James Scott
A.J. Bernheim Brush
John Krumm
ABSTRACT
Home heating is a major factor in worldwide energy use. Our system, PreHeat, aims to more efficiently heat homes by using occupancy sensing and occupancy prediction to automatically control home heating. We deployed PreHeat in five homes, three in the US and two in the UK. In UK homes, we controlled heating on a per-room basis to enable further energy savings. We compared PreHeat's prediction algorithm with a static program over an average 61 days per house, alternating days between these conditions, and measuring actual gas consumption and occupancy. In UK homes PreHeat both saved gas and reduced MissTime (the time that the house was occupied but not warm). In US homes, PreHeat decreased MissTime by a factor of 6-12, while consuming a similar amount of gas. In summary, PreHeat enables more efficient heating while removing the need for users to program thermostat schedules.
Supplemental Material
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- Krumm, J. and Brush, A. "Learning Time-Based Presence Probabilities", Proc. of Pervasive 2011, 2011. Google ScholarDigital Library
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Index Terms
- PreHeat: controlling home heating using occupancy prediction
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