An Ontology-based Context Model in Intelligent Environments
Gu, Tao, Wang, Xiao Hang, Pung, Hung Keng, Zhang, Da Qing
–arXiv.org Artificial Intelligence
Computing becomes increasingly mobile and pervasive today; these changes imply that applications and services must be aware of and adapt to their changing contexts in highly dynamic environments. Today, building context-aware systems is a complex task due to lack of an appropriate infrastructure support in intelligent environments. A context-aware infrastructure requires an appropriate context model to represent, manipulate and access context information. In this paper, we propose a formal context model based on ontology using OWL to address issues including semantic context representation, context reasoning and knowledge sharing, context classification, context dependency and quality of context. The main benefit of this model is the ability to reason about various contexts. Based on our context model, we also present a Service-Oriented Context-Aware Middleware (SOCAM) architecture for building of context-aware services.
arXiv.org Artificial Intelligence
Mar-6-2020
- Country:
- South America > Brazil
- Rio de Janeiro > Rio de Janeiro (0.04)
- North America > United States
- Texas > Dallas County
- Dallas (0.04)
- Massachusetts > Middlesex County
- Cambridge (0.04)
- Florida > Orange County
- Orlando (0.04)
- Texas > Dallas County
- Europe
- Czechia > Prague (0.04)
- Switzerland > Zürich
- Zürich (0.04)
- Asia
- Singapore > Central Region
- Singapore (0.04)
- China > Heilongjiang Province
- Daqing (0.04)
- Singapore > Central Region
- South America > Brazil
- Genre:
- Research Report (0.40)
- Industry:
- Technology: