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Information 2016, 7(2), 35; doi:10.3390/info7020035

User in the Loop: Adaptive Smart Homes Exploiting User Feedback—State of the Art and Future Directions

University of Lille, F-59000 Lille and Mines Douai, URIA, F-90508 Douai, France
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Academic Editors: Sugam Sharma and Anna Fensel
Received: 12 April 2016 / Revised: 17 May 2016 / Accepted: 3 June 2016 / Published: 15 June 2016
(This article belongs to the Special Issue Smart Home)
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Abstract

Due to the decrease of sensor and actuator prices and their ease of installation, smart homes and smart environments are more and more exploited in automation and health applications. In these applications, activity recognition has an important place. This article presents a general architecture that is responsible for adapting automation for the different users of the smart home while recognizing their activities. For that, semi-supervised learning algorithms and Markov-based models are used to determine the preferences of the user considering a combination of: (1) observations of the data that have been acquired since the start of the experiment and (2) feedback of the users on decisions that have been taken by the automation. We present preliminarily simulated experimental results regarding the determination of preferences for a user. View Full-Text
Keywords: smart homes; user-centered decision making; Markov decision process smart homes; user-centered decision making; Markov decision process
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This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. (CC BY 4.0).

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Karami, A.B.; Fleury, A.; Boonaert, J.; Lecoeuche, S. User in the Loop: Adaptive Smart Homes Exploiting User Feedback—State of the Art and Future Directions. Information 2016, 7, 35.

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