Sensor-based occupancy behavioral pattern recognition for energy and comfort management in intelligent buildings

Bing Dong, Burton Andrews

Research output: Contribution to conferencePaper

103 Scopus citations

Abstract

There has been extensive research focusing on developing smart environments by integrating data mining techniques into environments that are equipped with sensors and actuators. The ultimate goal is to reduce the energy consumption in buildings while maintaining a maximum comfort level for occupants. However, there are few studies successfully demonstrating energy savings from occupancy behavioural patterns that have been learned in a smart environment because of a lack of a formal connection to building energy management systems. In this study, the objective is to develop and implement algorithms for sensor-based modelling and prediction of user behaviour in intelligent buildings and connect the behavioural patterns to building energy and comfort management systems through simulation tools. The results are tested on data from a room equipped with a distributed set of sensors, and building simulations through EnergyPlus suggest potential energy savings of 30% while maintaining an indoor comfort level when compared with other basic energy savings HVAC control strategies.

Original languageEnglish (US)
Pages1444-1451
Number of pages8
StatePublished - 2009
Externally publishedYes
Event11th International IBPSA Conference - Building Simulation 2009, BS 2009 - Glasgow, United Kingdom
Duration: Jul 27 2007Jul 30 2007

Conference

Conference11th International IBPSA Conference - Building Simulation 2009, BS 2009
CountryUnited Kingdom
CityGlasgow
Period7/27/077/30/07

ASJC Scopus subject areas

  • Computer Science Applications
  • Building and Construction
  • Architecture
  • Modeling and Simulation

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