OccuTherm: Occupant Thermal Comfort Inference using Body Shape Information
Thermal comfort is a decisive factor for the well-being, productivity, and overall satisfaction of commercial building occupants. Many commercial building automation systems either use a fixed zone-wide temperature set-point for all occupants or they rely on extensive sensor deployments with frequent online interaction with occupants. This results in inadequate comfort levels or significant training effort from users, respectively. However, the increasing ubiquity of cheap, depth-based occupancy tracking systems has enabled an improvement in inferential capabilities. We propose the novel system OccuTherm to model thermal comfort of occupants. We conducted a laboratory study with 77 participants to collect data for the implementation of a thermal comfort model that derives thermal comfort using the human body shape. Based on the comparison with model baselines and ablations, we show that our approach infers thermal comfort of individuals with 60 % accuracy when body shape information is taken into account; 6 % more than state-of-the-art approaches. We make our code, mobile app, datasets, and models freely available.
- Research Organization:
- Carnegie Mellon Univ., Pittsburgh, PA (United States)
- Sponsoring Organization:
- USDOE Office of Energy Efficiency and Renewable Energy (EERE), Energy Efficiency Office. Building Technologies Office
- DOE Contract Number:
- EE0007682
- OSTI ID:
- 1576189
- Report Number(s):
- DOE-CMU-07682
- Resource Relation:
- Conference: 6th ACM International Conference on Systems for Energy-Efficient Buildings, Cities, and Transportation. BuildSys ’19. New York, NY, USA, 2019; Related Information: http://doi.acm.org/10.1145/3359427.3361915
- Country of Publication:
- United States
- Language:
- English
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