Leveraging context-awareness for Internet of Things ecosystem: Representation, organization, and management of context

Present-day devices are becoming increasingly smarter than their predecessors. From a simple passive light switch to an intelligent wristwatch, great strides have been made in networking smart devices, creating an autonomous ecosystem, the so-called Internet of Things. In an increasingly information-driven world, context-awareness supports the intended applications as well as their constituent devices, making them conscious of and adaptive to the specific scenario in real-time. Moreover, heterogeneous devices in the Internet of Things ecosystem peruse disparate data formats and semantics, giving rise to interoperability and information sharing challenges. Context modeling is a core feature that facilitates interoperability and information sharing between applications. Although generic context models exist, they do not consider pertinent dimensions of context to provide a generic vocabulary, and therefore, they cannot be extended to generalize situations commonly encountered in the Internet of Things environment. An extensible, generic modeling and representation of context is required to manage pertinent context dimensions in various ecosystems by being dynamically aware of the situation. This paper presents Context Model for Internet of Things, an extensible and generic ontology-based context modeling approach that provides relevant information at the right time. This work encompasses Context Ontology for Internet of Things, an ontology-based context organization approach, which provides an abstract and overarching vocabulary that fosters knowledge reusability and sharing. The proposed model has been implemented and evaluated with a use case to validate its adaptability, effectiveness, and viability. Our evaluation based on generality, effectiveness, and consistency shows that the proposed model can effectively represent, organize, and manage the context in different Internet of Things ecosystems