Energy Disaggregation & Appliance Identification in a Smart Home: Transfer Learning enables Edge Computing

arXiv:2301.03018v2 Announce Type: replace-cross
Abstract: Non-intrusive load monitoring (NILM) or energy disaggregation aims to extract the load profiles of individual consumer electronic appliances, given an aggregate load profile of the mains of a smart home. This work proposes a novel deep-learning and edge computing approach to solve the NILM problem and a few related problems as follows. 1) We build upon the reputed seq2-point convolutional neural network (CNN) model to come up with the proposed seq2-[3]-point CNN model to solve …

abstract arxiv computing consumer cs.ai cs.lg edge edge computing eess.sp electronic energy extract home identification monitoring novel profile profiles smart smart home transfer transfer learning type work