A Comprehensive Ontology for Internet of Things (COIoT)

Tayur, Varun M; Suchithra, R

doi:10.1109/icaccp.2019.8882936

Cited by 15 publications

(9 citation statements)

References 10 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Connecting the domains of device monitoring and IoT, Ryabinin et al demonstrate an ontology-based approach to manage and monitor resource-constrained Edge Computing devices [54]. The Comprehensive Ontology for IoT (COIoT) tries to build an interoperable knowledge base for IoT environments by reusing core concepts from existing ontologies and adds additional concepts to support the monitoring of context and services [55].…”

Section: Monitoring Ontologiesmentioning

confidence: 99%

Enabling Efficient Semantic Stream Processing Across the IoT Network Through Adaptive Distribution with DIVIDE

De Brouwer,

De Turck,

Ongenae

2024

J Netw Syst Manage

View full text Add to dashboard Cite

In the Internet of Things (IoT), semantic IoT platforms are often used to solve the challenges associated with the real-time integration of heterogeneous IoT sensor data, domain knowledge and context information. Existing platforms mostly have a static distribution and configuration of queries deployed on the platform's stream processing components. In contrast, the environmental context in which queries are deployed has a very dynamic nature: real-world set-ups involve varying tasks, device resource usage, networking conditions, etc. To solve this mismatch, this paper presents DIVIDE, an IoT platform component built on Semantic Web technologies. DIVIDE has a generic design containing multiple subcomponents that monitor the environment across a cascading architecture. By monitoring the use case context, DIVIDE adaptively derives the appropriate stream processing queries in a context-aware way. Using a Local Monitor deployed on edge devices, situational context parameters are measured and aggregated. The Meta Model allows modeling these measurements, and meta-information about devices and deployed stream processing queries. Through the definition of application-specific Global Monitor queries that are continuously evaluated centrally on the Meta Model, end users can dynamically configure how the situational context should influence the window parameter configuration and distribution of queries in the network. The paper evaluates a first implementation of DIVIDE on a homecare monitoring use case. The results show how DIVIDE can successfully adapt to varying device and networking conditions, taking into account the use case requirements. This way, DIVIDE allows better balancing use case specific trade-offs and achieves more efficient stream processing.

show abstract

Section: Monitoring Ontologiesmentioning

confidence: 99%

Enabling Efficient Semantic Stream Processing Across the IoT Network Through Adaptive Distribution with DIVIDE

De Brouwer,

De Turck,

Ongenae

2024

J Netw Syst Manage

View full text Add to dashboard Cite

show abstract

“…Some of the recent research on IoT ontologies delivered the unified ontology aiming to achieve semantic interoperability among heterogeneous testbeds [33]; the IoT-Stream lightweight ontology for data stream analytics and event detection [34]; the COIoT comprehensive ontology by reusing core concepts from existing ontologies and complementing concepts like policy, context, services and monitoring [35]; the evaluation method for ontologies verification and validation by using evaluation tools that detect errors by diagnosing various metrics and pitfalls [36]; the IoT architecture for virtual IoT devices and their semantic framework deployed at the edge of network and able to aggregate capabilities of IoT devices and derive new services by inference [37].…”

Section: Ontologies For Internet Of Thingsmentioning

confidence: 99%

Towards Ontology-Based Requirements Engineering for IoT-Supported Well-Being, Aging and Health

Belani¹,

Šolić²,

Perković³

2022

2022 IEEE 30th International Requirements Engineering Conference Workshops (REW)

View full text Add to dashboard Cite

Ontologies serve as a one of the formal means to represent and model knowledge in computer science, electrical engineering, system engineering and other related disciplines. Ontologies within requirements engineering may be used for formal representation of system requirements. In the Internet of Things, ontologies may be used to represent sensor knowledge and describe acquired data semantics. Designing an ontology comprehensive enough with an appropriate level of knowledge expressiveness, serving multiple purposes, from system requirements specifications to modeling knowledge based on data from IoT sensors, is one of the great challenges. This paper proposes an approach towards ontology-based requirements engineering for well-being, aging and health supported by the Internet of Things. Such an ontology design does not aim at creating a new ontology, but extending the appropriate one already existing, SAREF4EHAW, in order align with the well-being, aging and health concepts and structure the knowledge within the domain. Other contributions include a conceptual formulation for Well-Being, Aging and Health and a related taxonomy, as well as a concept of One Well-Being, Aging and Health. New attributes and relations have been proposed for the new ontology extension, along with the updated list of use cases and particular ontological requirements not covered by the original ontology. Future work envisions full specification of the new ontology extension, as well as structuring system requirements and sensor measurement parameters to follow description logic.

show abstract

“…The Hydra project 2 adopts OWL (i.e., an ontology language for Semantic Web) and SAWSDL (i.e., a semantic annotation of WSDL) to semantically annotate IoT services. A number of ontologies have been proposed to represent IoT resources and services including Ontology Web Language for Things (OWL-T) [20], IoT-Lite Ontology [1], Comprehensive Ontology for IoT (COIoT) [41] and IoT-Stream [10]. The Sensor Modeling Language SensorML which is a part of the OGC sensor Web enablement suite of standards, supports semantic descriptions of IoT services based on standardized XML tags.…”

Section: Iot Services Discoverymentioning

confidence: 99%

An Internet of Things Service Roadmap

Bouguettaya

Sheng

Benatallah

et al. 2021

Preprint

View full text Add to dashboard Cite

We propose a roadmap for leveraging the tremendous opportunities the Internet of Things (IoT) has to offer. We argue that the combination of the recent advances in service computing and IoT technology provide a unique framework for innovations not yet envisaged, as well as the emergence of yet-to-be-developed IoT applications. This roadmap covers: emerging novel IoT services, articulation of major research directions, and suggestion of a roadmap to guide the IoT and service computing community to address key IoT service challenges.

show abstract

A Comprehensive Ontology for Internet of Things (COIoT)

Cited by 15 publications

References 10 publications

Enabling Efficient Semantic Stream Processing Across the IoT Network Through Adaptive Distribution with DIVIDE

Enabling Efficient Semantic Stream Processing Across the IoT Network Through Adaptive Distribution with DIVIDE

Towards Ontology-Based Requirements Engineering for IoT-Supported Well-Being, Aging and Health

An Internet of Things Service Roadmap

Contact Info

Product

Resources

About