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User profiling and micro-accounting for smart energy management

Published: 11 November 2013 Publication History

Abstract

Energy management, and in particular its efficient optimization, is one of the hot trends in the current days, both at the enterprise level (optimization of whole corporate/government buildings) and single-citizens' homes. Energy efficiency is generally function of out-door techniques -- renewable energy, smart energy production and distribution, etc. -- and in-door techniques; in particular, very few energy managers -- each of us can be an energy manager of his own home - can state "who, when and why is consuming", conversely this knowledge is fundamental in order to diminish wasting of energy. Recent studies show that the energy wasted in the overall consumption is about the 30% of the total amount; examples of potential energy wasting are printers and PCs on during the night, status LED of different devices (TV, set-top-box, etc.) and/or lights, lights during normal day-light time, etc.

References

[1]
M. Caruso, C. Ilban, F. Leotta, M. Mecella, and S. Vassos. Synthesizing daily life logs through gaming and simulation. In Proceedings of 2nd Workshop on Recent Advances in Behavior Prediction and Pro-Active Pervasive Computing (AwareCast 2013), 2013.
[2]
C. Chen and D. J. Cook. Energy outlier detection in smart environments. Artificial Intelligence and Smarter Living, 11:07, 2011.
[3]
P. Rashidi and D. J. Cook. Keeping the resident in the loop: Adapting the smart home to the user. Systems, Man and Cybernetics, Part A: Systems and Humans, IEEE Transactions on, 39(5):949--959, 2009.

Cited By

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  • (2014)On the Black-Box Stand-by Recognition Strategies in Smart Homes EnvironmentsProceedings of the 2014 12th IEEE International Conference on Embedded and Ubiquitous Computing10.1109/EUC.2014.40(221-226)Online publication date: 26-Aug-2014

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cover image ACM Conferences
SenSys '13: Proceedings of the 11th ACM Conference on Embedded Networked Sensor Systems
November 2013
443 pages
ISBN:9781450320276
DOI:10.1145/2517351
Permission to make digital or hard copies of part or all 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 third-party components of this work must be honored. For all other uses, contact the Owner/Author.

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Association for Computing Machinery

New York, NY, United States

Publication History

Published: 11 November 2013

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Author Tags

  1. activity recognition
  2. energy saving
  3. micro-accounting
  4. smart spaces

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SenSys '13 Paper Acceptance Rate 21 of 123 submissions, 17%;
Overall Acceptance Rate 174 of 867 submissions, 20%

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  • (2014)On the Black-Box Stand-by Recognition Strategies in Smart Homes EnvironmentsProceedings of the 2014 12th IEEE International Conference on Embedded and Ubiquitous Computing10.1109/EUC.2014.40(221-226)Online publication date: 26-Aug-2014

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