Bibliographic Details
| Title: |
An Ontology-based Context Model in Intelligent Environments |
| Authors: |
Gu, Tao, Wang, Xiao Hang, Pung, Hung Keng, Zhang, Da Qing |
| Publication Year: |
2020 |
| Collection: |
Computer Science |
| Subject Terms: |
Computer Science - Distributed, Parallel, and Cluster Computing, Computer Science - Artificial Intelligence |
| More Details: |
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.
Comment: arXiv admin note: text overlap with arXiv:0906.3925 by other authors |
| Document Type: |
Working Paper |
| Access URL: |
http://arxiv.org/abs/2003.05055 |
| Accession Number: |
edsarx.2003.05055 |
| Database: |
arXiv |
