Principles of Internet of Things (IoT) Ecosystem: Insight Paradigm (Hardcover, 1st ed. 2020)

This book discusses the evolution of future-generation technologies through the Internet of things, bringing together all the related technologies on a single platform to offer valuable insights for undergraduate and postgraduate students, researchers, academics and industry practitioners. The book uses data, network engineering and intelligent decision- support system-by-design principles to design a reliable IoT-enabled ecosystem and to implement cyber-physical pervasive infrastructure solutions. It takes readers on a journey that begins with understanding the insight paradigm of IoT-enabled technologies and how it can be applied. It walks readers through engaging with real-time challenges and building a safe infrastructure for IoT-based, future-generation technologies. The book helps researchers and practitioners to understand the design architecture through IoT and the state of the art in IoT countermeasures. It also highlights the differences between heterogeneous platforms in IoT-enabled infrastructure and traditional ad hoc or infrastructural networks, and provides a comprehensive discussion on functional frameworks for IoT, object identification, IoT domain model, RFID technology, wearable sensors, WBAN, IoT semantics, knowledge extraction, and security and privacy issues in IoT-based ecosystems. Written by leading international experts, it explores IoT-enabled insight paradigms, which are utilized for the future benefit of humans. It also includes references to numerous works. Divided into stand-alone chapters, this highly readable book is intended for specialists, researchers, graduate students, designers, experts, and engineers involved in research on healthcare-related issues.

General

Imprint:	Springer Nature Switzerland AG
Country of origin:	Switzerland
Series:	Intelligent Systems Reference Library, 174
Release date:	2020
First published:	2020
Editors:	Sheng-Lung Peng • Souvik Pal • Lianfen Huang
Dimensions:	235 x 155mm (L x W)
Format:	Hardcover
Pages:	626
Edition:	1st ed. 2020
ISBN-13:	978-3-03-033595-3
Categories:	Books > Computing & IT > Applications of computing > Artificial intelligence > General
LSN:	3-03-033595-X
Barcode:	9783030335953

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