A dataset for non-intrusive load monitoring: Design and implementation
DPB Renaux, F Pottker, HC Ancelmo, AE Lazzaretti… - Energies, 2020 - mdpi.com
A NILM dataset is a valuable tool in the development of Non-Intrusive Load Monitoring
techniques, as it provides a means of evaluation of novel techniques and algorithms, as well …
techniques, as it provides a means of evaluation of novel techniques and algorithms, as well …
Feature Extraction of V–I Trajectory Using 2-D Fourier Series for Electrical Load Classification
BM Mulinari, L da Silva Nolasco, E Oroski… - IEEE Sensors …, 2022 - ieeexplore.ieee.org
Nonintrusive load monitoring (NILM) techniques allow the individual consumption of devices
in an installation to be reported to the user, collaborating in the awareness and managing …
in an installation to be reported to the user, collaborating in the awareness and managing …
A multi-agent NILM architecture for event detection and load classification
A multi-agent architecture for a Non-Intrusive Load Monitoring (NILM) solution is presented
and evaluated. The underlying rationale for such an architecture is that each agent (load …
and evaluated. The underlying rationale for such an architecture is that each agent (load …
New Appliance Signatures for NILM Based on Mono-Fractal Features and Multi-Fractal Formalism
A Mughees, M Kamran, N Mughees, A Mughees… - IEEE …, 2024 - ieeexplore.ieee.org
Smart energy management demands better ways to understand the energy consumption of
buildings. Nonintrusive Load Monitoring (NILM) is an emerging technique that …
buildings. Nonintrusive Load Monitoring (NILM) is an emerging technique that …
Novel Fractal-Based Features for Low-Power Appliances in Non-Intrusive Load Monitoring.
A Mughees, M Kamran - Computers, Materials & Continua, 2024 - search.ebscohost.com
Non-intrusive load monitoring is a method that disaggregates the overall energy
consumption of a building to estimate the electric power usage and operating status of each …
consumption of a building to estimate the electric power usage and operating status of each …
[PDF][PDF] Features extraction and selection with the scattering transform for electrical load classification
EL Aguiar, AE Lazzaretti, DR Pipa - Learn. Nonlinear Models, 2023 - sbic.org.br
The Scattering Transform (ST) presents itself as an alternative approach to the classic
methods that involve neural networks and deep learning techniques for the feature …
methods that involve neural networks and deep learning techniques for the feature …
[PDF][PDF] Performance of scattering transform feature extraction for electrical load classification
EL de Aguiar, AE Lazzaretti, DR Pipa - Proc. XV Congress on …, 2021 - sbic.org.br
The Scattering transform (ST) presents itself as an alternative approach to the classic
methods that involve neural networks and deep learning techniques for the feature …
methods that involve neural networks and deep learning techniques for the feature …