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, 25 February 2016

Is deep learning the future of NILM?

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Deep learning has recently revolutionised a number of well-studied machine learning and signal processing problems , such as image recogni...
2 comments:
Thursday, 18 February 2016

NILM 2016 registration and paper submission now open

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The 3rd International Workshop on Non-Intrusive Load Monitoring (NILM 2016) will be held in Vancouver, Canada from 14-15th May 2016, a...
Wednesday, 27 January 2016

PNNL NILM User Group

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The Pacific Northwest National Laboratory (PNNL) has set up on online NILM user group  via the Conduit platform. The user group consists of...
Wednesday, 20 January 2016

EPRI's 2015 NILM workshop

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The  Electric Power Research Institute (EPRI) has been a long term research player in the field of NILM since beginning development of NIAL...
Thursday, 7 January 2016

REFIT analysis using NILMTK converter

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I recently wrote a NILMTK converter for the REFIT data set , which allowed me to do a quick piece of analysis over the data set which I wan...
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Wednesday, 6 January 2016

From Southampton to London

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This week I finally said goodbye to Southampton as I started my new full-time role as a Data Scientist at British Gas Connected Homes. I...
Tuesday, 29 December 2015

3rd Int’l Workshop on NILM — SAVE THE DATE!

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The 3rd International Workshop on Non-Intrusive Load Monitoring (NILM) will be held in Vancouver, Canada from May 14 to 15, 2016. The ve...
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