ignore or over-simplify the expert knowledge and follow an energy-intensive approach to ensure occupant comfort. Recent study by Amirreza Heidari, a PhD student at ICE co-supervised by Prof. François Maréchal from IPESE, indicates that Reinforcement Learning, an aritificial intelligence method, can enable building controls to learn and adapt to the occupant behavior and provide a significant energy reduction while preserving comfort and health of people.
