Semi-automatic labeling for public non-intrusive load monitoring datasets

Abstract

In this paper we present and evaluate a semiautomatic labeling prototype to enable the creation of fully labeled energy disaggregation datasets from sub-metered data. Our results advocate in favor of our approach and show that it is possible to extract individual appliance transitions with considerable precision, as long as the individual appliance information is present in the sub-metered data, and its resolution is high enough.