I'm really looking forward to the conference, and will do my best to update this post with links to papers as they become available.
My name is Oliver Parson, and I'm currently employed as a Senior Data Scientist at Bulb. 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.
Tuesday 1 December 2015
NILM @ GlobalSIP 2015
The 3rd IEEE Global Conference on Signal and Information Processing will be held next month (14-16 December 2015) in Orlando, Florida. I was excited to see quite how many papers in the program are related to energy disaggregation, which are split across two sessions organised as part of the Smart Buildings Symposium and the Inference and Prediction session:
Toward a Semi-Supervised Non-Intrusive Load Monitoring System for Event-based Energy Disaggregation. Karim Said Barsim and Bin Yang (University of Stuttgart, Germany)
A new approach for supervised power disaggregation by using a deep recurrent LSTM network. Lukas Mauch and Bin Yang (University of Stuttgart, Germany)
Blind Non-intrusive Appliance Load Monitoring using Graph-based Signal Processing. Bochao Zhao, Vladimir Stankovic and Lina Stankovic (University of Strathclyde, United Kingdom)
A New Unsupervised Event Detector For Non-Intrusive Load Monitoring. Benjamin Wild, Karim Said Barsim and Bin Yang (University of Stuttgart, Germany)
Dataport and NILMTK: A Building data set Designed for Non-intrusive Load Monitoring. Oliver Parson (University of Southampton, United Kingdom); Grant Fisher and April Hersey (Pecan Street Inc, USA); Nipun Batra (IIIT Delhi, India); Jack Kelly (Imperial College London, United Kingdom); Amarjeet Singh (IIIT-Delhi, India); William J Knottenbelt (Imperial College London, United Kingdom); Alex Rogers (University of Southampton, United Kingdom)
Non-Intrusive Load Monitoring: A Power Consumption Based Relaxation. Kyle Anderson, Jose Moura and Mario Berges (Carnegie Mellon University, USA)
A feasibility study of automated plug-load identification from high-frequency measurements. Jingkun Gao (Carnegie Mellon University, USA); Emre C Kara (Lawrence Berkeley National Laboratory, USA); Suman Giri and Mario Berges (Carnegie Mellon University, USA)
Single-Channel Compressive Sampling of Electrical Data for Non-Intrusive Load Monitoring. Michelle Clark and Lutz Lampe (University of British Columbia, Canada)
Non-Intrusive Load Monitoring of HVAC Components using Signal Unmixing. Alireza Rahimpour (The University of Tennessee at Knoxville, USA); Hairong Qi (the University of Tennessee, USA)
Subscribe to:
Post Comments (Atom)
Very interesting post
ReplyDeleteThanks!
DeleteHi Oli, do you know where I can find PDFs of these papers? I've searched the IEEE Digital Library and Google Scholar for some but no joy at all.
ReplyDeleteHi Jack, I'm afraid I don't know of a central repository for the GlobalSIP papers, but I'll do my best to update this post with links as the papers become available!
Delete