[Paper Review] An Ontology-based Context Model in Intelligent Environments

Tao Gu, Xiao Hang Wang+2 more|arXiv (Cornell University)|Mar 6, 2020

Context-Aware Activity Recognition Systems16 references453 citations

TL;DR

Introduces an ontology-based context model using OWL to represent, reason about, and share context in intelligent environments, and presents the SOCAM middleware.

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.

Motivation & Objective

• Motivate the need for a robust context model in mobile and pervasive environments.
• Propose a formal ontology-driven context model (OWL-based) to represent and manage context.
• Address semantic representation, context reasoning, knowledge sharing, classification, dependency, and quality of context.
• Show how the model supports building context-aware services via a middleware architecture.

Proposed method

• Develop a formal context model grounded in ontology and implemented with OWL.
• Address semantic context representation, reasoning capabilities, knowledge sharing mechanisms, and quality of context.
• Define context classification and dependency concepts within the ontology.
• Propose the Service-Oriented Context-Aware Middleware (SOCAM) architecture to build context-aware services.

Experimental results

Research questions

• RQ1 How can contexts in intelligent environments be represented semantically using an ontology?
• RQ2 How can reasoning be performed over context to support dynamic adaptation?
• RQ3 How can a middleware architecture (SOCAM) enable service-oriented, context-aware applications?

Key findings

• The ontology-based model enables reasoning about diverse contexts.
• A SOCAM architecture is proposed for constructing context-aware services.
• The model supports context classification, dependencies, and quality of context for better service adaptation.
• The approach facilitates knowledge sharing of context information across components and services.