“Occupant presence and behavior in buildings is considered a key element towards building intelligent and pervasive environments. Yet, practical applications of energy intelligent buildings typically suffer from high sensor unreliability,” highlights a recent paper that proposes a fundamentally new way of inferring occupancy in smart buildings. The study has been able to demonstrate an additional 30% energy savings by propagating senor uncertainty and advocates the use of probabilistic data over traditional discrete classification outputs. This research has the potential to disrupt the popular approach to occupancy sensing and bring about new levels of energy efficiency. The paper – Propagating sensor uncertainty to better infer office occupancy in smart building control – was authored by Charikleia Papatsimpa and Jean-Paul Linnartz of the Department of Electrical Engineering at the Eindhoven University of Technology, in the Netherlands. They propose a layered probabilistic framework for occupancy-based control in intelligent buildings. In this cascade of layers, where each layer addresses […]