Ontologies for the internet of things

Hachem, Sara; Teixeira, Thiago; Issarny, Valérie

doi:10.1145/2093190.2093193

Cited by 126 publications

(51 citation statements)

References 17 publications

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“…The Semantic Sensor Network (SSN) ontology [195] provides the most important core vocabulary for sensing data and denes the notion of sensors and physical devices in general. However, several other initials are proposing ontologies for IoT [196,197].…”

Section: Summary Overviewmentioning

confidence: 99%

Application-derived communication protocol selection in M2M platforms for smart cities

Elmangoush

Steinke

Magedanz

et al. 2015

2015 18th International Conference on Intelligence in Next Generation Networks

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Section: Summary Overviewmentioning

confidence: 99%

Application-derived communication protocol selection in M2M platforms for smart cities

Elmangoush

Steinke

Magedanz

et al. 2015

2015 18th International Conference on Intelligence in Next Generation Networks

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“…The minimum required coverage (threshold) is sensor-specific and specified in a knowledge base describing metadata about sensors, actuators, physics, etc. (for more details we refer the reader to [16]). We take two cases into account when computing coverage:…”

Section: Deterministic Registration Solutionmentioning

confidence: 99%

Service-oriented middleware for large-scale mobile participatory sensing

Hachem¹,

Pathak²,

Issarny³

2014

Pervasive and Mobile Computing

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In this paper, we introduce MobIoT, a service-oriented middleware that enables large-scale mobile participatory sensing. Scalability is achieved by limiting the participation of redundant sensing devices. Precisely, MobIoT allows a new device to register its services only if it increases the sensing coverage of a physical attribute, along its expected path, for the set of registered devices. We present the design and implementation of MobIoT, which mobile devices use to determine their registration decision and become accessible for their services. Through experiments performed on real datasets, we show that our solution scales, while meeting sensing coverage requirements.

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“…For example, the unit and semantic type can refer to ontologies of physical concepts and related models (prediction, interpolation or error models) [47].…”

Section: Data Streammentioning

confidence: 99%

Dioptase: a distributed data streaming middleware for the future web of things

Billet

Issarny

2014

J Internet Serv Appl

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The Internet of Things (IoT) is a promising concept toward pervasive computing as it may radically change the way people interact with the physical world, by connecting sensors to the Internet and, at a higher level, to the Web, thereby enacting a Web of Things (WoT). One of the challenges raised by the WoT is the in-network continuous processing of data streams presented by Things, which must be investigated urgently because it affects the future data models of the IoT, and is critical regarding the scalability and the sustainability required by the IoT. This cross-cutting concern has been previously studied in the context of Wireless Sensor Networks (WSN) given the focus on the acquisition and in-network processing of sensed data. However, proposed solutions feature various proprietary and highly specialized technologies that are difficult to integrate and complex to use, which represents a hurdle to their wide deployment. At the other end of the spectrum, cloud-based solutions introduce a too high energy cost for the envisioned IoT scale, considering the energy cost of communication over computation. There is thus a need for a distributed middleware solution for data stream management that leverages existing WSN work, while integrating it with today's Web technologies in order to support the required flexibility and the interoperability of the IoT. Toward that goal, this paper introduces Dioptase, a lightweight Data Stream Management System for the WoT, which aims to integrate the Things and their streams into today's Web by presenting sensors and actuators as Web services. The middleware specifically provides a way to describe complex fully-distributed stream-based mashups and to deploy them dynamically, at any time, as task graphs, over available Things of the network, including resource-constrained ones.

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Ontologies for the internet of things

Cited by 126 publications

References 17 publications

Application-derived communication protocol selection in M2M platforms for smart cities

Application-derived communication protocol selection in M2M platforms for smart cities

Service-oriented middleware for large-scale mobile participatory sensing

Dioptase: a distributed data streaming middleware for the future web of things

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