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dc.creator | Zeiler, W. | |
dc.creator | Labeodan, T. | |
dc.creator | Bozem, G. | |
dc.creator | Maaijen, R. | |
dc.date.accessioned | 2014-01-10T20:21:16Z | |
dc.date.available | 2014-01-10T20:21:16Z | |
dc.date.issued | 2013 | |
dc.identifier.other | ESL-IC-13-10-51 | |
dc.identifier.uri | https://hdl.handle.net/1969.1/151461 | |
dc.description.abstract | Building occupancy information is a crucial factor that should be considered in the control strategy of building operations for improved energy efficiency and occupant comfort. As occupancy is stochastic and challenging to measure, a number of real-time occupancy detection systems comprising multiple sensors within a wireless network (WSN) using technologies such as radio frequency identification (RFID) and WIFI enabled devices have been proposed for use in large commercial office buildings. However due to high deployment cost and need for management of additional infrastructure for these systems, its application in demand driven control of heating, ventilation and air conditioning (HVAC) is limited notwithstanding the accruable worthwhile energy saving potentials. In this paper, some of this new technologies are briefly discussed and compared with opportunistic implicit building infrastructures which can be exploited for realtime demand driven HVAC control based on the application of the Kesselring decision support method. | en |
dc.publisher | Energy Systems Laboratory (http://esl.tamu.edu) | |
dc.publisher | Texas A&M University (http://www.tamu.edu) | |
dc.subject | demand driven HVAC control | en |
dc.subject | comfort | en |
dc.subject | energy | en |
dc.title | Towards Building Occupants Positioning: Track and Trace for Optimal Process Control | en |
dc.contributor.sponsor | TU Eindhoven University |
This item appears in the following Collection(s)
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ICEBO - International Conference for Enhanced Building Operations
International Conference for Enhanced Building Operations