Software-only Occupancy Inference in a Workplace

HVAC and lighting loads contribute a significant fraction of total energy consumed in office buildings. These loads vary as a function of occupancy and therefore inferring occupancy is vital to optimizing energy efficiency within these buildings. This work presents evaluation and comparison results from a field trial conducted in a large office building, which involved estimating occupancy with the help of existing opportunistic context sources versus instrumented hardware sensors. Our results show that opportunistic sensing yielded an accuracy of 80% in comparison with expensive hardware sensors and may be used to continuously estimate fine-grained workplace occupancy in an inexpensive manner. Moreover the inferred occupancy information may also be used to identify anomalies in thermal management and space utilization within the building. Keywords—Energy Efficiency, Occupancy, Soft sensing.