Long term occupancy estimation in a commercial space: an empirical study: poster abstract

Conference · Mon Apr 10 00:00:00 EDT 2017

DOI:https://doi.org/10.1145/3055031.3055062· OSTI ID:1811651

Liu, Kin Sum; Munir, Sirajum; Francis, Jonathan; Shelton, Charles; Lin, Shan

Understanding occupancy patterns in a building is very useful to control HVAC systems for improving energy efficiency of the building and occupant comfort. There has been a very little attempt to understand long term occupancy patterns in a commercial space. In this work, we leverage depth sensors (Kinect for XBOX One) to collect occupancy count from an 11,000 square foot commercial space (Bosch office) for nine months. We analyze the collected data and describe key findings that provide deep insights about how a commercial space is used and serve as a guideline to formulate novel and efficient control strategies.

• Research Organization: Stony Brook Univ., NY (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: 1811651
• Resource Relation: Conference: IPSN '17: Proceedings of the 16th ACM/IEEE International Conference on Information Processing in Sensor Networks, April 2017
• Country of Publication: United States
• Language: English