Energy saving in smart homes based on consumer behavior: A case study
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Authors
Author (Corporation)
Publication date
2015
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Type
04B - Conference paper
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Parent work
Proceedings of the 2015 IEEE International Smart Cities Conference
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Volume
Issue / Number
Pages / Duration
1-6
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Publisher / Publishing institution
IEEE
Place of publication / Event location
Guadalajara
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Abstract
This paper presents a case study of a recommender system that can be used to save energy in smart homes without lowering the comfort of the inhabitants. We present an algorithm that mines consumer behavior data only and applies machine learning to suggest actions for inhabitants to reduce the energy consumption of their homes. The system looks for frequent and
periodic patterns in the event data provided by the digitalSTROM home automation system. These patterns are converted into association rules, prioritized and compared with the current behavior of the inhabitants. If the system detects opportunities to save energy without decreasing the comfort level, it sends a recommendation to the inhabitants.
Keywords
save energy, smart homes, reduction of energy consumption
Subject (DDC)
Event
International Smart Cities Conference
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ISBN
978-1-4673-6552-9
978-1-4673-6551-2
978-1-4673-6551-2
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Language
English
Created during FHNW affiliation
Yes
Strategic action fields FHNW
Publication status
Published
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Peer review of the complete publication
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Citation
Zehnder, M., Wache, H., Witschel, H. F., Zanatta, D., & Rodriguez, M. (2015). Energy saving in smart homes based on consumer behavior: A case study. Proceedings of the 2015 IEEE International Smart Cities Conference, 1–6. https://doi.org/10.1109/ISC2.2015.7366231