Digital Technologies for Underwater Surveillance and Management: Data Analytics and Remote Sensing
English | 2026 | ISBN: 1041143982 | 397 pages | True PDF,EPUB | 38.70 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.Key Features
iscusses the use of deep learning and predictive analytics for sonar data interpretation and underwater anomaly detectionCovers multisensory remote sensing technologies, including LiDAR, SAS, and hyperspectral imaging for threat identificationExplores the deployment of IoT-enabled marine sensor networks and autonomous underwater vehicles (AUVs)Discusses blockchain and cybersecurity strategies for securing underwater surveillance dataIncludes applications in environmental monitoring: oil spills, coral reef health, and underwater earthquakesExamines case studies in naval defense, illegal fishing, and AI-driven marine surveillance systemsProvides technical insight into AI models such as CNNs, RNNs, and reinforcement learning for object classification and trackingThis book is for researchers, professionals, and scientists interested in underwater threat detection and security 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.
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.
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