Computer
MavHome: An Agent-Based Smart Home
PERCOM '03 Proceedings of the First IEEE International Conference on Pervasive Computing and Communications
Creating an Ambient-Intelligence Environment Using Embedded Agents
IEEE Intelligent Systems
Improved Gait Recognition by Gait Dynamics Normalization
IEEE Transactions on Pattern Analysis and Machine Intelligence
A framework for context-aware applications for smart spaces
NEW2AN'11/ruSMART'11 Proceedings of the 11th international conference and 4th international conference on Smart spaces and next generation wired/wireless networking
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One of the major limitations of Ambient Intelligent systems today is the lack of semantic models in human behavior and the environment, so that the system can recognize the specific activity being performed by the users and act accordingly. In this context, we address the general problem of knowledge representation in Smart Spaces. In order to monitor and act over human behavior in intelligent environments, we design a sufficiently simple and flexible visual language to be managed by non-expert users, thus facilitating the programming of the environment. The prototype of the visual language serves to represent rules about human behavior to provide the Smart Space with more usability. These rules can be mapped into SPARQL queries and rule subscriptions. In addition, we add support to represent imprecise and fuzzy knowledge. The proposed general-domain language can help managing resource allocation, assisting people with special needs, in remote monitoring and other domains.