The Hierarchical Hidden Markov Model: Analysis and Applications
Machine Learning
Issues in Developing Context-Aware Computing
HUC '99 Proceedings of the 1st international symposium on Handheld and Ubiquitous Computing
A Framework for Developing Mobile, Context-aware Applications
PERCOM '04 Proceedings of the Second IEEE International Conference on Pervasive Computing and Communications (PerCom'04)
A service-oriented middleware for building context-aware services
Journal of Network and Computer Applications
An infrastructure approach to context-aware computing
Human-Computer Interaction
Feature fusion-based multiple people tracking
PCM'05 Proceedings of the 6th Pacific-Rim conference on Advances in Multimedia Information Processing - Volume Part I
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In this paper, we present an Ontology-based Context-aware multi-Agent Service System(OCASS) architecture to provide these context-aware services in a smart home. To model various contexts, we design Ontology which supports to share context knowledge, detect and resolve inconsistency of the knowledge. In addition, we classify context-aware services into three layers – Session, Task, Subtask – to make sure definition of service conflict problems and to solve the problems easily. With our context model and the classification of service conflicts, our system supports autonomic tasks including recognizing and learning user’s formal/informal activity pattern, and resolving conflicts between services in different situations of users invisibly.