Non-intrusive load monitoring for multi-objects in smart building

Dandan Li, Jiangfeng Li, Xin Zeng, Vladimir Stankovic, Lina Stankovic, Qingjiang Shi

Research output: Contribution to conferencePaperpeer-review

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Abstract

The rapidly expansion of Internet of Things (IoT) has ignited renewed interest in energy disaggregation via nonintrusive load monitoring (NILM). Compared to the more frequent NILM approach of training one model for each appliance, this paper proposes a multi-label learning approach based on the widely cited sequence2point convolutional neural network (CNN). Using the smart meter readings collected in an office building, we demonstrate the accuracy and practicality of the proposed network compared to start-of-the-art one-to-one NILM models.
Original languageEnglish
Number of pages5
Publication statusPublished - 22 Sep 2021
EventFourth International Balkan Conference on Communications and Networking - Novi Sad, Serbia
Duration: 20 Sep 202122 Sep 2021
Conference number: 4
http://www.balkancom.info/2021/

Conference

ConferenceFourth International Balkan Conference on Communications and Networking
Abbreviated titleBalkancom 2021
Country/TerritorySerbia
CityNovi Sad
Period20/09/2122/09/21
Internet address

Keywords

  • non-intrsuive
  • load monitoring
  • multi-objects
  • smart building

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