Occupancy detection and prediction from electricity consumption data in smart homes: application to a Portuguese case-study

ABSTRACT This research proposes an investigation on the problem of detecting and predicting occupancy by using solely readily available electricity consumption data, obtained from smart metres. The following research questions are defined: (1) Is it possible to predict occupancy by using solely electricity consumption data?; (2) Is it possible to use a single classification model to monitor occupancy in multiple households? The findings show that an occupancy detection accuracy of up to 92% can be achieved by using solely electricity consumption data. The problem of generalizing the classification model, i.e. using a single classification model to monitor occupancy in multiple households, is also addressed. It is found that an occupancy detection accuracy of up to 83% is achievable in this case. Regarding occupancy prediction, occupancy in multiple households with an accuracy of up to 75% is obtained, by using solely electricity consumption data. For both occupancy monitoring and prediction, it is found that households with a low level of occupancy can benefit more from these systems.