poster

SURF and SURF-PI: a file format and API for non-intrusive load monitoring public datasets

Authors:

Lucas Pereira,

Nuno Nunes,

Mario BergésAuthors Info & Claims

e-Energy '14: Proceedings of the 5th international conference on Future energy systems

Pages 225 - 226

https://doi.org/10.1145/2602044.2602078

Published: 11 June 2014 Publication History

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Abstract

In this paper we propose a common file format and API for public Non-Intrusive Load Monitoring (NILM) datasets such that researchers can easily evaluate their approaches across the different datasets and benchmark their results against prior work. The proposed file format enables storing the power demand of the whole house along with individual appliance consumption, and other relevant metadata in a single compact file, whereas the API supports the creation and manipulation of individual files and datasets in the proposed format.

References

[1]

G. Hart, "Nonintrusive appliance load monitoring," Proc. IEEE, vol. 80, no. 12, 1992.

Google Scholar

[2]

Z. Kolter and M. Johnson, "REDD: A public data set for energy disaggregation research," SustKDD '11.

Google Scholar

[3]

K. Anderson et al., "BLUED: A Fully Labeled Public Dataset for Event-Based Non-Intrusive Load Monitoring Research," SustKDD '12.

Google Scholar

[4]

Electric Power Research Institute, "Non-Intrusive Load Monitoring (NILM) Technologies for End-Use Load Disaggregation: Laboratory Evaluation I." {Online}. Available: http://tinyurl.com/kloo5wq.

Google Scholar

[5]

N. Batra et al., "NILMTK: An Open Source Toolkit for Non-intrusive Load Monitoring," e-Energy '14.

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Cited By

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Pereira LVelosa NPereira M(2022)A data model and file format to represent and store high frequency energy monitoring and disaggregation datasetsScientific Reports10.1038/s41598-022-14517-y12:1Online publication date: 18-Jun-2022
https://doi.org/10.1038/s41598-022-14517-y
Kriechbaumer TJorde DJacobsen H(2019)Waveform Signal Entropy and Compression Study of Whole-Building Energy DatasetsProceedings of the Tenth ACM International Conference on Future Energy Systems10.1145/3307772.3328285(58-67)Online publication date: 15-Jun-2019
https://dl.acm.org/doi/10.1145/3307772.3328285
Pereira LRibeiro MNunes N(2017)Engineering and deploying a hardware and software platform to collect and label non-intrusive load monitoring datasets2017 Sustainable Internet and ICT for Sustainability (SustainIT)10.23919/SustainIT.2017.8379791(1-9)Online publication date: Dec-2017
https://doi.org/10.23919/SustainIT.2017.8379791
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Index Terms

SURF and SURF-PI: a file format and API for non-intrusive load monitoring public datasets
1. Software and its engineering
  1. Software notations and tools
    1. Software libraries and repositories

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Information & Contributors

Information

Published In

e-Energy '14: Proceedings of the 5th international conference on Future energy systems

June 2014

326 pages

ISBN:9781450328197

DOI:10.1145/2602044

General Chairs:
Jon Crowcroft
University of Cambridge, UK
,
Richard Penty
University of Cambridge, UK
,
Program Chairs:
Jean-Yves Le Boudex
EPFL, Switzerland
,
Prashant Shenoy
University of Massachusetts, Amherst, USA

Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than the author(s) must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected].

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Association for Computing Machinery

New York, NY, United States

Publication History

Published: 11 June 2014

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e-Energy '14

Sponsor:

SIGCOMM

e-Energy '14: The Fifth International Conference on Future Energy Systems

June 11 - 13, 2014

Cambridge, United Kingdom

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e-Energy '14 Paper Acceptance Rate 23 of 112 submissions, 21%;

Overall Acceptance Rate 160 of 446 submissions, 36%

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E-Energy '25

Sponsor:
sigenergy

The 16th ACM International Conference on Future and Sustainable Energy Systems

June 17 - 20, 2025

Rotterdam , Netherlands

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Cited By

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Pereira LVelosa NPereira M(2022)A data model and file format to represent and store high frequency energy monitoring and disaggregation datasetsScientific Reports10.1038/s41598-022-14517-y12:1Online publication date: 18-Jun-2022
https://doi.org/10.1038/s41598-022-14517-y
Kriechbaumer TJorde DJacobsen H(2019)Waveform Signal Entropy and Compression Study of Whole-Building Energy DatasetsProceedings of the Tenth ACM International Conference on Future Energy Systems10.1145/3307772.3328285(58-67)Online publication date: 15-Jun-2019
https://dl.acm.org/doi/10.1145/3307772.3328285
Pereira LRibeiro MNunes N(2017)Engineering and deploying a hardware and software platform to collect and label non-intrusive load monitoring datasets2017 Sustainable Internet and ICT for Sustainability (SustainIT)10.23919/SustainIT.2017.8379791(1-9)Online publication date: Dec-2017
https://doi.org/10.23919/SustainIT.2017.8379791
Pereira LNunes N(2015)Semi-automatic labeling for public non-intrusive load monitoring datasets2015 Sustainable Internet and ICT for Sustainability (SustainIT)10.1109/SustainIT.2015.7101378(1-4)Online publication date: Apr-2015
https://doi.org/10.1109/SustainIT.2015.7101378
Pereira LNunes N(2015)Towards systematic performance evaluation of non-intrusive load monitoring algorithms and systems2015 Sustainable Internet and ICT for Sustainability (SustainIT)10.1109/SustainIT.2015.7101373(1-3)Online publication date: Apr-2015
https://doi.org/10.1109/SustainIT.2015.7101373

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