Non-Intrusive Load Monitoring Toolkit (nilmtk)
A curated resources of awesome NILM resources
Deep Neural Networks Applied to Energy Disaggregation
Code for NILM experiments using Neural Networks. Uses Keras/Tensorflow and the NILMTK.
A repository of awesome Non-Intrusive Load Monitoring(NILM) with code.
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
[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
Non-Intrusive Load Monitoring (NILM) for Home Assistant. Estimate appliance activity and energy usage from a whole-home power sensor, all locally.
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
In this repository are available codes in python for implementation of classification of loads and event detection using PLAID dataset
To associate your repository with the nilm topic, visit your repo's landing page and select "manage topics."