Special Session 2

SPECIAL SESSION #2

Nazila Fough

Robert Gordon University , UK

• n.fough1@rgu.ac.uk

Wai Keung Fung

Cardiff Metropolitan University, UK

• wfung@cardiffmet.ac.uk

Naoki Motoi

Kobe University, Japan

• motoi@maritime.kobe-u.ac.jp

Somasundar Kannan

Robert Gordon University, UK

• s.kannan1@rgu.ac.uk

Jinchang Ren

Robert Gordon University, UK

• j.ren@rgu.ac.uk

"Transparent Ocean" refers to the use of advanced underwater imaging and sensing technologies to explore and study the world's oceans. With the help of advanced technologies of underwater sensor networks and swarms, sensor nodes can be deployed autonomously or semi-autonomously to the required locations for data acquisition. By using advanced sensors and cameras that can see through the water and capture high-resolution images and data, researchers and engineers can gain a deeper understanding of the ocean's ecosystems, geology, and the behaviour of marine animals. Transparent Ocean technology has applications in a wide range of fields, from marine biology and oceanography to offshore oil and gas exploration and underwater archaeology. The use of advanced imaging and sensing technologies can help us to better understand the impact of climate change on the oceans, identify new species of marine life, and explore previously undiscovered underwater environments. With the development of new materials and technologies, Transparent Ocean technology is becoming more accessible and affordable, opening up new opportunities for research and exploration in the world's oceans.

This special session aims to explore the latest developments and advancements in the field of ocean sensing technology and underwater swarms. The session will focus on how underwater sensor networks can be used to achieve a transparent ocean by providing accurate and reliable data on various ocean parameters such as temperature, salinity, pH, and dissolved oxygen levels, as well as images and videos at pre-specified locations and formations. The session will bring together leading researchers, scientists, and industry experts to discuss the challenges and opportunities associated with underwater sensor networks, including but not limited to planning, control, navigation and localisation of underwater vehicles and swarms, underwater wireless communications, sensing and imaging, and AI/machine learning in underwater technologies. Participants will share their experiences in deploying and managing these networks, and discuss the latest technological innovations in the field. The session will also explore the potential applications of underwater sensor networks in ocean monitoring, environmental protection, and marine resource management.

Overall, the special session promises to be a dynamic and informative event that will provide valuable insights into the future of ocean sensing technology. Attendees can expect to gain a better understanding of the latest trends, challenges, and opportunities in this exciting field, and to network with professionals from academia and industry around the world.

Topics covered in this special session will consider:

• Novel and Bio-inspired Design of Underwater Vehicles
• Autonomous Underwater Vehicles (AUVs) Navigation and Control
• Underwater Swarm Formation Planning and Control
• Underwater Swarm Localisation and SLAM
• Underwater Acoustic Communications and Networking Architectures for large scale Underwater Sensor Networks
• Underwater Acoustic Channel Characteristics and Propagation Models for Communications
• Energy-efficient routing protocols for Underwater Sensor Networks in Harsh Environments
• Intelligent Data Fusion Techniques for Underwater Sensor Networks
• Impacts of Ocean Dynamics on Underwater Sensor Networks.
• Effects of Underwater Noise on the Performance of Underwater Sensor Networks
• Advanced Sensing and imaging systems in Underwater Sensor Networks
• Distributed Sensing in Underwater Sensor Networks
• Sensor Placement for Effective Coverage of Underwater Sensor Networks
• Underwater Sensor Network Security, Cyber-attacks and Counter-measures

Nazila Fough (SMIEEE) is a lecturer and researcher in electrical and electronic engineering in the School of Engineering. She has a PhD in data network and telecommunication with a focus on real-time video communication, a MSc in control systems, and a BEng (Hons) in electronic engineering. Previously, she worked as a network engineer in the telecommunications and internet network industries for 6 years. She is a CISCO-certified instructor. Currently, she is working on several academic and industrial projects related to UWSN and subsea communication. Her research interests are in domain of wireless networks, network security , underwater wireless sensors network ( UWSN) and subsea communication , video compression, image processing, real-time multimedia communication, QOS, QOE, and congestion control.

Wai Keung Fung (SMIEEE) is a Senior Lecturer in Electronics, Robotics and Control Engineering and the Deputy Head of EUREKA Robotics Centre at Cardiff Metropolitan University. He is also the lead of the Autonomous Robotics Lab under the EUREKA Robotics Centre. He has extensive research experience in autonomous robotics, networked robotics, computational intelligence and human-robot interactions. In particular, he led a university-industry collaboration project on simultaneous underwater swarm localisation and he was involved in projects on applying AI/machine learning in autonomous robots and robot learning and real-time teleoperation and telemanipulation systems.

Naoki Motoi received the B.E. degree in system design engineering and the M.E. and Ph.D. degrees in integrated design engineering from Keio University, Japan, in 2005, 2007 and 2010, respectively. In 2007, he joined the Partner Robot Division, Toyota Motor Corporation, Japan. From 2011 to 2013, he was a Research Associate at Yokohama National University, Japan. Since 2014, he has been with Kobe University, Japan, where he is a currently Associate Professor. From 2019 to 2020, he also held the position of a Visiting Professor at Automation and Control Institute (ACIN), TU Wien, Austria. His current research interests include robotics, motion control, and haptic.

Somasundar Kannan is a Lecturer in Electrical & Electronics Engineering at Robert Gordon University. He has several years of research, teaching and industrial consulting experience in modelling and control of robotics systems including Remotely Operated Vehicles (ROV), medical robots, aerial robots, custom inspection robots, light weight manipulators and space robotic systems. Over the years he has worked on research and industrial projects in developing nonlinear models and control techniques to understand complex dynamics and enhance control performance. He has published several papers in the application of sensing, estimation and control techniques to linear and nonlinear systems, robotic systems especially exploring tools such as Model Predictive Control (MPC), Nonlinear and Adaptive control, Cooperative and Distributed control, Observer design and Observer based control.

Jinchang Ren (SMIEEE) received his B. Eng. degree in computer software, M.Eng. in image processing, and D. Eng. in computer vision, all from Northwestern Polytechnical University, Xi’an, China. He was also awarded a Ph.D. degree in Electronic Imaging and Media Communication from the University of Bradford, Bradford, U.K. Currently he is a full Professor of Computing Sciences, Transparent Ocean Lead, and Director of the Hyperspectral Imaging Lab at the National Subsea Centre (NSC), also Director of NSC International PGR Academy, Robert Gordon University, Aberdeen, U.K.
Dr. Ren’s research interests focus mainly on hyperspectral imaging, image processing, computer vision, big data analytics and machine learning. He has published 300+ peer reviewed journal/conferences articles, and acts as an Associate Editor for several international journals including IEEE TGRS and J. of the Franklin Institute et al. He has also chaired and co-chaired a number of conferences and workshops. His students have received many awards, such as the Best PhD thesis from IET Image and Vision Section (for Dr J. Zabalza’s work in hyperspectral image analysis) in 2016 and various conferences/workshops.