Modeling context and situations in pervasive computing environments

TL;DR

This paper introduces RoCoMO, a comprehensive ontology for modeling complex situations in pervasive computing environments, addressing limitations of previous models by including provenance, security, and interoperability features.

Contribution

The paper presents a novel, flexible context ontology called RoCoMO that enhances situation modeling with features like provenance, security, and multiple context representations.

Findings

RoCoMO effectively models complex situations in pervasive environments.

The ontology supports provenance, security, and interoperability.

Case study demonstrates practical utility of RoCoMO.

Abstract

In pervasive computing environments, various entities often have to cooperate and integrate seamlessly in a \emph{situation} which can, thus, be considered as an amalgamation of the context of several entities interacting and coordinating with each other, and often performing one or more activities. However, none of the existing context models and ontologies address situation modeling. In this paper, we describe the design, structure and implementation of a generic, flexible and extensible context ontology called Rover Context Model Ontology (RoCoMO) for context and situation modeling in pervasive computing systems and environments. We highlight several limitations of the existing context models and ontologies, such as lack of provision for provenance, traceability, quality of context, multiple representation of contextual information, as well as support for security, privacy and interoperability, and explain how we are addressing these limitations in our approach. We also illustrate the applicability and utility of RoCoMO using a practical and extensive case study.