Non-Intrusive Load Monitoring Toolkit (nilmtk)
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Updated
Apr 23, 2024 - Python
Non-Intrusive Load Monitoring Toolkit (nilmtk)
Deep Neural Networks Applied to Energy Disaggregation
An archive for NILM papers with source code and other supplemental material
A repository of awesome Non-Intrusive Load Monitoring(NILM) with code.
Multi-NILM: Multi Label Non Intrusive Load Monitoring
Energy Management Using Real-Time Non-Intrusive Load Monitoring
This repo provides four weight pruning algorithms for use in sequence-to-point energy disaggregation as well as three alternative neural network architectures.
Undergraduate research by Yuzhe Lim in Spring 2019. Field of research: Deep Neural Networks application on NILM (Nonintrusive load monitoring) for Energy Disaggregation
This contains the energy disaggregation code based on Graph Signal Processing approach
A Synthetic Energy Consumption Dataset for Non-Intrusive Load Monitoring
Overview of research papers with focus on low frequency NILM employing DNNs
🔌 Load Monitoring and Energy Disaggregation on a RasPi
A User-Oriented Energy Monitor to Enhance Energy Efficiency in Households
A Moroccan Buildings’ Electricity Consumption Dataset. MORED is made available by TICLab of the International University of Rabat (UIR), and the data collection was carried out as part of PVBuild research project, coordinated by Prof. Mounir Ghogho and funded by the United States Agency for International Development (USAID).
Overview of NILM works employing Deep Neural Networks on low frequency data
Supplemental material on comparability and performance evaluation in NILM
Code for our MPS 2019 paper entitled "A Machine Learning Approach for NILM based on Odd Harmonic Current Vectors"
Non Intrusive Load Monitoring data repository and data converter for NILMTK
Presentation of Neural NILM for BuildSys 2015 conference in November 2015
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