15 research outputs found

    A Survey on the Web of Things

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    The Web of Things (WoT) paradigm was proposed first in the late 2000s, with the idea of leveraging Web standards to interconnect all types of embedded devices. More than ten years later, the fragmentation of the IoT landscape has dramatically increased as a consequence of the exponential growth of connected devices, making interoperability one of the key issues for most IoT deployments. Contextually, many studies have demonstrated the applicability of Web technologies on IoT scenarios, while the joint efforts from the academia and the industry have led to the proposals of standard specifications for developing WoT systems. Through a systematic review of the literature, we provide a detailed illustration of the WoT paradigm for both researchers and newcomers, by reconstructing the temporal evolution of key concepts and the historical trends, providing an in-depth taxonomy of software architectures and enabling technologies of WoT deployments and, finally, discussing the maturity of WoT vertical markets. Moreover, we identify some future research directions that may open the way to further innovation on WoT systems

    General ontology for internet of things (goiot) to achieve semantic interoperability using sensor, observation, sample and actuator (sosa) approach

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    Internet of Things (IoT) devices are increasing day by day, thus a common vocabulary is required to make sure these devices from a different manufacturer can communicate with each other by themselves known as semantic interoperability. Ontology is required to solve the semantic interoperability problem of the IoT. Ontology provides a base to represent objects in a specific domain. Classes, Instances, and Relationships are the components required to built ontology. Problems with existing IoT ontologies are as follows: (i) Incomplete IoT Concepts; (ii) Most of the Existing IoT ontologies did not includes all critical elements of IoT; (iii) The existing ontologies are not built on the latest ontology language standard recommended by W3C which is Web Ontology Language (OWL); (iv) The IoT ontologies in literature did not follow any Evaluation Measurement such as Reasoner. The objective of this research is to study the existing literature about IoT and Ontology and their relationship. Then to develop and evaluate GoIoT by using Protégé and pallet reasoner respectively. The methodology is divided into three portions which are Analysis, Development and Implementation, and Evaluation and Measurements. In the analysis part, basic concepts of IoT and Ontology are discussed. In Development and Implementation, SOSA is adopted to create a new ontology, namely GoIoT. It talks about the existing reused IoT concept and how new IoT concepts are further integrated. Further, it discusses which language and tools are used to build this ontology. The newly constructed GoIoT is evaluated via semantic reasoner and experts. The reasoner results showed zero error in GoIoT ontology which simply means that no issue is found among ontology components. Five (5) experts have also evaluated ontology in terms of nine (9) evaluation criteria. The mean value of five (5) expert combine is 83.059 % and this value shows that the Ontology developed can be accepted as Ontology that represent General Ontology for IOT

    Governance of Autonomous Agents on the Web: Challenges and Opportunities

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    International audienceThe study of autonomous agents has a long tradition in the Multiagent System and the Semantic Web communities, with applications ranging from automating business processes to personal assistants. More recently, the Web of Things (WoT), which is an extension of the Internet of Things (IoT) with metadata expressed in Web standards, and its community provide further motivation for pushing the autonomous agents research agenda forward. Although representing and reasoning about norms, policies and preferences is crucial to ensuring that autonomous agents act in a manner that satisfies stakeholder requirements, normative concepts, policies and preferences have yet to be considered as first-class abstractions in Web-based multiagent systems. Towards this end, this paper motivates the need for alignment and joint research across the Multiagent Systems, Semantic Web, and WoT communities, introduces a conceptual framework for governance of autonomous agents on the Web, and identifies several research challenges and opportunities

    Applications of ontology in the internet of things: A systematic analysis

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    Ontology has been increasingly implemented to facilitate the Internet of Things (IoT) activities, such as tracking and information discovery, storage, information exchange, and object addressing. However, a complete understanding of using ontology in the IoT mechanism remains lacking. The main goal of this research is to recognize the use of ontology in the IoT process and investigate the services of ontology in IoT activities. A systematic literature review (SLR) is conducted using predefined protocols to analyze the literature about the usage of ontologies in IoT. The following conclusions are obtained from the SLR. (1) Primary studies (i.e., selected 115 articles) have addressed the need to use ontologies in IoT for industries and the academe, especially to minimize interoperability and integration of IoT devices. (2) About 31.30% of extant literature discussed ontology development concerning the IoT interoperability issue, while IoT privacy and integration issues are partially discussed in the literature. (3) IoT styles of modeling ontologies are diverse, whereas 35.65% of total studies adopted the OWL style. (4) The 32 articles (i.e., 27.83% of the total studies) reused IoT ontologies to handle diverse IoT methodologies. (5) A total of 45 IoT ontologies are well acknowledged, but the IoT community has widely utilized none. An in-depth analysis of different IoT ontologies suggests that the existing ontologies are beneficial in designing new IoT ontology or achieving three main requirements of the IoT field: interoperability, integration, and privacy. This SLR is finalized by identifying numerous validity threats and future directions

