Editors:
- Provides a guideline manual on how semantic technologies can be applied to solve real-life problems originating in the IoT domain
- Focuses on semantic data representation and extended functionalities of the semantic layered
- Discusses applications of the Internet of Everything concept in real-life solutions
Part of the book series: Studies in Computational Intelligence (SCI, volume 941)
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Table of contents (18 chapters)
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Front Matter
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IoT Data and Interoperability
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Front Matter
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Domain-Specific Applications
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Front Matter
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Problem-Specific Applications
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Front Matter
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About this book
This book is focused on an emerging area, i.e. combination of IoT and semantic technologies, which should enable breaking the silos of local and/or domain-specific IoT deployments.
Taking into account the way that IoT ecosystems are realized, several challenges can be identified. Among them of definite importance are (this list is, obviously, not exhaustive): (i) How to provide common representation and/or shared understanding of data that will enable analysis across (systematically growing) ecosystems? (ii) How to build ecosystems based on data flows? (iii) How to track data provenance? (iv) How to ensure/manage trust? (v) How to search for things/data within ecosystems? (vi) How to store data and assure its quality?
Semantic technologies are often considered among the possible ways of addressing these (and other, related) questions. More precisely, in academic research and in industrial practice, semantic technologies materialize in the following contexts (this list is, also, not exhaustive, but indicates the breadth of scope of semantic technology usability): (i) representation of artefacts in IoT ecosystems and IoT networks, (ii) providing interoperability between heterogeneous IoT artefacts, (ii) representation of provenance information, enabling provenance tracking, trust establishment, and quality assessment, (iv) semantic search, enabling flexible access to data originating in different places across the ecosystem, (v) flexible storage of heterogeneous data. Finally, Semantic Web, Web of Things, and Linked Open Data are architectural paradigms, with which the aforementioned solutions are to be integrated, to provide production-ready deployments.
Editors and Affiliations
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Amity Institute of Information Technology, Amity University Uttar Pradesh Lucknow Campus, Lucknow, India
Rajiv Pandey, Nidhi Srivastava
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Systems Research Institute, Polish Academy of Sciences, Warsaw, Poland
Marcin Paprzycki, Katarzyna Wasielewska-Michniewska
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Database System Laboratory, University of Aizu, Aizu-Wakamatsu, Japan
Subhash Bhalla
Bibliographic Information
Book Title: Semantic IoT: Theory and Applications
Book Subtitle: Interoperability, Provenance and Beyond
Editors: Rajiv Pandey, Marcin Paprzycki, Nidhi Srivastava, Subhash Bhalla, Katarzyna Wasielewska-Michniewska
Series Title: Studies in Computational Intelligence
DOI: https://doi.org/10.1007/978-3-030-64619-6
Publisher: Springer Cham
eBook Packages: Intelligent Technologies and Robotics, Intelligent Technologies and Robotics (R0)
Copyright Information: Springer Nature Switzerland AG 2021
Hardcover ISBN: 978-3-030-64618-9Published: 13 April 2021
Softcover ISBN: 978-3-030-64621-9Published: 14 April 2022
eBook ISBN: 978-3-030-64619-6Published: 12 April 2021
Series ISSN: 1860-949X
Series E-ISSN: 1860-9503
Edition Number: 1
Number of Pages: XX, 415
Number of Illustrations: 163 b/w illustrations, 111 illustrations in colour
Topics: Computational Intelligence, Cyber-physical systems, IoT, Artificial Intelligence, Data Engineering