2015/03/24 by Preeti Bhargava, Bhargava, Preeti, Shivsubramani Krishnamoorthy +3
Computer Science · Engineering · #Artificial Intelligence (cs.AI) #Computers and Society (cs.CY) #Context-Aware Activity Recognition Systems #Data Management and Algorithms #FOS: Computer and information sciences #Human-Computer Interaction (cs.HC) #Robotics and Automated Systems
paper · pdf · doi:10.48550/arxiv.1503.07159
openalex publication_date 2015/03/24 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/28
In pervasive computing environments, various entities often have to cooperate and integrate seamlessly in a 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.