REDD: A public data set for energy disaggregation research. Energy and sustainability issues raise a large number of problems that can be tackled using approaches from data mining and machine learning, but traction of such problems has been slow due to the lack of publicly available data. In this paper we present the Reference Energy Disaggregation Data Set (REDD), a freely available data set containing detailed power usage information from several homes, which is aimed at furthering research on energy disaggregation (the task of determining the component appliance contributions from an aggregated electricity signal). We discuss past approaches to disaggregation and how they have influenced our design choices in collecting data, we describe the hardware and software setups for the data collection, and we present initial benchmark disaggregation results using a well-known Factorial Hidden Markov Model (FHMM) technique.
Keywords for this software
References in zbMATH (referenced in 2 articles )
Showing results 1 to 2 of 2.
- Parson, Oliver; Ghosh, Siddhartha; Weal, Mark; Rogers, Alex: An unsupervised training method for non-intrusive appliance load monitoring (2014)
- Johnson, Matthew J.; Willsky, Alan S.: Bayesian nonparametric hidden semi-Markov models (2013)