Introduction To Aiot Pdf
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AIoT and Smart Sensing
AIoT and Smart Sensing: A Comprehensive Guide to the Next Generation of Smart Devices offers an in‐depth exploration of the intersection of Artificial Intelligence of Things (AIoT) and smart sensing technologies. As the convergence of AI and IoT reshapes industries, this book serves as an essential guide for understanding the technological foundations, security protocols, and wide‐ranging applications that make AIoT a transformative force. By examining both foundational and applied aspects, this book aims to provide readers with a holistic view of how AIoT is driving innovation in agriculture, healthcare, smart cities, and beyond. What sets this book apart is its dual focus on technological frameworks and real‐world applications. The first part addresses key security issues, technological innovations, and practical implementations. The second part demonstrates AIoT’s impact on diverse sectors, including agriculture, healthcare, and cultural fields. By linking theory with practice, this book not only introduces cutting‐edge concepts but also showcases their potential for revolutionizing industries. Key features include: Comprehensive coverage of AIoT security protocols, including RFID systems, blockchain in healthcare, and multi‐cloud environments in smart cities Detailed case studies on precision farming, AI‐driven crop management, and sustainable agriculture Exploration of AI innovations in medical diagnostics, chronic healthcare management, and personalized patient care Unique cultural applications, such as AI‐based recognition of Carnatic ragas, highlighting AIoT’s versatility Future trends in AIoT for healthcare, including advanced monitoring and diagnostic systems This book is designed for a wide audience, including researchers, professionals, and students in fields such as AI, IoT, healthcare, agriculture, and smart city development. It is an invaluable resource for anyone seeking to understand the future of smart sensing and AIoT‐driven technologies.
Forthcoming Networks and Sustainability in the AIoT Era
This book introduces a groundbreaking approach to enhancing IoT device security, providing a comprehensive overview of its applications and methodologies. Covering a wide array of topics, from crime prediction to cyberbullying detection, from facial recognition to analyzing email spam, it addresses diverse challenges in contemporary society. Aimed at researchers, practitioners, and policymakers, this book equips readers with practical tools to tackle real-world issues using advanced machine learning algorithms. Whether you're a data scientist, law enforcement officer, or urban planner, this book is a valuable resource for implementing predictive models and enhancing public safety measures. It is a comprehensive guide for implementing machine learning solutions across various domains, ensuring optimal performance and reliability. Whether you're delving into IoT security or exploring the potential of AI in urban landscapes, this book provides invaluable insights and tools to navigate the evolving landscape of technology and data science. The book provides a comprehensive overview of the challenges and solutions in contemporary cybersecurity. Through case studies and practical examples, readers gain a deeper understanding of the security concerns surrounding IoT devices and learn how to mitigate risks effectively. The book's interdisciplinary approach caters to a diverse audience, including academics, industry professionals, and government officials, who seek to address the growing cybersecurity threats in IoT environments. Key uses of this book include implementing robust security measures for IoT devices, conducting research on machine learning algorithms for attack detection, and developing policies to enhance cybersecurity in IoT ecosystems. By leveraging advanced machine learning techniques, readers can effectively detect and mitigate cyber threats, ensuring the integrity and reliability of IoT systems. Overall, this book is a valuable resource for anyone involved in designing, implementing, or regulating IoT devices and systems.
AIoT Innovations in Digital Health
Artificial Intelligence (AI) innovations in digital health offer unprecedented opportunities to facilitate human health and provide tools and techniques that reduce overall costs. This book discusses the use of AI to improve diagnostic accuracy, patient monitoring, the use of remote diagnostic tools, identification of life-threatening diseases, medical robotics applications, drug discovery, technology-driven solutions, and much more. AIoT Innovations in Digital Health: Emerging Trends, Challenges, and Solutions presents integrated technologies such as Green Computing, IoT, and Big Data using AI, Machine Learning, Deep Learning, and Federated Learning for Healthcare. It discusses the future of medical robotics using Machine Learning and highlights the use of Federated Learning-based patient monitoring applications. This book also elaborates on the role that AI and Machine Learning play in drug discovery. Interested readers will include anyone working in or involved in smart healthcare research which includes, but is not limited to, healthcare specialists, computer science engineers, electronics engineers, systems engineers, and pharmaceutical practitioners.