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Fog-enabled intelligent IoT systems

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Fog-enabled intelligent IoT systems

Record Type:	Electronic resources : Monograph/item
Title/Author:	Fog-enabled intelligent IoT systemsby Yang Yang .. [et al.].
other author:	Yang, Yang.
Published:	Cham :Springer International Publishing :2020.
Description:	xviii, 217 p. :ill. (some col.), digital ;24 cm.
Contained By:	Springer eBooks
Subject:	Internet of things.
Online resource:	https://doi.org/10.1007/978-3-030-23185-9
ISBN:	9783030231859$q(electronic bk.)

Fog-enabled intelligent IoT systems
Fog-enabled intelligent IoT systems[electronic resource] /by Yang Yang .. [et al.]. - Cham :Springer International Publishing :2020. - xviii, 217 p. :ill. (some col.), digital ;24 cm.

Introduction -- IoT technologies and applications -- Fog computing architecture and technologies -- Challenges and solutions for cross-domain applications -- Fog-enabled intelligent transportation system -- Fog-enabled smart home and user behavior recognition -- Fog-enabled industrial 4.0 -- Fog-enabled wireless network self-optimization -- Conclusion.

This book first provides a comprehensive review of state-of-the-art IoT technologies and applications in different industrial sectors and public services. The authors give in-depth analyses of fog computing architecture and key technologies that fulfill the challenging requirements of enabling computing services anywhere along the cloud-to-thing continuum. Further, in order to make IoT systems more intelligent and more efficient, two fog-enabled frameworks with detailed technical approaches are proposed for realistic application scenarios with no or limited priori domain knowledge, i.e. physical laws, system statuses, operation principles and execution rules. Based on these fog-enabled frameworks, a series of data-driven self-learning applications in different industrial sectors and public services are investigated and discussed, such as Intelligent Transportation System, Smart Home, Industrial 4.0, Wireless Network Self-Optimization, and User Behavior Recognition. Finally, the advantages and future directions of fog-enabled intelligent IoT systems are summarized in terms of service flexibility, scalability, quality, maintainability, cost efficiency, as well as latency. Provides a comprehensive review of state-of-the-art IoT technologies and applications in different industrial sectors and public services Presents a fog-enabled service architecture with detailed technical approaches for realistic cross-domain application scenarios with limited prior domain knowledge Outlines a series of data-driven self-learning applications (with new algorithms) in different industrial sectors and public services.

ISBN: 9783030231859$q(electronic bk.)

Standard No.: 10.1007/978-3-030-23185-9doiSubjects--Topical Terms:

670954
Internet of things.

LC Class. No.: QA76.585

Dewey Class. No.: 004.6782

Fog-enabled intelligent IoT systems
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245 0 0 $a Fog-enabled intelligent IoT systems $h [electronic resource] / $c by Yang Yang .. [et al.].
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505 0 $a Introduction -- IoT technologies and applications -- Fog computing architecture and technologies -- Challenges and solutions for cross-domain applications -- Fog-enabled intelligent transportation system -- Fog-enabled smart home and user behavior recognition -- Fog-enabled industrial 4.0 -- Fog-enabled wireless network self-optimization -- Conclusion.
520 $a This book first provides a comprehensive review of state-of-the-art IoT technologies and applications in different industrial sectors and public services. The authors give in-depth analyses of fog computing architecture and key technologies that fulfill the challenging requirements of enabling computing services anywhere along the cloud-to-thing continuum. Further, in order to make IoT systems more intelligent and more efficient, two fog-enabled frameworks with detailed technical approaches are proposed for realistic application scenarios with no or limited priori domain knowledge, i.e. physical laws, system statuses, operation principles and execution rules. Based on these fog-enabled frameworks, a series of data-driven self-learning applications in different industrial sectors and public services are investigated and discussed, such as Intelligent Transportation System, Smart Home, Industrial 4.0, Wireless Network Self-Optimization, and User Behavior Recognition. Finally, the advantages and future directions of fog-enabled intelligent IoT systems are summarized in terms of service flexibility, scalability, quality, maintainability, cost efficiency, as well as latency. Provides a comprehensive review of state-of-the-art IoT technologies and applications in different industrial sectors and public services Presents a fog-enabled service architecture with detailed technical approaches for realistic cross-domain application scenarios with limited prior domain knowledge Outlines a series of data-driven self-learning applications (with new algorithms) in different industrial sectors and public services.
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