Digital Technologies for Underwater Surveillance and Management

Data Analytics and Remote Sensing
1. Auflage 2026
ISBN: 978-1-041-14398-7
Verlag: Taylor & Francis Ltd

Buch, Englisch, 414 Seiten, Format (B × H): 178 mm x 254 mm

Reihe: Chapman & Hall/CRC Cyber-Physical Systems

This book provides a technical and practical roadmap for using advanced AI, data analytics, and sensing technologies to safeguard the underwater domain. It covers cutting-edge tools such as synthetic aperture sonar (SAS), LiDAR, hyperspectral imaging, and satellite-based systems for detecting submerged threats, environmental hazards, and illicit maritime activity. Through the integration of AI, IoT, deep learning, and blockchain, the book presents scalable, autonomous solutions for anomaly detection, risk assessment, and secure marine surveillance. With a focus on naval defense, disaster response, and ecological protection, this book offers a unified view of how digital technologies are redefining underwater monitoring and threat mitigation.

Key Features:

· Discusses the use of deep learning and predictive analytics for sonar data interpretation and underwater anomaly detection

· Covers multisensory remote sensing technologies including LiDAR, SAS, and hyperspectral imaging for threat identification.

· Explores the deployment of IoT-enabled marine sensor networks and autonomous underwater vehicles (AUVs).

· Discusses blockchain and cybersecurity strategies for securing underwater surveillance data.

· Includes applications in environmental monitoring: oil spills, coral reef health, and underwater earthquakes.

· Examines case studies in naval defense, illegal fishing, and AI-driven marine surveillance systems.

· Provides technical insight into AI models such as CNNs, RNNs, and reinforcement learning for object classification and tracking

It is for researchers, professionals, and scientists interested in underwater threat detection and security systems.

Zielgruppe

Academic

Autoren/Hrsg.

Jain, Vishal

Taherdoost, Hamed

Panwar, Arvind

Slimani, Khadija

Fachgebiete

• Technische Wissenschaften Elektronik | Nachrichtentechnik Nachrichten- und Kommunikationstechnik Optische Nachrichtentechnik
• Mathematik | Informatik EDV | Informatik Daten / Datenbanken Data Mining
• Mathematik | Informatik EDV | Informatik Technische Informatik
• Mathematik | Informatik EDV | Informatik Informatik Mensch-Maschine-Interaktion Ambient Intelligence, RFID, Internet der Dinge
• Mathematik | Informatik EDV | Informatik Informatik Künstliche Intelligenz Maschinelles Lernen
• Mathematik | Informatik EDV | Informatik Informatik Mensch-Maschine-Interaktion Informationsvisualisierung
• Geowissenschaften Geologie GIS, Geoinformatik

Inhaltsverzeichnis

Chapter 1: AI-Driven Underwater Surveillance for Maritime Security and Environmental Monitoring. Chapter 2: Deepening Insights: The Role of Data Augmentation in Underwater Remote Sensing Analytics. Chapter 3: Underwater Image Feature Extraction and Analysis for the Choice of Enhancement Model. Chapter 4: Artificial Intelligence (AI)-Driven Remote Sensing and Predictive Analytics for Illegal Underwater Activity Detection. Chapter 5: Predictive Analytics using AI for Underwater Security and Risk Assessment. Chapter 6: Developments in Underwater Image Processing and Computer Vision for Intelligent Maritime Surveillance. Chapter 7: Internet of Underwater Things and Sensor Networks for Real-Time Smart Ocean Monitoring and Management. Chapter 8: Revolutionizing Subaquatic Perception: Cutting-Edge Advances in Underwater Image Processing and Computer Vision. Chapter 9: Echoes and Optics: Understanding the Physical Principles and Technological Frameworks Behind Remote Sensing for Submarine Environments. Chapter 10: Blockchain-Enabled Secure Data Frameworks for Underwater Surveillance and Maritime Intelligence. Chapter 11: Deep Learning for Acoustic Signal Analysis. Chapter 12: Neural Depths: AI-Powered Anomaly Detection and Risk Analytics in Smart Underwater Surveillance. Chapter 13: Federated Learning in Underwater Sensor Networks: Decentralized Intelligence for Secure Marine Surveillance. Chapter 14: Tracing Underwater Contaminants: Remote Sensing of Ions and Chemicals. Chapter 15: IoT and Sensor Networks for Real-Time Underwater Monitoring. Chapter 16: Next-Generation Acoustic Signal Analysis Using Deep Learning for Smart Systems. Chapter 17: Submerged Networks, Surface Threats: A Comprehensive Review of Security Vulnerabilities in Underwater Wireless Sensor Systems. Chapter 18: Next-Generation Sensing Platforms for Underwater Environmental Intelligence. Chapter 19: Challenges and Limitations of AI in Underwater Surveillance. Chapter 20: Artificial Intelligence in Underwater Surveillance: Challenges, Limitations, and Emerging Research Directions.

