A multi-expert deep learning framework for accurate and scalable appliance-level energy disaggregation

Muhammad Zaigham Abbas, Malik Intisar Ali Sajjad, Gianfranco Chicco, Roberto Napoli, Department of Electrical Engineering, University of Engineering and Technology, Dipartimento Energia , Galileo Ferraris, Politecnico di Torino

Proceedings of the Institution of Mechanical Engineers, Part A: Journal of Power and Energy

Published online on August 05, 2026

Abstract

Proceedings of the Institution of Mechanical Engineers, Part A: Journal of Power and Energy, Ahead of Print.
Accurate identification of individual appliance activation and power consumption is essential for effective energy consumption analysis in residential buildings. Non-Intrusive Load Monitoring (NILM) allows the disaggregation of appliance consumption using ...