Nonintrusive load monitoring of electrical devices in health smart homes

This paper presents a non-intrusive load monitoring system for determining the operation schedule of multiple electrical devices, operated simultaneously, in a health smart home. Profiling the usage of electrical devices can be used as a method for determining an occupant's activities of daily living, which can support independent living of older adults. The proposed non-intrusive load monitoring system determines the status of electrical devices based on the analysis of load signatures. A feature-based model using the real power is employed in this work. Experimental results show that the proposed approach can achieve 86.25% device recognition accuracy for 5 common household electrical devices operating simultaneously using a KNN classifier.