Semantic IoT: Theory and Applications
Pandey, Rajiv|Paprzycki, Marcin|Srivastava, Nidhi|Bhalla, Subhash|Wasielewska-Michniewska, Katarzyna
Language: English
Published by Springer International Publishing, 2021
Series: Book 35 of 538 - Studies in Computational Intelligence
- Hardcover
- New
Seller: moluna, Greven, Germanymoluna
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Condition: New
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Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Provides a guideline manual on how semantic technologies can be applied to solve real-life problems originating in the IoT domainFocuses on semantic data representation and extended functionalities of the semantic layeredDiscusses applicati.
Seller Inventory # 458551410
- Title
- Semantic IoT: Theory and Applications
- Author
- Pandey, Rajiv|Paprzycki, Marcin|Srivastava, Nidhi|Bhalla, Subhash|Wasielewska-Michniewska, Katarzyna
- Publisher
- Springer International Publishing
- Publication year
- 2021
- Condition
- New
- Binding
- Gebunden
- Language
- English
- ISBN 10
- 3030646181
- ISBN 13
- 9783030646189
- Series
- Book 35 of 538: Studies in Computational Intelligence
- Seller catalogs
- Mathematik/Naturwissenschaften/Technik/Medizin
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.
"Synopsis" may belong to another edition of this title.
From the Back Cover
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.
"About the title" may belong to another edition of this title.
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