Detecting Swimming Pools in 15-Minute Load Data

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

The ability to detect appliances in load data highly depends on the resolution of the data. While a lot of related work exists on detecting appliances in second or sub-second granularity load data, in this paper, we detect swimming pools through their filter pumps in load data with the 15-minute granularity prescribed by the European Union for smart meters. We model the filter pump based on exemplary measurements and describe a prototypical algorithm to extract the filter pump's consumption from the aggregated mains signal of a real-world household. We evaluate pool detection performance with different classifiers on a data set with 843 households, where the information on the existence of a swimming pool is available. We achieve 94.8% detection accuracy with a precision of 68.5% with an off-the-shelf classifier. Decreasing the temporal resolution in several steps to 8 hours negatively affects the recall while the precision stays at the same level. We find that these results raise privacy concerns even at the minimum temporal resolution of smart meter data that is legally required in the European Union. © 2018 IEEE.
Original languageEnglish
Title of host publication2018 17th IEEE International Conference On Trust, Security And Privacy In Computing And Communications/ 12th IEEE International Conference On Big Data Science And Engineering (TrustCom/BigDataSE)
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages1651-1655
Number of pages5
ISBN (Electronic)978-1-5386-4388-4
ISBN (Print)978-1-5386-4389-1
DOIs
Publication statusPublished - 2018
Event17th IEEE International Conference on Trust, Security and Privacy in Computing and Communications and 12th IEEE International Conference on Big Data Science and Engineering, Trustcom/BigDataSE 2018 - New York, United States
Duration: 1 Aug 20183 Aug 2019

Conference

Conference17th IEEE International Conference on Trust, Security and Privacy in Computing and Communications and 12th IEEE International Conference on Big Data Science and Engineering, Trustcom/BigDataSE 2018
Abbreviated titleTrustcom/BigDataSE 2018
Country/TerritoryUnited States
CityNew York
Period1/08/183/08/19

Keywords

  • privacy
  • Smart metering
  • Classification (of information)
  • Data privacy
  • Lakes
  • Pumps
  • Smart meters
  • Swimming pools
  • Detection accuracy
  • Detection performance
  • European union
  • Privacy concerns
  • Pump-based
  • Related works
  • Temporal resolution
  • Big data

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