Detection of occupancy status from internet connectivity for non-intrusive load monitoring

Abstract

Non-intrusive load monitoring (NILM) methods are widely used for appliance level energy disaggregation in residential buildings. These methods mostly depend on electrical features, and they have not been much successful in applying for commercial buildings. However, recent research has indicated that the accuracy of existing NILM methods can be improved by associating with occupancy data. Therefore, in this paper a novel occupancy detection algorithm is proposed which can detect occupancy status of individuals using the connectivity of their information technology (IT) devices to the local area network of the building. The model is validated using data collected at a university building, with mean errors of 01:23 and 04:02 minutes for the detection of arrival and departure. The occupancy profiles developed by the proposed model can be used to disaggregate energy consumption in a commercial building to appliance and occupant level.