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Machine learning modeling for IoUT n...

Aziz El-Banna, Ahmad A.

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Machine learning modeling for IoUT networks = internet of underwater things /

Record Type:	Electronic resources : Monograph/item
Title/Author:	Machine learning modeling for IoUT networks/ by Ahmad A. Aziz El-Banna, Kaishun Wu.
Reminder of title:	internet of underwater things /
Author:	Aziz El-Banna, Ahmad A.
other author:	Wu, Kaishun.
Published:	Cham :Springer International Publishing : : 2021.,
Description:	xii, 63 p. :ill. (some col.), digital ;24 cm.
[NT 15003449]:	Introduction -- Seawater's Key Physical Variables -- Opportunistic Transmission -- Localization and Positioning -- ML Modeling for Underwater Communication -- Open Challenges -- Conclusion.
Contained By:	Springer Nature eBook
Subject:	Machine learning. -
Online resource:	https://doi.org/10.1007/978-3-030-68567-6
ISBN:	9783030685676

Machine learning modeling for IoUT networks = internet of underwater things /
Aziz El-Banna, Ahmad A.

Machine learning modeling for IoUT networksinternet of underwater things /[electronic resource] :by Ahmad A. Aziz El-Banna, Kaishun Wu. - Cham :Springer International Publishing :2021. - xii, 63 p. :ill. (some col.), digital ;24 cm. - SpringerBriefs in computer science,2191-5768. - SpringerBriefs in computer science..

Introduction -- Seawater's Key Physical Variables -- Opportunistic Transmission -- Localization and Positioning -- ML Modeling for Underwater Communication -- Open Challenges -- Conclusion.

This book discusses how machine learning and the Internet of Things (IoT) are playing a part in smart control of underwater environments, known as Internet of Underwater Things (IoUT) The authors first present seawater's key physical variables and go on to discuss opportunistic transmission, localization and positioning, machine learning modeling for underwater communication, and ongoing challenges in the field. In addition, the authors present applications of machine learning techniques for opportunistic communication and underwater localization. They also discuss the current challenges of machine learning modeling of underwater communication from two communication engineering and data science perspectives.

ISBN: 9783030685676

Standard No.: 10.1007/978-3-030-68567-6doiSubjects--Topical Terms:

533906
Machine learning.

LC Class. No.: Q325.5 / .A95 2021

Dewey Class. No.: 006.31

Machine learning modeling for IoUT networks = internet of underwater things /
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100 1 $a Aziz El-Banna, Ahmad A. $3 3495462
245 1 0 $a Machine learning modeling for IoUT networks $h [electronic resource] : $b internet of underwater things / $c by Ahmad A. Aziz El-Banna, Kaishun Wu.
260 $a Cham : $b Springer International Publishing : $b Imprint: Springer, $c 2021.
300 $a xii, 63 p. : $b ill. (some col.), digital ; $c 24 cm.
490 1 $a SpringerBriefs in computer science, $x 2191-5768
505 0 $a Introduction -- Seawater's Key Physical Variables -- Opportunistic Transmission -- Localization and Positioning -- ML Modeling for Underwater Communication -- Open Challenges -- Conclusion.
520 $a This book discusses how machine learning and the Internet of Things (IoT) are playing a part in smart control of underwater environments, known as Internet of Underwater Things (IoUT) The authors first present seawater's key physical variables and go on to discuss opportunistic transmission, localization and positioning, machine learning modeling for underwater communication, and ongoing challenges in the field. In addition, the authors present applications of machine learning techniques for opportunistic communication and underwater localization. They also discuss the current challenges of machine learning modeling of underwater communication from two communication engineering and data science perspectives.
650 0 $a Machine learning. $3 533906
650 0 $a Internet of things. $3 2057703
650 0 $a Underwater acoustic telemetry. $3 1097249
650 1 4 $a Communications Engineering, Networks. $3 891094
650 2 4 $a Control, Robotics, Mechatronics. $3 1002220
650 2 4 $a Artificial Intelligence. $3 769149
700 1 $a Wu, Kaishun. $3 2059213
710 2 $a SpringerLink (Online service) $3 836513
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