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.

Monday, 10 April 2017

Jack's NILM Competition Survey

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Jack Kelly  recently published the results  of a survey which he designed to assess the appetite for a NILM competition. The survey covers ...
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Tuesday, 3 January 2017

COOLL dataset released

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The COOLL dataset was recently released by researchers at the PRISME laboratory at the University of Orléans, which contains high-frequency...
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Friday, 4 November 2016

Energy Futures Lab talk at Imperial College London

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I gave a talk at the Energy Futures Lab at Imperial College London this afternoon, which covered some of the data products which my team at...
Monday, 31 October 2016

Machine learning & the connected home: useful data or meaningless noise?

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Later this week I'll be giving a talk at the Energy Futures Lab on the recent work we've been doing around the data collected from...
Thursday, 20 October 2016

EPRI EU NILM 2016 review

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"NILM is a challenging problem. But it’s not impossible." This was one of Prof Bin Yang's five concluding messages of his keyn...
Monday, 17 October 2016

EPRI EU NILM 2016 livestream

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The stream of day 1 of the EPRI EU NILM workshop is now live: http://youtu.be/4RARHKiSg08 Update 21.10.2016: A playlist of individual pr...
Tuesday, 27 September 2016

A competition for energy disaggregation algorithms

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Cross-posted from Jack Kelly's blog : Now that I've (finally!) submitted my PhD thesis, I can focus on designing and implementing ...
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