Luis Daniel Martinez Salgado
Deep Learning YOLO like model Applied on Energy Disaggregation.
Rel. Edoardo Patti, Marco Castangia. Politecnico di Torino, Master of science program in Ict For Smart Societies, 2022
Abstract
Appliance Load Monitoring (ALM) is nowadays crucial for energy management solutions, allowing user to obtain appliance-specific energy consumption data that can be used on design an energy optimization plan. Non-Intrusive Load Monitoring (NILM), or energy disaggregation, is currently the most attractive approach to address this problem since it avoids deploying a smart meter for each appliance on the system, but instead aim to disaggregate a specific appliance consumption from the total aggregated load data of a single building. We present a novel model inspirated on the architecture of YOLO, that stand for You Only Look Once, which objective is to detect in a single forward pass where is an appliance activation.
We show that the proposed model can learn the singular signatures of the target appliances
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