Real-Time Occupancy Estimation Using WiFi Network to Optimize HVAC Operation

Abstract

Commercial and residential buildings consume about 27% of total energy used in the US, out of which nearly half is consumed by commercial building sector and it expected to grow in the next 30-year period. Literature suggests that occupancy data may improve the energy consumption of the buildings, especially in HVAC operation. In the past few years studies came up with various frameworks based on existing infrastructure to estimate occupancy, out of which commodity WiFi gained popularity in detecting, estimating, and tracking occupants within buildings. However, there are concerns with those frameworks such as added infrastructure and computational efforts, upgrades to existing infrastructure, and privacy of occupants. This paper presents a simplistic framework based on commodity WiFi to estimate real time occupancy data without any added infrastructure or upgrades, while protecting the occupant privacy and can produce significant energy reduction in HVAC operation. The framework is tested on a large lecture hall in an institutional building that has multiple classes scheduled. The initial tests showed that the WiFi based occupancy had a 0.96 correlation with the established ground truth. Additionally, the WiFi based occupancy schedule resulted in at least 50% savings in HVAC energy consumption over static schedule.