Semantic interoperability in sensor applications making sense of sensor data

Brandt, Paul; Basten, Twan; Stuiik, Sander; Bui, Vinh; Clercq, Paul de; Pires, Luís Ferreira; Sinderen, Marten van

doi:10.1109/cicare.2013.6583065

Cited by 9 publications

(8 citation statements)

References 24 publications

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“…It aims to acquire context information at real-time using ontological methods by integrating external data such as a meteorological website in order to prevent disease. ContoExam [20] is an ontology developed to address the interoperability problem of sensor networks in the context of e-health domain applications. It contains specific expressions and specifications for medical use as examination vocabulary and expressions.…”

Section: Ontologies For Healthcare Descriptionmentioning

confidence: 99%

Semantic Middleware Architectures for IoT Healthcare Applications

Conchon¹,

Bastide²

2019

Lecture Notes in Computer Science

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The adoption of the Internet of Things (IoT) in healthcare has received considerable interest in the past decade. Indeed, IoT-based solutions are poised to transform how we keep people safe and healthy especially as the demand for solutions to lower healthcare costs increases in the coming years. However, the heterogeneity of the things that can be connected in such environments makes interoperability among them a challenging problem. Moreover, the observations produced by these things are made available with various vocabularies and data formats. This heterogeneity prevents generic solutions from being adopted on a global scale and makes difficult to share and reuse data for other purposes than those for which they were initially set up. In this book chapter, we provide an overview of the different solutions from both technical and semantic perspectives that have been used recently to tackle the interoperability issue in such IoT environments and especially in healthcare domain. We also present an overview of semantic middleware solutions that have combined the technical and semantic techniques for a complete interoperable solution.

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Section: Ontologies For Healthcare Descriptionmentioning

confidence: 99%

Semantic Middleware Architectures for IoT Healthcare Applications

Conchon¹,

Bastide²

2019

Lecture Notes in Computer Science

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“…In [2], it is extended and specialized into two separate aspects, the functional SoC and the semantic SoC. As shown in Figure 2, the functional SoC is represented by three vertical layers and the semantic SoC is represented by four horizontal layers.…”

Section: Semantic Separation Of Concernsmentioning

confidence: 99%

“…With semantic transparency, interoperability with minimized mutual dependence is achieved. Semantic transparency is defined in [2] as the characteristic that the external world is unaware of how each component establishes appropriate local semantics from a globally shared conceptualization (the application ontology), i.e., minimizing syntactical dependencies. The word 'appropriate' is used to reflect the fact that each component will use their own interpretation of a domain conceptualization on behalf of their own purpose.…”

Section: Semantic Transparencymentioning

confidence: 99%

“…In this paper, we present the analysis, design, reference implementation and qualitative evaluation of a semantic layer added to VITRU-VIUS with the purpose to improve the semantic interoperability among sensor networks and applications. We adopt the ontology-based approach of [2], in which the developed ontology on context-aware examinations has the potential of not only supporting correct interpretation of sensor data but also ensuring its appropriate use in accordance with the purpose of a given application. The ontology can be regarded as a vehicle that unifies the data originating from different system components into a universal understanding, thereby achieving interoperability at the semantic level.…”

Section: Introductionmentioning

confidence: 99%

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Semantic Interoperability in Body Area Sensor Networks and Applications

Bui

Brandt

Liu

et al. 2014

Proceedings of the 9th International Conference on Body Area Networks

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Crucial to the success of Body Area Sensor Networks is the flexibility with which stakeholders can share, extend and adapt the system with respect to sensors, data and functionality. The first step is to develop an interoperable platform with explicit interfaces, which takes care of common management tasks. Beyond that, interoperability is defined by semantics. This paper presents the analysis, design, implementation and evaluation of a semantic layer within an existing BASN platform for the purpose of improving the semantic interoperability among sensor networks and applications. We adopt an ontology-based approach but rather than having a single overall ontology, we find that using clear semantic domains and mappings between them improves composability and reduces interoperability problems. We discuss the design choices and a reference implementation on an Android phone and actual sensor devices. We show by a qualitative evaluation that this semantic interoperability indeed provides significant improvements in flexibility.

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“…In general, IoT platforms address syntactical interoperability by adopting standardized serialization formats, such as JSON and the Efficient XML Interchange (EXI) [214]. Several initiatives applied semantic technologies for the IoT [199,[215][216][217] and some targeted the semantic interoperability for IoT platforms within the IoT European Platforms Initiative (IoT-EPI) 71 . The IoT European Research Cluster (IERC) plays a major role for the integration of the solutions produced by these projects, aiming at defining a common vision of these IoT technologies at the European level [218].…”

Section: Semantic Interoperabilitymentioning

confidence: 99%

Semantic model-driven development for IoT interoperability of emergency services

Moreira¹

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Disaster Risk Reduction (DRR) is a systematic approach to analyze potential disasters and reduce their occurrence rate and possible impact. The main DRR component is an Early Warning System (EWS), which is a distributed information system that is able to monitor the physical world and issue warnings if abnormal situations occur. EWSs that use Internet-of-Things (IoT) technologies, so called IoT EWS, are suitable to realize (near) real-time data acquisition, risk detection and message brokering between data sources and information receivers, comprising both humans (e.g., emergency managers) and machines (e.g., sirens). Over the last years, numerous IoT EWSs were developed to monitor different types of hazards. Multi-hazard EWSs are a special class of EWS that can detect different types of situations and, if necessary, react to them. Multi-hazard EWSs require integration of existing EWSs and seamless integration with new EWSs. Interoperability of EWS components is necessary for effective integration, e.g., so that sensors, devices and platforms work with each other and with other EWSs. Although IoT technologies offer possibilities to improve the EWS efficiency and effectiveness, this potential can only be exploited if interoperability challenges are addressed at all levels. In this thesis, we focus on how to improve the semantic interoperability of IoT EWSs. Semantic interoperability refers to the ability of two or more EWSs (or EWS components) to share data elements in a prescribed format (syntax) and precise unambiguous meaning (semantics). From a literature review on semantic IoT EWS approaches, we selected the three major challenges that need to be addressed together: 1) semantic integration of a variety of data sources that make use of different standards, ontologies and data models; 2) near-real-time processing in time-and safety-critical applications; and 3) data analysis for effective situation awareness and decision support. This thesis introduces the "SEmantic Model-driven development for IoT Interoperability of emergenCy serviceS" (SEMIoTICS) framework, which is a holistic approach for semantic IoT EWS. SEMIoTICS consists of a semantic modeldriven architecture that facilitates the application of data representations, model transformations and distributed software components. SEMIoTICS is a framework that can be used to develop interoperable IoT EWSs for different domains, enabling an IoT EWS to act as a cloud-based semantic broker for situation-aware decision support. SEMIoTICS is leveraged by the adoption of ontology-driven conceptual modelling for situation-aware applications, covering both EWS design-time (specification and implementation) and runtime. Furthermore, the SEMIoTICS guides the application of the Findable, Accessible, Interoperable and Reusable (FAIR) data principles, in which the role of standardization is emphasized. SEMIoTICS was validated in the context of the H2020 INTER-IoT project, in which a semantic interoperable IoT EWS was developed to detect accident risks with trucks that deli...

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Semantic interoperability in sensor applications making sense of sensor data

Cited by 9 publications

References 24 publications

Semantic Middleware Architectures for IoT Healthcare Applications

Semantic Middleware Architectures for IoT Healthcare Applications

Semantic Interoperability in Body Area Sensor Networks and Applications

Semantic model-driven development for IoT interoperability of emergency services

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