Proceedings of the 12th ACM international conference on Ubiquitous computing
The smart thermostat: using occupancy sensors to save energy in homes
Proceedings of the 8th ACM Conference on Embedded Networked Sensor Systems
Private memoirs of a smart meter
Proceedings of the 2nd ACM Workshop on Embedded Sensing Systems for Energy-Efficiency in Building
LIBSVM: A library for support vector machines
ACM Transactions on Intelligent Systems and Technology (TIST)
PreHeat: controlling home heating using occupancy prediction
Proceedings of the 13th international conference on Ubiquitous computing
Empath: a continuous remote emotional health monitoring system for depressive illness
Proceedings of the 2nd Conference on Wireless Health
Nonintrusive appliance load monitoring: Review and outlook
IEEE Transactions on Consumer Electronics
Automatic socio-economic classification of households using electricity consumption data
Proceedings of the fourth international conference on Future energy systems
An opportunistic activity-sensing approach to save energy in office buildings
Proceedings of the fourth international conference on Future energy systems
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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%.