Non-Intrusive Load Monitoring Toolkit (nilmtk)
A curated resources of awesome NILM resources
Deep Neural Networks Applied to Energy Disaggregation
A repository of awesome Non-Intrusive Load Monitoring(NILM) with code.
Code for NILM experiments using Neural Networks. Uses Keras/Tensorflow and the NILMTK.
Energy Management Using Real-Time Non-Intrusive Load Monitoring
The super-state hidden Markov model disaggregator that uses a sparse Viterbi algorithm for decoding. This project contains the source code that was use for my IEEE Transactions on Smart Grid journal paper.
Multi-NILM: Multi Label Non Intrusive Load Monitoring
Non-Intrusive Load Monitoring (NILM) for Home Assistant. Estimate appliance activity and energy usage from a whole-home power sensor, all locally.
[KDD 2025] NILMFormer: A Sequence-To-Sequence Non-Stationarity Aware Transformer for Non-Intrusive Load Monitoring
An Attention-based Deep Neural Network for Non-Intrusive Load Monitoring
Simple, fast and handy data loaders for NILM datasets to explore the data at convenience, provided with basic transformations like resampling, normalization and extract activities by thresholding.
A new CNN architecture to perform detection, feature extraction, and multi-label classification of loads, in non-intrusive load monitoring (NILM) approaches, with a single model for high-frequency signals.
A reimplementation of Jack Kelly's rectangles neural network architecture based on Keras and the NILMToolkit.
A Synthetic Energy Consumption Dataset for Non-Intrusive Load Monitoring
Undergraduate research by Yuzhe Lim in Spring 2019. Field of research: Deep Neural Networks application on NILM (Nonintrusive load monitoring) for Energy Disaggregation
An ESP32 based plug level electricity meter
Home Assistant integration that estimates per-appliance power and energy from your whole-home power signal, even for appliances with no sensor
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