Название: Digital Technologies for Underwater Surveillance and Management: Data Analytics and Remote Sensing
Автор: Vishal Jain, Hamed Taherdoost, Arvind Panwar, Khadija Slimani
Издательство: CRC Press
Серия: Chapman & Hall/CRC Cyber-Physical Systems
Год: 2027
Страниц: 397
Язык: английский
Формат: True PDF, True EPUB
Размер: 38.7 MB

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.

Digital Technologies for Underwater Surveillance and Management has been developed to address this pressing need by presenting a comprehensive, multidisciplinary perspective on how Artificial Intelligence (AI), Machine learning, remote sensing, Big Data analytics, blockchain, Federated Learning, and the Internet of Underwater Things (IoUT) are transforming subaquatic monitoring and security operations. This edited volume consolidates cutting-edge research, advanced methodologies, and real-world applications that collectively demonstrate how intelligent technologies can bridge long-standing gaps in underwater visibility, data interpretation, anomaly detection, and decision-making.

The chapters in this volume span a broad spectrum of emerging topics, including AI-driven maritime surveillance, predictive analytics for underwater risk assessment, advanced underwater image processing, acoustic signal analysis, anomaly detection frameworks, secure blockchain-enabled data pipelines, Federated Learning for decentralized sensor networks, and next-generation underwater sensing platforms. The book also critically examines the limitations, risks, cost implications, and ethical dimensions of deploying intelligent systems in complex underwater environments. Together, these contributions provide both theoretical depth and applied insight into modern underwater surveillance ecosystems.

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

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

Contents: