Underwater Information Perception and Processing Via Underwater Sensor Networks

Meiqin Liu, Ronghao Zheng, Senlin Zhang (Autoren)

Buch | Hardcover

391 Seiten

2024 | 2024 ed.
Springer Nature (Verlag)
978-981-97-4668-2 (ISBN)

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This book highlights the latest advances and trends in information perception and processing of underwater sensor networks (USNs). Underwater sensor networks are networks of autonomous sensor nodes distributed over a given region of water to collaboratively perform a given task. Nearly 70% of the Earth's surface is covered by water, mainly oceans, and more than 80% of the ocean remains unexplored. The emergence of USNs is a new direction in ocean exploration and data collection. USNs offer many applications in both civilian and non-civilian fields. However, due to the characteristics of underwater environments, USNs face challenges such as limited bandwidth, high propagation delay, media access control, routing, resource utilization, power limitation, etc. Researchers have studied and provided many techniques over the past decades to address these issues.

This book systematically summarizes the development and covers a wide range of applications of USNs, including mobile node localization, target detection, target recognition, target tracking, sensor scheduling, and environmental monitoring. It also focuses on the introduction of new technologies, including deep reinforcement learning, into underwater information perception and processing.

This book is suitable for university lecturers, graduate students, and industry professionals working in the field of USNs.

Meiqin Liu received the B.E. and Ph.D. degrees in control theory and control engineering from Central South University, Changsha, China, in 1994 and 1999, respectively. She was Post-Doctoral Research Fellow with the Huazhong University of Science and Technology, Wuhan, China, from 1999 to 2001. She was Visiting Scholar with the University of New Orleans, New Orleans, LA, USA, from 2008 to 2009. She was Professor at the College of Electrical Engineering, Zhejiang University, Hangzhou, China, from 2001 to 2021. She is currently Professor with the Institute of Artificial Intelligence and Robotics, Xi’an Jiaotong University, Xi’an, China, and also at the College of Electrical Engineering, Zhejiang University, Hangzhou, China. She has authored more than 200 papers in major journals and international conferences. She has led 16 national or provincial or ministerial projects in the last five years, including nine projects funded by the National Natural Science Foundation of China (NSFC). Ronghao Zheng received his bachelor’s degree in Electrical Engineering and master’s degree in Control Theory and Control Engineering both from Zhejiang University, China in 2007 and 2010, respectively. He received his Ph.D. degree from the Department of Mechanical and Biomedical Engineering, City University of Hong Kong in 2014. He is currently with the Department of Systems Science and Engineering, Zhejiang University, China. His research interests lie in the area of distributed algorithms and control, particularly the coordination of networked mobile robot teams with applications in automated systems and security. Senlin Zhang received the B.E. degree in control theory and control engineering from the Wuhan University of Technology, Wuhan, China, and the M.E. degree in control theory and control engineering from Zhejiang University, Hangzhou, China, in 1984 and 1991, respectively. He is currently a Professor with the State Key Laboratory of Industrial Control Technology and the College of Electrical Engineering, Zhejiang University, Hangzhou, China. He has authored more than 200 papers in major journals and international conferences. His current research interests include unmanned undersea systems, intelligent systems, and multi-sensor networks.

Underwater Sensor Networks(USNs).- Mobile Nodes localization in USNs.- Underwater targets detection and DOA estimation via the USNs.- Underwater Target Recognition via the USNs.- Multi-node Cooperative Target Tracking via USNs.- Energy-efficient Sensor Scheduling Method for Target Tracking in USNs.- Underwater Environment Monitoring Using USNs.

Erscheinungsdatum	19.12.2024
Zusatzinfo	220 Illustrations, color; 16 Illustrations, black and white; XVIII, 391 p. 236 illus., 220 illus. in color.
Verlagsort	Singapore
Sprache	englisch
Maße	155 x 235 mm
Themenwelt	Informatik ► Theorie / Studium ► Künstliche Intelligenz / Robotik
Themenwelt	Technik ► Elektrotechnik / Energietechnik
Schlagworte	Active target tracking • Deep learning • Direction Of Arrival (DOA) Estimation • Environmental monitoring • Information Fusion • node localization • sensor scheduling • target detection • Target passive tracking • Target Recognition
ISBN-10	981-97-4668-X / 981974668X
ISBN-13	978-981-97-4668-2 / 9789819746682
Zustand	Neuware