Disaggregated Homes

My name is Oliver Parson, and I'm currently employed as a Product Data Science Lead at Octopus. I'm interested in investigating the ways in which machine learning can be used to break down household energy consumption data into individual appliances, also known as Non-intrusive Appliance Load Monitoring (NILM) or energy disaggregation.

Thursday, 22 May 2014

UK energy disaggregation meet-up

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The field of energy disaggregation has expanded so much since I started my PhD in 2010, with new companies and research groups joining the f...
Thursday, 15 May 2014

NILM 2014 workshop schedule released

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The schedule for the NILM 2014 workshop in Austin has just been released. The workshop will include 3 sessions of paper presentations, a s...
Friday, 9 May 2014

Training disaggregation algorithms without sub-metered data

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I'm keen to include an unsupervised disaggregation algorithm (one that doesn't require appliance data for training) in NILMTK . At t...
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Thursday, 1 May 2014

Thesis code release

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Today I'm releasing the code I wrote for the experiments in my thesis. The code includes an implementation of a Bayesian hidden Markov m...
Wednesday, 23 April 2014

Paper accepted at NILM 2014

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My paper titled ' A Scalable Non-intrusive Load Monitoring System for Fridge-Freezer Energy Efficiency Estimation ' was recently acc...
Wednesday, 16 April 2014

Introducing NILMTK: an open source toolkit for non-intrusive load monitoring

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Today, Nipun Batra, Jack Kelly and Oliver Parson are really pleased to announce the release of NILMTK: an open source toolkit for non-intrus...
Thursday, 10 April 2014

Thesis available online

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Today I can finally say that the finished version of my thesis has been submitted and is now available online. Here's the full reference...
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