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, 30 July 2020

NILM 2020 to be held online in November

›
The NILM 2020 Workshop will be a one day online conference held during the week commencing 16 November 2020. The workshop will be jointly o...
Monday, 29 June 2020

DEBS 2020 NILM Grand Challenge

›
The DEBS Grand Challenge is a series of competitions in which both academics and professionals compete with the goal of building faster and ...
Thursday, 4 June 2020

IDEAL Household Energy Dataset released

›
The IDEAL Household Energy Dataset  was recently announced by researchers at the University of Edinburgh. The data set description reads: ...
Monday, 23 March 2020

George Hart's 1984 progress report: "Nonintrusive Appliance Load Data Acquisition Method"

›
Stephen Makonin recently made George Hart's 1984 progress report available, titled " Nonintrusive Appliance Load Data Acquisition ...
Monday, 16 December 2019

From Hive to Bulb

›
Last month I said a slightly sad farewell to many great friends as I left  Hive . The smart home and internet of things fields present some ...
Monday, 11 November 2019

Towards reproducible state-of-the-art energy disaggregation

›
This week Nipun Batra will present a paper which aims to improve the reproducibility of state-of-the-art NILM at BuildSys 2019 in New York...
Wednesday, 6 November 2019

New Slack channel for the NILM community

›
Vicente Masip has set up a Slack channel  for researchers to discuss anything related to NILM. Slack features include: Organised discuss...
‹
›
Home
View web version
Powered by Blogger.