Sensing and Data Collection Methods for Occupant-Centric Building Control: A Critical Review of State of the Art

Abstract

Given the recent improvements in building automation and sensing infrastructure, Occupant-Centric Control (OCC) strategies have been introduced. OCC is a novel approach for indoor climate control in which occupant preferences are directly measured or indirectly inferred from various sensors or control interfaces to optimize building operations. However, obtaining occupants’ data and preferences is typically challenging because of their dynamic and inconsistent behaviours. As a result, inaccurate assumptions are usually used in building operations, which often leads to wasteful energy use or may trigger occupant discomfort. In contrast, data generated by building systems can be used to tailor their operations to unique occupant behavioural patterns. To this end, this paper provides a comprehensive overview of the approaches used in sensing and acquisition of occupancy and occupants’ preferences to develop OCC for buildings. Previous studies were first analyzed to identify their locations, durations, and building types. Data collection methods used in these studies were then further categorized based on the type of information they provide, namely (1) occupants’ interactions with building systems (e.g., thermostat setpoint changes, light switches, and opening/closing of windows/blinds), (2) occupants’ preferences (e.g., occupants’ comfort level), and finally (3) indoor and/or outdoor environmental parameters which trigger occupant-building interactions. Alternative data collection approaches, such as those relying on augmented reality and facial recognition to evaluate comfort were also reviewed to outline their main advantages and limitations. Consequently, this paper provides an overview of OCC developments and relevant data collection methods for both researchers and building operators.