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

• Main Authors: Abir B. Karami, Anthony Fleury, Jacques Boonaert, Stéphane Lecoeuche
• Format: Article
• Language: English
• Published: MDPI AG 2016-06-01
• Series: Information
• Subjects: smart homes; user-centered decision making; Markov decision process
• Online Access: http://www.mdpi.com/2078-2489/7/2/35
• ISSN: 2078-2489

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.