    Interactive Experience Design: Integrated and Tangible Storytelling with Maritime Museum Artefacts

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    Museums play the role of intermediary between cultural heritage and visitors, and are often described as places and environments for education and enjoyment. The European Union also encourages innovative uses of museums to support education through the cultural heritage resources. However, the importance of visitors’ active role in museums as places for education and entertainment, on the one hand, and the growing and indispensable presence of technology in the cultural heritage domain, on the other hand, provided the initial ideas to develop the research. This thesis, presents the study and design for an interactive storytelling installation for a maritime museum. The installation is designed to integrate different museum artefacts into the storytelling system to enrich the visitors experience through tangible storytelling. The project was conducted in collaboration with another PhD student, Luca Ciotoli. His contribution was mainly focused on the narrative and storytelling features of the research, while my contribution was focused on the interaction- and technology-related features, including the design and implementation of the prototype. The research is deployed using a four-phase iterative approach. The first phase of the research, Study, deals with literature review and different studies to identify the requirements. The second phase, Design, determines the broad outlines of the project i.e., an interactive storytelling installation. The design phase includes interaction and museum experience design. We investigated different design approaches, e.g., interaction and museum experience design, to develop a conceptual design. The third phase, prototype, allows us to determine how to fulfill the tasks and meet the requirements that are established for the research. Prototyping involves content creation, storyboarding, integrating augmented artefacts into the storytelling system. Th final phase, test, refers to the evaluations that are conducted during the aforementioned phases e.g., formative and the final usability testing with users. The outcome of the research confirms previous results in the literature about how digital narratives can be enriched with the tangible dimension, moreover it shows how this dimension can enable to communicate stories and knowledge of the past that are complex, such as the art of navigating in the past, by integrating tangible objects that play different roles in the storytelling process

    Next Generation Internet of Things – Distributed Intelligence at the Edge and Human-Machine Interactions

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    This book provides an overview of the next generation Internet of Things (IoT), ranging from research, innovation, development priorities, to enabling technologies in a global context. It is intended as a standalone in a series covering the activities of the Internet of Things European Research Cluster (IERC), including research, technological innovation, validation, and deployment.The following chapters build on the ideas put forward by the European Research Cluster, the IoT European Platform Initiative (IoT–EPI), the IoT European Large-Scale Pilots Programme and the IoT European Security and Privacy Projects, presenting global views and state-of-the-art results regarding the next generation of IoT research, innovation, development, and deployment.The IoT and Industrial Internet of Things (IIoT) are evolving towards the next generation of Tactile IoT/IIoT, bringing together hyperconnectivity (5G and beyond), edge computing, Distributed Ledger Technologies (DLTs), virtual/ andaugmented reality (VR/AR), and artificial intelligence (AI) transformation.Following the wider adoption of consumer IoT, the next generation of IoT/IIoT innovation for business is driven by industries, addressing interoperability issues and providing new end-to-end security solutions to face continuous treats.The advances of AI technology in vision, speech recognition, natural language processing and dialog are enabling the development of end-to-end intelligent systems encapsulating multiple technologies, delivering services in real-time using limited resources. These developments are focusing on designing and delivering embedded and hierarchical AI solutions in IoT/IIoT, edge computing, using distributed architectures, DLTs platforms and distributed end-to-end security, which provide real-time decisions using less data and computational resources, while accessing each type of resource in a way that enhances the accuracy and performance of models in the various IoT/IIoT applications.The convergence and combination of IoT, AI and other related technologies to derive insights, decisions and revenue from sensor data provide new business models and sources of monetization. Meanwhile, scalable, IoT-enabled applications have become part of larger business objectives, enabling digital transformation with a focus on new services and applications.Serving the next generation of Tactile IoT/IIoT real-time use cases over 5G and Network Slicing technology is essential for consumer and industrial applications and support reducing operational costs, increasing efficiency and leveraging additional capabilities for real-time autonomous systems.New IoT distributed architectures, combined with system-level architectures for edge/fog computing, are evolving IoT platforms, including AI and DLTs, with embedded intelligence into the hyperconnectivity infrastructure.The next generation of IoT/IIoT technologies are highly transformational, enabling innovation at scale, and autonomous decision-making in various application domains such as healthcare, smart homes, smart buildings, smart cities, energy, agriculture, transportation and autonomous vehicles, the military, logistics and supply chain, retail and wholesale, manufacturing, mining and oil and gas

