Interoperable and adaptive fuzzy services for ambient intelligence applications
ACM Transactions on Autonomous and Adaptive Systems (TAAS)
Learning patterns in ambient intelligence environments: a survey
Artificial Intelligence Review
3PC: System support for adaptive peer-to-peer pervasive computing
ACM Transactions on Autonomous and Adaptive Systems (TAAS) - Special section on formal methods in pervasive computing, pervasive adaptation, and self-adaptive systems: Models and algorithms
Capacitive indoor positioning and contact sensing for activity recognition in smart homes
Journal of Ambient Intelligence and Smart Environments
Behavioural pattern identification and prediction in intelligent environments
Applied Soft Computing
Ambient intelligence for quality of life assessment
Journal of Ambient Intelligence and Smart Environments - Ambient and Smart Component Technologies for Human Centric Computing
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A proactive and ubiquitous computing system in a home environment must operate unobtrusively. This article presents the steps for developing an autonomous home-control system. The system's method uses fuzzy, continuous-time control, online adaptation, and a context-aware intelligent environment. The control and learning methods allow the home to adapt to user routines unobtrusively and smoothly. The adaptation is based on recognizing patterns of human practices, which can change over time. The authors applied these methods to a fuzzy-controlled lighting system in a smart-home laboratory environment. The authors obtained results from both functional and long-term practical tests.