Abstract
Understanding occupancy paterns 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 litle atempt to understand long term occupancy paterns 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.
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CITATION STYLE
Liu, K. S., Munir, S., Francis, J., Shelton, C., & Lin, S. (2017). Poster abstract: Long term occupancy estimation in a commercial space: An empirical study. In Proceedings - 2017 16th ACM/IEEE International Conference on Information Processing in Sensor Networks, IPSN 2017 (pp. 307–308). Association for Computing Machinery, Inc. https://doi.org/10.1145/3055031.3055062
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