Overview
- Presents the basics of the Internet of Underwater Things (IoUT) architecture and underwater transmission
- Includes applications of machine learning techniques for underwater communication
- Features open challenges in the two perspectives of communication and machine learning for underwater networking
Part of the book series: SpringerBriefs in Computer Science (BRIEFSCOMPUTER)
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Table of contents (6 chapters)
Keywords
About this book
Authors and Affiliations
About the authors
Kaishun Wu received the Ph.D. degree in computer science and engineering from HKUST in 2011. After that, he worked as a Research Assistant Professor with HKUST. In 2013, he joined SZU as a Distinguished Professor. He has coauthored two books and published over 100 high quality research articles in international leading journals and primer conferences, such as IEEE TMC, IEEE TPDS, ACM MobiCom, and IEEE INFOCOM. He is also the inventor of 6 U.S. and over 90 Chinese pending patents. He is a fellow of IET. He received the 2012 Hong Kong Young Scientist Award and the 2014 Hong Kong ICT Awards: Best Innovation and 2014 IEEE ComSoc Asia–Pacific Outstanding Young Researcher Award.
Bibliographic Information
Book Title: Machine Learning Modeling for IoUT Networks
Book Subtitle: Internet of Underwater Things
Authors: Ahmad A. Aziz El-Banna, Kaishun Wu
Series Title: SpringerBriefs in Computer Science
DOI: https://doi.org/10.1007/978-3-030-68567-6
Publisher: Springer Cham
eBook Packages: Computer Science, Computer Science (R0)
Copyright Information: The Author(s), under exclusive license to Springer Nature Switzerland AG 2021
Softcover ISBN: 978-3-030-68566-9Published: 30 May 2021
eBook ISBN: 978-3-030-68567-6Published: 29 May 2021
Series ISSN: 2191-5768
Series E-ISSN: 2191-5776
Edition Number: 1
Number of Pages: XII, 63
Number of Illustrations: 8 b/w illustrations, 24 illustrations in colour
Topics: Communications Engineering, Networks, Control, Robotics, Mechatronics, Artificial Intelligence