Software-only occupancy inference in a workplace findings from a field trial

Abstract

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.