12,000

We have over 12,000 students, from over 100 countries, within one of the safest campuses in the UK

93%

93% of Lancaster students go into work or further study within six months of graduating

Home > Research > Publications & Outputs > PreHeat: controlling home heating using occupan...
View graph of relations

« Back

PreHeat: controlling home heating using occupancy prediction

Research output: Contribution in Book/Report/ProceedingsConference contribution

Published

  • James Scott
  • A.J. Bernheim Brush
  • John Krumm
  • Brian Meyers
  • Michael Hazas
  • Stephen Hodges
  • Nicolas Villar
Publication date2011
Host publicationProceedings of the 13th international conference on Ubiquitous computing (UbiComp '11)
Place of publicationNew York
PublisherACM
Pages281-290
Number of pages10
ISBN (Print)978-1-4503-0630-0
Original languageEnglish

Publication series

NameUbiComp '11
PublisherACM

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.