Buildings in the U.S. require a large amount of energy, representing nearly 40% of the total consumption, most of which is consumed as electricity. Buildings also have a proportionally large carbon-footprint and can waste a lot of energy in unnecessary heating and cooling. At the same time, energy and environmental standards are becoming stricter, and new methods are being sought for performance certification based on a building’s operation.
This project combines state-of-the-art sensor networking and novel data processing and control algorithms to determine where people are located inside buildings and actuate the heating and cooling systems accordingly, both in real-time and in predicting where people will go next based on past movements. The project is currently deployed on the UC Merced campus in the SE1 Building, as all of the buildings at UC Merced are managed by a central energy system and operated on a static schedule from 6am to 10pm. Known as the “Optical Turnstile” project, the data will allow for more fine-grained control strategies and give facilities managers more knowledge on how to optimally heat and cool the building.
This project has been featured in a recent issue of the CITRIS Signal.