Machine Learning Modeling for IoUT Networks: Internet of Underwater Things

Machine learning and IoT are used in smart control of underwater environments, with applications in opportunistic communication and localization. Challenges include modeling underwater communication from two perspectives.

Format: Paperback / softback
Length: 63 pages
Publication date: 30 May 2021
Publisher: Springer Nature Switzerland AG

The book delves into the captivating realm of smart control in underwater environments, facilitated by the convergence of machine learning and the Internet of Things (IoT). The authors commence by introducing the fundamental physical characteristics of seawater, laying the foundation for subsequent discussions. They then explore the realm of opportunistic transmission, emphasizing its significance in underwater communication. This is followed by an in-depth exploration of localization and positioning techniques, leveraging machine learning algorithms to enhance accuracy and reliability. The authors further delve into the realm of machine learning modeling for underwater communication, highlighting its potential to revolutionize the field. Additionally, they address the ongoing challenges faced in this domain, drawing from two distinct perspectives: communication engineering and data science.

Furthermore, the book showcases practical applications of machine learning techniques in opportunistic communication and underwater localization. It sheds light on the current challenges associated with machine learning modeling of underwater communication, emphasizing the need for interdisciplinary collaboration and innovative solutions. By examining these topics in depth, the book provides valuable insights into the future of smart control in underwater environments, offering a comprehensive understanding of the interplay between machine learning, IoT, and underwater technology.

The book delves into the captivating realm of smart control in underwater environments, facilitated by the convergence of machine learning and the Internet of Things (IoT). The authors commence by introducing the fundamental physical characteristics of seawater, laying the foundation for subsequent discussions. They then explore the realm of opportunistic transmission, emphasizing its significance in underwater communication. This is followed by an in-depth exploration of localization and positioning techniques, leveraging machine learning algorithms to enhance accuracy and reliability. The authors further delve into the realm of machine learning modeling for underwater communication, highlighting its potential to revolutionize the field. Additionally, they address the ongoing challenges faced in this domain, drawing from two distinct perspectives: communication engineering and data science.

Furthermore, the book showcases practical applications of machine learning techniques in opportunistic communication and underwater localization. It sheds light on the current challenges associated with machine learning modeling of underwater communication, emphasizing the need for interdisciplinary collaboration and innovative solutions. By examining these topics in depth, the book provides valuable insights into the future of smart control in underwater environments, offering a comprehensive understanding of the interplay between machine learning, IoT, and underwater technology.

Weight: 454g
Dimension: 235 x 155 (mm)
ISBN-13: 9783030685669
Edition number: 1st ed. 2021