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

Report from NILM2014@London on comparing NILM algorithms

The first "NILM in London" workshop was held on Wednesday 3rd September. In this blog post, I'd like to try to summarise the discussion around comparing NILM algorithms.

Report from NILM2014@London on building an online discussion venue and wiki for NILM


The first "NILM in London" workshop was held on Wednesday 3rd September. It was a lot of fun and we had some great conversations. In this blog post, I'd like to try to summarise the discussion around building an online discussion forum for NILM.

NILMTK v0.2 released!!

Hurray! We've released NILMTK v0.2! See this list of improvements on the docs page.

Introducing NILM Metadata: a schema for energy datasets and prior knowledge about appliances

One of our aims with the open-source energy disaggregation toolkit NILMTK is to make it easy to import any of the 10+ NILM datasets currently available. One of the pain points when writing a NILMTK importer for a new dataset is that each dataset uses a different metadata schema and, sometimes, there simply is no metadata associated with some datasets. At best, this means that we have to manually map from the dataset's appliance names to NILMTK's standard appliance names. At worse, it means that it's impossible to unambiguously import the dataset (did that channel really only include the fridge? It sure looks like there are other appliances on there. What's the wiring hierarchy between the mains meter, the circuit meters and the appliance meters? Does that channel record active power or apparent power? What pre-processing has already been applied? etc. etc.)

Post-doc funding

I'm probably still a year or so away from finishing my PhD but I've started to explore funding opportunities for UK computer science post doctoral researchers. (I think I'd really quite like to continue working on energy disaggregation after my PhD; there are still lots of research problems; and we're a very long way from having a robust, open source disaggregation tool for end-users).

Imperial have a 'funding opportunities' web site.

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

Today, Nipun Batra, Jack Kelly and Oliver Parson are really pleased to announce the release of NILMTK: an open source toolkit for non-intrusive load monitoring. The toolkit will allow researchers to easily develop algorithms which disaggregate a household’s total electricity consumption into individual appliances.

Specifically, the toolkit includes:

Non-Intrusive Load Monitoring ToolKit (nilmtk)

Nipun, Oli and I have just started work on an open source toolkit for non-intrusive load monitoring called nilmtk. We're pretty excited about it! It's only in the very, very earliest stages (the code repository currently has precisely zero lines of code in it!) although we've started to flesh out the design on the project's wiki.


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