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
This contains the energy disaggregation code based on Graph Signal Processing approach
Multi-NILM: Multi Label Non Intrusive Load Monitoring
A repository of awesome Non-Intrusive Load Monitoring(NILM) with code.
This repo provides four weight pruning algorithms for use in sequence-to-point energy disaggregation as well as three alternative neural network architectures.
Energy Management Using Real-Time Non-Intrusive Load Monitoring
🔌 Load Monitoring and Energy Disaggregation on a RasPi
A Synthetic Energy Consumption Dataset for Non-Intrusive Load Monitoring
Minion - World's Smallest AI Energy Auditor
Overview of research papers with focus on low frequency NILM employing DNNs
Undergraduate research by Yuzhe Lim in Spring 2019. Field of research: Deep Neural Networks application on NILM (Nonintrusive load monitoring) for Energy Disaggregation
Machine Learning and Internet of Things approach for turning off appliances when not used for saving power consumption.
A User-Oriented Energy Monitor to Enhance Energy Efficiency in Households
DEPS: Dataset de la Escuela Politénica Superior
Supplemental material on comparability and performance evaluation in NILM
Presentation of Neural NILM for BuildSys 2015 conference in November 2015
Metrics to assess the generalisation ability of NILM algorithms
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