Data Analytics and Artificial Intelligence for Predictive Maintenance in Industry 4.0 unites data science, machine learning, IIOT, and AI to enable predictive and prescriptive maintenance across manufacturing, energy, transportation, agriculture, and healthcare. With contributions from leading academics and practitioners, the book bridges foundational principles with cutting-edge industrial case studies ranging from digital twins and anomaly detection to federated learning and secure healt...

The integration of blockchain and Internet of Things (IoT) drone technology revolutionizes surveillance systems by enhancing security, transparency, and data privacy. As drones become more advanced, they generate real-time data that require secure management. Blockchain technology offers a decentralized framework to store, share, and authenticate this data, reducing risks of tampering and unauthorized access. Further exploration into how combining blockchain with IoT-enabled drones can tra...

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...

Data Analytics and Artificial Intelligence for Predictive Maintenance in Industry 4.0 unites data science, machine learning, IIOT, and AI to enable predictive and prescriptive maintenance across manufacturing, energy, transportation, agriculture, and healthcare. With contributions from leading academics and practitioners, the book bridges foundational principles with cutting-edge industrial case studies ranging from digital twins and anomaly detection to federated learning and secure healt...

Explainable AI in Clinical Practice: Methods, Applications, and Implementation bridges the gap between artificial intelligence capabilities and their practical implementation in healthcare. The book explores applications of explainable AI in diagnostic support and treatment planning, offering insights into making AI systems interpretable and accountable. Through real-world case studies and ethical frameworks, readers learn to transform opaque AI systems into tools that enhance clinical pra...

Explainable AI in Clinical Practice: Advanced Applications and Future Directions builds on foundational concepts to explore the practical implementation and emerging trends of transparent AI in healthcare. Featuring contributions from leading experts, this volume presents advanced methodologies, real-world case studies across various medical specialties, and strategies for overcoming ethical, regulatory, and operational challenges. The book offers comprehensive frameworks for integrating e...

In the era of data-driven healthcare, the ability to gather insights from diverse data sources is critical for advancing precision medicine and improving patient outcomes. However, concerns around data privacy and security compliance often hinder the analysis of sensitive health information. Federated Learning offers a great solution by enabling collaborative health intelligence across institutions without requiring data to leave local environments. By training machine learning models on d...