Occupancy Detection from Electricity Consumption Data






Faculty/Professorship: Information Systems and Energy Efficient Systems  
Author(s): Kleiminger, Wilhelm; Beckel, Christian; Staake, Thorsten ; Santini, Silvia
Title of the compilation: BuildSys'13: Proceedings of the 5th ACM Workshop on Embedded Systems For Energy-Efficient Buildings
Corporate Body: 5th ACM Workshop on Embedded Systems For Energy-Efficient Buildings
BuildSys'13
Publisher Information: New York, NY, USA : ACM
Year of publication: 2013
Pages: 1-8
ISBN: 978-1-4503-2431-1
Language(s): English
DOI: 10.1145/2528282.2528295
URL: http://dl.acm.org/citation.cfm?id=2528295
Abstract: 
Detecting when a household is occupied by its residents is fundamental to enable a number of home automation applications. Current systems for occupancy detection usually require the installation of dedicated sensors, like passive infrared sensors, magnetic reed switches, or cameras. In this paper, we investigate the suitability of digital electricity meters -- which are already available in millions of households worldwide -- to be used as occupancy sensors. To this end, we have collected fine-grained electricity consumption data along with ground-truth occupancy information for 5 households during a period of about 8 months. Our results show that using common classification methods it is possible to achieve occupancy detection accuracies of more than 80%.
Type: Conferenceobject
URI: https://fis.uni-bamberg.de/handle/uniba/3176
Year of publication: 22. April 2014