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Reliable state transition detection in off-the-shelf low frequency electric meters

Authors:

Deokwoo Jung,

Athanasios Bamis,

Andreas SavvidesAuthors Info & Claims

BuildSys '11: Proceedings of the Third ACM Workshop on Embedded Sensing Systems for Energy-Efficiency in Buildings

Pages 47 - 48

https://doi.org/10.1145/2434020.2434035

Published: 01 November 2011 Publication History

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Abstract

This poster paper describes a method for estimating the ON/OFF usage profile for appliances inside a home using an off-the-Unlike previous approaches that put their emphasis on the detection of individual events using high frequency sampling, our approach aims to reliably detect sequences of ON/OFF events from traces of less reliable ON/OFF events identified on data from low-frequency sampling. The proposed algorithm is evaluated experimentally using a collection of home appliances.

References

[1]

Energy information administration. us household electricity report. In US Dept of Energy, http://www.eia.gov/emeu/reps/enduse/er01_us_figs.html, 2005.

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[2]

D. Jung and A. Savvides. Estimating building consumption breakdowns using on/off state sensing and incremental sub-meter deployment. In Proceedings of the 8th ACM Conference on Embedded Networked Sensor Systems (SenSys). ACM, 2010.

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[3]

Alan Marchiori, Douglas Hakkarinen, Qi Han, and Lieko Earle. Circuit-level load monitoring for household energy management. IEEE Pervasive Computing, 10:40--48, 2011.

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Index Terms

Reliable state transition detection in off-the-shelf low frequency electric meters
1. Computer systems organization
  1. Embedded and cyber-physical systems
  2. Real-time systems
2. Social and professional topics
  1. Professional topics
    1. Computing and business
      1. Automation

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Published In

BuildSys '11: Proceedings of the Third ACM Workshop on Embedded Sensing Systems for Energy-Efficiency in Buildings

November 2011

87 pages

ISBN:9781450307499

DOI:10.1145/2434020

General Chair:
Antonio Ruzzelli
University College, Dublin, Ireland

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 ACM 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: 01 November 2011

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SenSys '11

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SenSys '11: The 9th ACM Conference on Embedded Network Sensor Systems

November 1, 2011

Washington, Seattle

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Overall Acceptance Rate 148 of 500 submissions, 30%

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Reliable and secure body fall detection algorithm in a wireless mesh network

Activity analysis based on low sample rate smart meters

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