Occupant Location Prediction Using Association RuleMining

Workshop on AI Problems and Approaches for Intelligent Environments

Conor Ryan ; Kenneth N. Brown

Others  :  http://ceur-ws.org/Vol-907/AI4IE_paper5.pdf
PID  :  43221

来源: CEUR

【 摘 要 】

HVAC systems are significant consumers of energy, however building management systems do not typically operatethem in accordance with occupant movements. Due to the delayedresponse of HVAC systems, prediction of occupant locations isnecessary to maximize energy efficiency. In this paper we presentan approach to occupant location prediction based on associationrule mining, which allows prediction based on historical occupantmovements and any available real time information. We show howassociation rule mining can be adapted for occupant prediction andshow the results of applying this approach on simulated and real occupants.