Description: Artificial Intelligence-based Internet of Things Systems

Artificial Intelligence-based Internet of Things Systems [E-Book] / edited by Souvik Pal, Debashis De, Rajkumar Buyya.

The book discusses the evolution of future generation technologies through Internet of Things (IoT) in the scope of Artificial Intelligence (AI). The main focus of this volume is to bring all the related technologies in a single platform, so that undergraduate and postgraduate students, researchers,...

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Personal Name(s):	Buyya, Rajkumar, editor
	De, Debashis, editor / Pal, Souvik, editor
Edition:	1st edition 2022.
Imprint:	Cham : Springer, 2022
Physical Description:	XVII, 509 pages 167 illustrations, 119 illustrations in color (online resource)
Note:	englisch
ISBN:	9783030870591
DOI:	10.1007/978-3-030-87059-1
Series Title:	Internet of Things, Technology, Communications and Computing
Subject (LOC):	Application software. Cooperating objects (Computer systems). Telecommunication.

The book discusses the evolution of future generation technologies through Internet of Things (IoT) in the scope of Artificial Intelligence (AI). The main focus of this volume is to bring all the related technologies in a single platform, so that undergraduate and postgraduate students, researchers, academicians, and industry people can easily understand the AI algorithms, machine learning algorithms, and learning analytics in IoT-enabled technologies. This book uses data and network engineering and intelligent decision support system-by-design principles to design a reliable AI-enabled IoT ecosystem and to implement cyber-physical pervasive infrastructure solutions. This book brings together some of the top IoT-enabled AI experts throughout the world who contribute their knowledge regarding different IoT-based technology aspects. Addresses the complete functional framework workflow in AI-enabled IoT ecosystem; Presents intelligent object identification and object discovery through the IoT ecosystem and its implications to the real world; Explores security and privacy issues and trustworthy machine learning related to data-intensive technologies in AI-based IoT ecosystems.