Stream Compression of DLMS Smart Meter Readings

Marcell Fehér, Daniel Enrique Lucani Rötter, Morten Tranberg Hansen, Flemming Enevold Vester

Research output: Contribution to book/anthology/report/proceedingArticle in proceedingsResearchpeer-review

Abstract

Smart electricity meters typically upload power consumption readings once or few times a day. Utility providers aim to increase the upload frequency in order to access consumption information in near real time, but the currently used data compressors fail to provide sufficient savings in this new scenario on the low-bandwidth, high-cost data connection. We propose a new compression method and data format for DLMS smart meter readings, which is significantly better with frequent uploads and makes it feasible to report every reading in near real time with the same or lower data sizes than the currently available compressors in the DLMS protocol.
Original languageEnglish
Title of host publicationICC 2022 - IEEE International Conference on Communications
Number of pages6
PublisherIEEE
Publication date11 Aug 2022
Pages5517-5522
ISBN (Print)978-1-5386-8348-4
ISBN (Electronic)978-1-5386-8347-7
DOIs
Publication statusPublished - 11 Aug 2022
EventICC 2022 - IEEE International Conference on Communications - Republic of Seoul, Korea, -
Duration: 16 May 202222 May 2022

Conference

ConferenceICC 2022 - IEEE International Conference on Communications
Country/Territory-
CityRepublic of Seoul, Korea
Period16/05/202222/05/2022
SeriesIEEE International Conference on Communications
ISSN1550-3607

Keywords

  • Data Compression
  • Generalized Deduplication
  • Smart meter
  • DLMS
  • IoT
  • Compression

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  • Scale-loT

    Lucani Rötter, D. E.

    01/01/201831/12/2022

    Project: Research

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