    Next Generation Internet of Things – Distributed Intelligence at the Edge and Human-Machine Interactions

    Get PDF
    This book provides an overview of the next generation Internet of Things (IoT), ranging from research, innovation, development priorities, to enabling technologies in a global context. It is intended as a standalone in a series covering the activities of the Internet of Things European Research Cluster (IERC), including research, technological innovation, validation, and deployment.The following chapters build on the ideas put forward by the European Research Cluster, the IoT European Platform Initiative (IoT–EPI), the IoT European Large-Scale Pilots Programme and the IoT European Security and Privacy Projects, presenting global views and state-of-the-art results regarding the next generation of IoT research, innovation, development, and deployment.The IoT and Industrial Internet of Things (IIoT) are evolving towards the next generation of Tactile IoT/IIoT, bringing together hyperconnectivity (5G and beyond), edge computing, Distributed Ledger Technologies (DLTs), virtual/ andaugmented reality (VR/AR), and artificial intelligence (AI) transformation.Following the wider adoption of consumer IoT, the next generation of IoT/IIoT innovation for business is driven by industries, addressing interoperability issues and providing new end-to-end security solutions to face continuous treats.The advances of AI technology in vision, speech recognition, natural language processing and dialog are enabling the development of end-to-end intelligent systems encapsulating multiple technologies, delivering services in real-time using limited resources. These developments are focusing on designing and delivering embedded and hierarchical AI solutions in IoT/IIoT, edge computing, using distributed architectures, DLTs platforms and distributed end-to-end security, which provide real-time decisions using less data and computational resources, while accessing each type of resource in a way that enhances the accuracy and performance of models in the various IoT/IIoT applications.The convergence and combination of IoT, AI and other related technologies to derive insights, decisions and revenue from sensor data provide new business models and sources of monetization. Meanwhile, scalable, IoT-enabled applications have become part of larger business objectives, enabling digital transformation with a focus on new services and applications.Serving the next generation of Tactile IoT/IIoT real-time use cases over 5G and Network Slicing technology is essential for consumer and industrial applications and support reducing operational costs, increasing efficiency and leveraging additional capabilities for real-time autonomous systems.New IoT distributed architectures, combined with system-level architectures for edge/fog computing, are evolving IoT platforms, including AI and DLTs, with embedded intelligence into the hyperconnectivity infrastructure.The next generation of IoT/IIoT technologies are highly transformational, enabling innovation at scale, and autonomous decision-making in various application domains such as healthcare, smart homes, smart buildings, smart cities, energy, agriculture, transportation and autonomous vehicles, the military, logistics and supply chain, retail and wholesale, manufacturing, mining and oil and gas

    A Multi-Stakeholder Information Model to Drive Process Connectivity In Smart Buildings

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    Smart buildings utilise IoT technology to provide stakeholders with efficient, comfortable, and secure experiences. However, previous studies have primarily focused on the technical aspects of it and how it can address specific stakeholder requirements. This study adopts socio-technical theory principles to propose a model that addresses stakeholders' needs by considering the interrelationship between social and technical subsystems. A systematic literature review and thematic analysis of 43 IoT conceptual frameworks for smart building studies informed the design of a comprehensive conceptual model and IoT framework for smart buildings. The study's findings suggest that addressing stakeholder requirements is essential for developing an information model in smart buildings. A multi-stakeholder information model integrating multiple stakeholders' perspectives enhances information sharing and improves process connectivity between various systems and subsystems. The socio-technical systems framework emphasises the importance of considering technical and social aspects while integrating smart building systems for seamless operation and effectiveness. The study's findings have significant implications for enhancing stakeholders' experience and improving operational efficiency in commercial buildings. The insights from the study can inform smart building systems design to consider all stakeholder requirements holistically, promoting process connectivity in smart buildings. The literature analysis contributed to developing a comprehensive IoT framework, addressing the need for holistic thinking when proposing IoT frameworks for smart buildings by considering different stakeholders in the building

    2013 Doctoral Workshop on Distributed Systems

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    The Doctoral Workshop on Distributed Systems was held at Les Plans-sur-Bex, Switzerland, from June 26-28, 2013. Ph.D. students from the Universities of Neuchâtel and Bern as well as the University of Applied Sciences of Fribourg presented their current research work and discussed recent research results. This technical report includes the extended abstracts of the talks given during the workshop
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