The ECO data set and the performance of non-intrusive load monitoring algorithms
By Christian Beckel, Wilhelm Kleiminger, Romano Cicchetti, Thorsten Staake, Silvia Santini. International Conference on Systems for Energy-Efficient Built Environments, 2014
348 citations recorded by the source corpus.
Subfields: Building and Construction, Electrical and Electronic Engineering
View Paper: https://www.semanticscholar.org/paper/e914d493e8f18e1223c8698a3eab8c1f26c03ffe
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In Electrical and Electronic Engineering
Citations in the corpus
- MacroBase: Prioritizing Attention in Fast Data (2016, methodology): “MacroBase can also detect temporal behaviors via feature transformation, which we demonstrate using a dataset of 16M points capturing a month of electricity usage from devices within a household [12].”
- Two Is Not Enough: Privacy Assessment of Aggregation Schemes in Smart Metering (2017, background): “Name Origin Households LPs/Hh Resolution Dataport [32] US 707 647 15 min Redd [31] US 5 7 1 s AMPds [33] Canada 1 726 1 min ECO [34, 35] Switzerland 6 192 1 min UCI [36] France 1 1358 1 min GOVAU [37] Australia 31 406 30 min UMASS [38] US 376 1 1 min”
- MacroBase: Analytic Monitoring for the Internet of Things (2016, methodology): “ies. MacroBase can also detect temporal behaviors via feature transformation, which we demonstrate using a dataset of 16M points capturing a month of electricity usage from devices within a household [12]. We augment MDP by adding a sequence of feature transforms that i:) partition the stream by dev”