An Ontology-based Context Model in Intelligent Environments

TLDR

Computing is increasingly mobile and pervasive, requiring applications to adapt to dynamic contexts, yet building context‑aware systems is complex due to insufficient infrastructure support, underscoring the need for a robust context model that represents, manipulates, and accesses context information. The paper proposes a formal ontology‑based context model using OWL to support semantic representation, reasoning, knowledge sharing, classification, dependency, and quality, and introduces a Service‑Oriented Context‑Aware Middleware (SOCAM) architecture for building context‑aware services. The authors develop the OWL‑based ontology model and implement it within the SOCAM architecture, providing a structured framework for context representation and reasoning. The model’s primary benefit is its ability to reason about diverse contexts.

Abstract

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.