Über Autor(innen)

Vishal Jain is presently working as a Professor at the Department of Computer Science & Engineering, School of Engineering & Technology, Vivekananda Institute of Professional Studies - Technical Campus, New Delhi. Before that, he worked as Professor at Sharda University, Greater Noida and Associate Professor at Bharati Vidyapeeth’s Institute of Computer Applications and Management (BVICAM), New Delhi. He has associated as a member of the Faculty Board, Board of Planning and Management, Executive Council, Academic Council, Curriculum Development and Review Committee and Academic Audit of various higher education Institutions. He is associated with Kuala Lumpur University of Science and Technology (KLUST) (formerly known as Infrastructure University Kuala Lumpur (IUKL)), Malaysia, Lincoln University College, Malaysia and Research Institute of IoT Cybersecurity, Department of Electronic Engineering, National Kaohsiung University of Science and Technology, Taiwan for research oriented activities. He has supervised three Ph.D and two scholars are pursuing. He has more than 3400 research citations with Google Scholar (h-index score 30 and i-10 index 66) and has authored more than 250 research papers in professional journals and conferences. He has authored and edited more than 70 books (most of them are indexed at the Scopus) with various reputed publishers, including Elsevier, Springer, IET, Apple Academic Press, CRC, Taylor and Francis Group, Scrivener, Wiley, Emerald, NOVA Science, River Publishers, IGI-Global and Bentham Science. He has more than 300 Scopus publications. He is the book series editor of 10 book series with the reputed international publishers. Along with the regular teaching, he had organized various Conferences, Faculty Development Programme, Seminars, Hackathon, Faculty and Students Oriented activities. His research areas include machine learning, information retrieval, semantic web, ontology engineering, data mining, ad hoc networks, sensor networks and network security. He received a Young Active Member Award for the year 2012–13 from the Computer Society of India, and Best Faculty Award for the year 2017 and Best Researcher Award for the year 2019 from BVICAM, New Delhi.

Hamed Taherdoost is an award-winning leader in research and development, known for his contributions across both industry and academia. He is the founder of Hamta Business Corporation, Associate Professor and Chair of RSAC at University Canada West, & Director of R&D at Q Minded Quark Minded Technology Inc. He has over 20 years of experience in both industry and academic sectors. He has worked at international companies from Cyprus, the UK, Malta, Iran, Malaysia, and Canada and has been highly involved in development of several projects in different industries, healthcare, transportation, residential, oil and gas and IT. Additionally, he has served as a trusted technical and technology consultant for multiple companies, providing advisory and mentorship. Dr. Taherdoost has extensive experience in research and development, particularly in the SR&ED domain, with a 100% success rate in over 100 projects, resulting in claims exceeding $30 million. His leadership roles have spanned multiple six-figure companies, including serving in “C” level positions. He specializes in guiding startups and has played a critical role in scaling innovative projects across various industries. His contributions have cemented his reputation as a leader in fostering innovation and delivering impactful solutions. In academia, Dr. Taherdoost has held teaching positions in Southeast Asia, the Middle East, Europe, and North America since 2009. He began his academic career as a lecturer at AU & PNU and later served as an adjunct professor and faculty fellow at Westcliff University, USA and Gisma University of Applied Sciences, Germany. His research tenure at IAU lasted over eight years, during which he supervised numerous students.

Arvind Panwar is a distinguished researcher and academician with over 15 years of experience in Computer Science and Engineering. He holds a Ph.D. from Guru Gobind Singh Indraprastha University, where his thesis focused on designing a secure cloud-based blockchain framework for health record management. His expertise spans blockchain technology, information security, cybersecurity, and data analytics. Dr. Panwar is actively involved in academic publishing, having authored 9 SCI/SCOPUS-indexed journal articles, 15 conference papers, and 18 book chapters. He is currently editing three significant books for esteemed publishers: Data Analytics and Artificial Intelligence for Predictive Maintenance in Industry 4.0 for Bentham, Qubits Unveiled: Quantum Computing Solutions for Efficient Supply Logistics for Nova Publications, and Energy Efficient Internet of Things-Based Wireless Sensor Network for Wiley-Scrivener Publishing LLC. These works highlight his expertise in cutting-edge technologies and their applications in modern industry and logistics. A prolific innovator, Dr. Panwar holds 8 granted patents and 11 published patents in the domains of blockchain, AI, and IoT applications. His academic contributions include mentoring graduate students, spearheading interdisciplinary research, and engaging in global collaborations, such as his visiting professorship at South Kazakhstan Pedagogical University. Dr. Panwar’s dedication to advancing technological innovation and his extensive academic achievements make him a leading figure in bridging research and industry.

Khadija Slimani completed her Ph.D., which was jointly supervised by the University of Ibn Tofail in Morocco and the University of Technology of Belfort Montbeliard (UTBM) in France. This collaborative international effort showcased her commitment to academic excellence and cross-cultural research. During her doctoral studies, Dr. Slimani delved into the realms of machine learning, deep learning, pattern recognition, and computer vision, with a specific focus on academic emotion recognition. This interdisciplinary approach, spanning both Moroccan and French academic environments, enriched her research experience and contributed to the global perspective of her work. After completing her Ph.D. thesis, Dr. Slimani pursued a postdoctoral position at the University of Poitiers, France, demonstrating her versatility in research by delving into Objects DRI (Detection, Recognition, and Identification). Her application of AI methodologies aimed at enhancing video content filtering for optimal security reflected the international scope of her expertise. Dr. Slimani's academic contributions extended to various engineering schools in Paris, France; where she took on teaching responsibilities across multiple modules, including data science, deep learning, machine Learning, data bases, and computer vision. She is currently holding the esteemed title of Associate Professor at the Graduate School of Automatic Electronic Computing in Paris, France. Her scholarly achievements include over 18 published articles in esteemed journals and conferences, supported by an impressive h-index of 10 in Scopus. Notably, she played a key role as a guest editor for the special issue "Integrating Intelligence: Advancements in Applied Research with Smart Technologies" in the Journal of Autonomous Intelligence (eISSN: 2630-5046) and served as a guest editor for the proceedings published in E3S Web of Conference 2022 and 2023, both Scopus/web of science indexed. Through her diverse roles, Dr. Slimani consistently inspires and contributes to shaping the next generation of researchers.