Last week I had the pleasure of being an examiner for Nguyen Kien Trung's PhD thesis at the Université Nice Sophia Antipolis. Kien's thesis focused on a an efficient electricity disaggregation algorithm which he deployed using a low-cost system-on-chip. Kien successfully defended his thesis against the panel's questions, which sometimes came in a mixture of English and French, which I found particularly very impressive!
I also managed a brief visit to Qualisteo's office, who demonstrated some the disaggregation algorithms they're applying across a range of built environments, including the Eiffel Tower, a motorway tunnel and a sports stadium. I had a great time, but hopefully my next trip to Nice will last a little longer than 24 hours!
Dear Oliver,
ReplyDeleteI have already downloaded your thesis entitled "unsupervised training....smart meter data". I am looking in my Master thesis to work over HMM for energy disaggregation when we have multiple appliances. The objective is to specify the best algorithm for this. This is why i was wondering wether you can provide me with a source code for training and appliance recognition with a method based on HMM...Thank you!
You can find links to my code from the publications page of my website: http://www.oliverparson.co.uk/publications
DeleteHope this helps!