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Article
Forecasting Internal Temperature in a Home with a Sensor Network
Procedia Computer Science
  • Bruce Spencer, University of New Brunswick
  • Omar Alfandi, Zayed University
Document Type
Conference Proceeding
Publication Date
1-1-2016
Abstract

© 2016 The Authors. We forecast internal temperature in a home with sensors, modeled as a linear function of recent sensor values. The Smart∗Project provides publicly available data from an inhabited home over a three month period, reporting on 38 sensors including environmental readings, circuit loads, motion detectors, and switches controlling lights and fans. We select 13 of these sensors that have some influence on the internal temperature, and create forecasts that are accurate to within about 1.6°F (0.9°C) over the next six hours. Temperature prediction is important for saving energy while maintaining comfortable conditions in the home.

Publisher
Elsevier
Disciplines
Keywords
  • data,
  • Home Sensor Network,
  • Smart,
  • Temperature Forecasting
Scopus ID

84971268459

Creative Commons License
Creative Commons Attribution-NonCommercial-No Derivative Works 4.0 International
Indexed in Scopus
Yes
Open Access
Yes
Open Access Type
Gold: This publication is openly available in an open access journal/series
Citation Information
Bruce Spencer and Omar Alfandi. "Forecasting Internal Temperature in a Home with a Sensor Network" Procedia Computer Science Vol. 83 (2016) p. 1244 - 1249 ISSN: <p><a href="https://v2.sherpa.ac.uk/id/publication/issn/1877-0509" target="_blank">1877-0509</a></p>
Available at: http://works.bepress.com/omar-alfandi/3/