LIMITED OFFER
Save 50% on book bundles
Immediately download your ebook while waiting for your print delivery. No promo code needed.
AI Below the Surface
Navigating the Deep Ocean with Intelligence
- 1st Edition - April 1, 2026
- Editors: Palanichamy Naveen, Vinayakumar Ravi, Ajay Arunachalam
- Language: English
- Paperback ISBN:9 7 8 - 0 - 4 4 3 - 3 3 6 2 9 - 4
- eBook ISBN:9 7 8 - 0 - 4 4 3 - 3 3 6 3 0 - 0
"AI Below the Surface: Navigating the Deep Ocean with Intelligence" provides a comprehensive overview of how Artificial Intelligence (AI) is utilized in marine science, marine bi… Read more
Purchase options
Institutional subscription on ScienceDirect
Request a sales quote"AI Below the Surface: Navigating the Deep Ocean with Intelligence" provides a comprehensive overview of how Artificial Intelligence (AI) is utilized in marine science, marine biology, and oceanography. Comprising 12 chapters authored by global experts in AI, marine biology, and oceanography, the book caters to students, researchers, and practitioners seeking a deep understanding of AI's impact in these fields. This resource serves as an accessible and indispensable guide, shedding light on the transformative role of AI in marine exploration. Through its exploration of advanced AI technologies and their interaction with complex underwater ecosystems, this edited volume offers valuable insights into future applications and trends as well as to ethical considerations and challenges.
• Offers a thorough examination on how AI is reshaping our approach to understanding and interacting with the underwater world.
• Provides real-world examples and case studies that demonstrate the practical applications of AI in underwater robotics, marine life monitoring, and object recognition.
• Includes future trends and innovations into cohesive narrative that appeals to both technology enthusiasts and marine scientists, fostering cross-disciplinary dialogue and collaboration.
• Provides real-world examples and case studies that demonstrate the practical applications of AI in underwater robotics, marine life monitoring, and object recognition.
• Includes future trends and innovations into cohesive narrative that appeals to both technology enthusiasts and marine scientists, fostering cross-disciplinary dialogue and collaboration.
students and researchers in the fields of oceanography and artificial intelligence, marine biology, and underwater exploration who seek a comprehensive understanding of how AI is transforming these areas.
1. Introduction to AI and Underwater Exploration: Overview of Artificial Intelligence and its significance. Introduction to underwater environments and the need for intelligent exploration. 2. AI-Driven Underwater Vehicles and Drones: In-depth exploration of AI-powered underwater vehicles. Case studies highlighting the integration of AI in underwater drones. 3. Intelligent Marine Life Monitoring: The role of AI in tracking and monitoring marine life. Real-world examples of successful AI applications in marine biology. 4. Object Recognition and Interaction in the Deep Sea: Exploration of AI's role in object recognition and interaction underwater. Examples of how AI enhances interactions with underwater objects and structures. 5. Challenges and Ethical Considerations in Underwater AI: Examination of challenges associated with AI in underwater environments. Ethical considerations and responsible AI practices in marine exploration. 6. Future Trends in AI and Underwater Technology: Exploration of upcoming trends and innovations in AI and underwater technology. Speculation on the future of AI applications in marine exploration. 7. Data Analytics for Underwater Environments: The role of AI in processing and analyzing data collected from underwater sensors. Case studies demonstrating the impact of data analytics in marine research. 8. AI-Assisted Oceanographic Research: Integration of AI in oceanographic studies and climate modeling. Examples of how AI enhances our understanding of ocean dynamics. 9. Autonomous Underwater Vehicles (AUVs) and Machine Learning: Exploration of AUVs and their applications in underwater exploration. How machine learning algorithms improve the autonomy and decision-making of AUVs. 10. Human-Machine Collaboration in Underwater Exploration: The synergy between human expertise and AI in underwater research. Collaborative efforts and challenges in human-machine teams for marine exploration. 11. AI Applications in Underwater Archaeology: How AI is employed in the discovery and preservation of underwater archaeological sites. Case studies highlighting the role of AI in uncovering historical artifacts beneath the sea. 12. Societal Impact and Public Perception of AI in the Deep: Exploration of how AI in underwater environments impacts society. Public perception, awareness, and potential implications of AI applications in marine exploration. Authors: 1. Sakamoto, S (corresponding author), Seikei Univ, Dept Comp & Informat Sci, 3-3-1 Kichijoji Kitamachi, Musashino, Tokyo 1808633, Japan. 2. Emiola, I (corresponding author), Univ Cent Florida, Dept Elect & Comp Engn, Orlando, FL 32816 USA. 3. Celic, L (corresponding author), Univ Zagreb, Fac Elect Engn & Comp, Zagreb, Croatia. 4. Petho, Z (corresponding author), Budapest Univ Technol & Econ, Dept Automot Technol, Budapest, Hungary. 5. Thankappan, M (corresponding author), Univ Oberta Catalunya UOC, Estudis Inforrnat Multimedia & Telecomunicacio In, Barcelona, Spain. 6. Park, HK (corresponding author), KOREATECH, Sch Elect Elect & Commun Engn, Cheonan 31253, South Korea. 7. Jung, K (corresponding author), Daejeon Univ, Dept Fintech, Daejeon 34520, South Korea. 8. Allouch, M (corresponding author), Univ Paris Saclay, UVSQ, 45 Ave Etats Unis, F-78000 Versailles, France. 9. Chen, SY (corresponding author), Tamkang Univ, Dept Comp Sci & Informat Engn, New Taipei, Taiwan. 10. Kim, Y (corresponding author), Inha Univ, Dept Elect Engn, Incheon, South Korea. 11. You, CS (corresponding author), Natl Univ Singapore, Dept Elect & Comp Engn, Singapore, Singapore. 12. Han, X (corresponding author), Univ S Florida, Dept Comp Sci & Engn, Tampa, FL 33620 USA.
