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Live stream of London NILM Workshop on Weds 8th July

It's almost time for the London NILM Workshop!

We'll be live streaming the event via a Google Hangout On Air. The stream will start at 10:00 BST (UTC+1), but do keep an eye on NILM_Workshop on Twitter for any new links if we encounter technical difficulties on the day!

Announcing the 2015 European NILM workshop

The Second European Workshop on Non-intrusive Load Monitoring will be held on 8th July 2015 at Imperial College London. More details on Oli's blog.

UK-DALE paper is now published in NPG's Scientific Data's journal

Nature Publishing Group has a new(ish) journal called Scientific Data. Today Scientific Data published our paper "The UK-DALE dataset, domestic appliance-level electricity demand and whole-house demand from five UK homes". And, a few days ago, our dataset received the first data DOI from the UK Energy Research Council's Energy Data Centre (UKERC EDC): DOI:10.5286/UKERC.EDC.000001.

Energy disaggregation online discussion forum

I've finally gotten round to putting together an online discussion forum for energy disaggregation! Feel free to join! Also, while we're finding our feet with this Google Group, please feel free to discuss the Google Group settings on the Energy Disaggregation forum.

Updated version of our UK-DALE dataset paper

Here's an updated version of our UK-DALE dataset paper. It will be on arXiv on Tuesday. Let me know if you spot any typos!

This new version adds 8 figures and a large table describing the dataset. And this update adds a fifth house and data from House 1 up to Jan 5th 2015 ;).

NILMTK Survey

We've seen some really encouraging adoption of NILMTK (our open-source toolkit for non-intrusive load monitoring) since we started work on it a year ago. However, it's quite hard to keep track of how people our using the toolkit, what features they'd like to see, and what direction the toolkit should be heading in. For this reason, we've created a NILMTK Survey, which will hopefully solve these problems. Please fill out the survey if you have any interest in energy disaggregation research, and let us know what's important to you. Thanks!

(this post was written by Oli Parson, and cross-posted from Oli's blog)

MSc project proposal: An online competition for comparing energy disaggregation algorithms

A sizeable challenge in the energy disaggregation community is that of comparing NILM algorithms from different researchers. In other words, if we have two papers, and one paper reports an accuracy of 80%, and another reports an accuracy of 85% then we cannot infer that the second paper is better because the authors used different datasets, different pre-processing etc. Hence we are working on a project proposal for the consideration of Imperial Computer Science MSc students. If a group of students selects the project then they'll work on it for the duration of next term. Here's the full, draft project specification. Comments most welcome!

NILMTK v0.2 wins best demo at BuildSys 2014; and demo is online

Oli Parson and Nipun Batra (my two awesome collaborators on the core of our open source energy disaggregation framework NILMTK) have just attended BuildSys 2014 in Memphis. Oli presented NILMTK v0.2 as a demo and it won best demo! Hurray! Well done Oli for doing an excellent presentation. The demo is an IPython notebook and is available to view online: NILMTK v0.2 BuildSys demo. Also, you can read more about energy disaggregation at BuildSys on Oli's blog.

Make machine learning easy enough for kids to use in their creations (MSc group project proposal)

The aim of this project is to make sophisticated machine learning tools so easy to use that kids (and adults with little knowledge of computer science) can use machine learning algorithms in their creations. The approach is to wrap machine learning tools as simple ‘building blocks’ which can be bolted together with existing rapid prototyping tools to allow users to quickly throw together sophisticated inventions. e.g. Lego robots which can classify objects using a video camera, or can understand natural speech, or learn some task through trial and error (e.g. balancing on one leg). Full (draft) spec here

16kHz recordings of voltage and current for whole home for >1 year available

Our 'UK Domestic Appliance-Level Electricity (UK-DALE)' dataset was released earlier this year (here's our paper on the dataset). Up until now, the data available consisted of data recorded every second (for the whole house power demand of two houses) or recorded every six seconds (for all appliance-level data and the whole-house demand for all four houses). But I also recorded voltage and current at 16kHz for two houses. I have finally gotten round to figuring out how to put almost 4 TBytes of data online.

The 16kHz signal is compressed as FLAC and is available in 1 hour chunks (each chunk is about 200 MBytes in size). You can download it using anonymous FTP. Details here under the section 'The full 16 kHz dataset via FTP'.

And, while we're on the topic of updates to UK-DALE, a little while ago I updated the metadata for UK-DALE to bring it into line with the new NILM Metadata v0.2 schema, and I also updated the NILMTK converter for UK-DALE.

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