Identification of TV Channel Watching from Smart Meter Data Using Energy Disaggregation

Pascal A. Schirmer, Iosif Mporas and Akbar Sheikh-Akbari
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Pascal A. Schirmer: Communications Intelligent Systems Group, School of Engineering and Computer Science, University of Hertfordshire, Hatfield AL10 9AB, UK
Iosif Mporas: Communications Intelligent Systems Group, School of Engineering and Computer Science, University of Hertfordshire, Hatfield AL10 9AB, UK
Akbar Sheikh-Akbari: Engineering and Computing, School of Built Environment, Leeds Beckett University, Leeds LS1 3HE, UK

Energies, 2021, vol. 14, issue 9, 1-16

Abstract: Smart meters are used to measure the energy consumption of households. Specifically, within the energy consumption task, a smart meter must be used for load forecasting, the reduction in consumer bills as well as the reduction in grid distortions. Smart meters can be used to disaggregate the energy consumption at the device level. In this paper, we investigated the potential of identifying the multimedia content played by a TV or monitor device using the central house’s smart meter measuring the aggregated energy consumption from all working appliances of the household. The proposed architecture was based on the elastic matching of aggregated energy signal frames with 20 reference TV channel signals. Different elastic matching algorithms, which use symmetric distance measures, were used with the best achieved video content identification accuracy of 93.6% using the MVM algorithm.

Keywords: video content identification; smart meters; load disaggregation (search for similar items in EconPapers)
JEL-codes: Q Q0 Q4 Q40 Q41 Q42 Q43 Q47 Q48 Q49 (search for similar items in EconPapers)
Date: 2021
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (1)

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