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This edited volume presents a comprehensive and interdisciplinary perspective on Cloud-Enabled Artificial Intelligence of Things (AIoT), highlighting recent advances at the convergence of artificial intelligence, the Internet of Things (IoT), cloud computing, edge intelligence, and cybersecurity. The book brings together scholarly contributions that address emerging AIoT paradigms, architectures, and application domains, encompassing intelligent sensing, secure cloud-enabled frameworks, machine learning and deep learning techniques, precision agriculture, healthcare analytics, digital twins, and intelligent cyber-physical systems. By integrating theoretical foundations with contemporary developments, the volume offers a timely and holistic understanding of next-generation AIoT technologies and their transformative potential. The book provides readers with in-depth analyses of cloud-enabled AIoT models, bioinspired AI approaches, AI/ML-driven cybersecurity mechanisms, distributed edge-computing architectures, and domain-specific applications, including non-contact vital signs estimation, nutrient deficiency detection, protein–ligand binding affinity prediction, and secure visitor validation systems. Each chapter presents state-of-the-art methodologies, critical challenges, and future research directions, enabling readers to develop both conceptual and practical insights into the design, deployment, scalability, and security of intelligent cloud-enabled ecosystems. The volume serves as a valuable reference for understanding the integration of AI, IoT, and cloud technologies in addressing complex real-world problems. Key Features This book is intended for researchers, academicians, postgraduate students, industry practitioners, and technology professionals working in AI, IoT, cloud computing, cybersecurity, smart agriculture, healthcare informatics, and intelligent systems who seek an interdisciplinary and application-focused perspective on next-generation AIoT technologies.
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