- No. of pages: 320
- Language: English
- Edition: 1
- Published: April 1, 2026
- Imprint: Elsevier
- Paperback ISBN: 9780443336294
- eBook ISBN: 9780443336300
PN
Palanichamy Naveen
Naveen P. completed his Ph.D. in the field of Image Processing from Kalasalingam Academy of Research and Education. He has more than 10 years of teaching experience. Prior to joining KPR Institute of Engineering and Technology, he was associated as NIRF Co-ordinator at Sri Eshwar College of Engineering and also served as Assistant Director - Accreditation and Ranking at Kalasalingam Academy of Research and Education. His research interests include Image Processing and Machine Learning. He received the best faculty award from Kalasalingam Academy of Research and Education in the year 2019. He has published dozen of papers in International Journals and several patents. He is presently an Associate Editor in the Journal of Intelligent and Fuzzy Systems and AD ALTA-Journal of Interdisciplinary Research. He currently serves as an Editorial Board member for the International Journal of Interactive Multimedia and Artificial Intelligence and the Journal of Current Science and Technology.
Affiliations and expertise
KPRVR
Vinayakumar Ravi
Dr. Vinayakumar Ravi is an Assistant Research Professor at the Center for Artificial Intelligence, Prince Mohammad Bin Fahd University, Khobar, Saudi Arabia. Dr. Ravi has been a Postdoctoral Research Fellow developing and implementing novel computational and machine learning algorithms and applications for big data integration and data mining with Cincinnati Children's Hospital Medical Center, Cincinnati, USA. He received his Ph.D. in Computer Science from Amrita School of Engineering, Coimbatore, India. His current research interests include applications of data mining, Artificial Intelligence, machine learning and, deep learning for biomedical informatics, cyber security, image processing, and natural language processing. Dr. Ravi is editor of Efficient Data Handling for Massive Internet of Medical Things: Healthcare Data Analytics, Springer. Dr. Ravi is an editorial board member for Journal of the Institute of Electronics and Computer (JIEC), International Journal of Digital Crime and Forensics (IJDCF), and he has organized a shared task force on detecting malicious domain names (DMD 2018) as part of SSCC'18 and ICACCI'18.
Affiliations and expertise
Assistant Research Professor, Center for Artificial Intelligence, Prince Mohammad Bin Fahd University, Khobar, Saudi ArabiaAA
Ajay Arunachalam
Ajay Arunachalam is part of the division of research and Data Science Unit at Cambridge University Press & Assessment, United Kingdom. His core interests include Opacity in AI Systems, Applied AI, Machine Learning, Deep Learning, Reinforcement Learning, Optimization, Big Data, Algorithmic trading, Natural Language Processing, and Computer Vision. His research envisions learning algorithms that can learn feature representations from both unlabelled and labelled data, be it guided with and/or without human interaction, and that are on different levels of abstractions in order to bridge the gap between low-level data and high-level abstract concepts. He led the team of data analysts, data engineers, ML engineers, and data scientists in the past. He was a post-doctoral researcher (Artificial Intelligence) at the Centre for Applied Autonomous Sensor Systems (AASS), School of Science and Technology, Örebro University, Örebro, Sweden, to which he contributes with research on Autonomous Precision Agriculture Robot. Prior to his present role, he was working as a Data Scientist at True Corporation Public Company Limited, a Communications Conglomerate, working with Petabytes of data, and building & deploying models in production. He received the Ph.D. degree in Computer Science and Information Systems (CSIS) from National Institute of Development Administration (NIDA), Thailand. He holds a master’s in computer science & engineering. from Anna University, Chennai, India, and a bachelor's in computer engineering from Savitribai Phule Pune University, Pune, India. His research interests include Distributed Systems, Wireless and Mobile Networking, Algorithmic Trading, Big Data, Applied Machine Learning/Deep Learning, Opacity in AI systems, Optimization, FOSS related to e-learning/m-learning/e-governance.
Affiliations and expertise
Research Division, Cambridge University Press & Assessment, UK