lon-io / nilm

Non Intrusive Load Monitoring

Non Intrusive Load Monitoring

This project contains source code for NILM algorithms and experiments on the UK-DALE dataset.

Pre-requisites

• Tensorflow
• Numpy
• Pandas
• Matplotlib

Folder structure

• Algos: Actual implementation of the models
  • multi: Multi-appliance models
• lib: Supporting modules
• processing: Notebooks for pre-processing
• experiments: different experiments run
  • exp_generalization: Generalization experiments
  • exp_multi_appliance: Multi-appliance experiments

Usage

• Download the 2017 release of the UK-DALE dataset from https://jack-kelly.com/data/
• Run the processing/processing-enhanced.ipynb file to generate data chunks for house 1
• Run the processing/processing-enhanced-house-2.ipynb file to generate data chunks for house 2
• Run either the experiments/sample-experiment.py file or any of the notebooks experiments in the experiments directory (ideally in a Google Colab environment)