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Machine Learning Paradigm for Internet of Things Applications
book

Machine Learning Paradigm for Internet of Things Applications

by Shalli Rani, R. Maheswar, G. R. Kanagachidambaresan, Sachin Ahuja, Deepali Gupta
March 2022
Intermediate to advanced
304 pages
7h 38m
English
Wiley-Scrivener
Content preview from Machine Learning Paradigm for Internet of Things Applications

13Internet of Underwater Things: Challenges, Routing Protocols, and ML Algorithms

Monika Chaudhary, Nitin Goyal* and Aadil Mushtaq

Chitkara University Institute of Engineering and Technology, Chitkara University, Punjab, India

Abstract

The Internet of Underwater Things (IoUT) is the system of intelligent linked underwater things and a diverse kind of Internet of Things (IoT). IoUT is expected to permit different practicable requests, similar to ecological monitor, underwater examination, and calamity prohibition. With these uses, IoUT is considered unique of the likely technology around developed intelligent towns. To help the idea of IoUT, Underwater Wireless Sensor Networks (UWSNs) have appeared as an auspicious network system. UWSNs have various special characteristics, such a longer propagation delay, small bandwidth, and miserable reliability. This chapter presents challenges that can occur in IoUT. Also, the existing routing protocols for effective communication are discussed in great detail here. IoUT empowers a system of autonomous underwater vehicles (AUV) interconnecting with each other, detecting, collecting, and communicating data to sink node. Then, this data can be helpful in wide range of applications like ship wreckage detection, early discovery of tsunamis, marine health observing, as well as gathering real-time oceanic info. This chapter focuses on the complete terminology of IoUT including its basic concept, architectural requirements, challenges, routing ...

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Publisher Resources

ISBN: 9781119760474Purchase Link