Neelu Jyothi Ahuja – författare

The book examines the integration of IoT, Blockchain, and Smart Healthcare, providing a comprehensive analysis of these advanced technologies and their impact on the healthcare industry. It offers practical examples of how Blockchain and IoT devices can be used to address real-world healthcare challenges and overcome the hurdles of implementing them in the healthcare sector.

IoT, Blockchain, and Smart Healthcare: Integration Techniques and Case Studies provides a detailed exploration of how these technologies are combined, giving readers a deep understanding of their role in revolutionizing healthcare. It explores the practical applications of Blockchain and IoT devices in solving healthcare problems and addresses the challenges of incorporating these technologies into healthcare systems. The book also provides practical guidance on implementing cutting-edge methodologies, enabling readers to apply theoretical knowledge in real-world situations effectively.

By bridging the gap between technology and healthcare, this book makes complex concepts understandable to a wide audience, including healthcare professionals, researchers, technology enthusiasts, and policymakers.

The book examines the integration of IoT, Blockchain, and Smart Healthcare, providing a comprehensive analysis of these advanced technologies and their impact on the healthcare industry. It offers practical examples of how Blockchain and IoT devices can be used to address real-world healthcare challenges and overcome the hurdles of implementing them in the healthcare sector.

IoT, Blockchain, and Smart Healthcare: Integration Techniques and Case Studies provides a detailed exploration of how these technologies are combined, giving readers a deep understanding of their role in revolutionizing healthcare. It explores the practical applications of Blockchain and IoT devices in solving healthcare problems and addresses the challenges of incorporating these technologies into healthcare systems. The book also provides practical guidance on implementing cutting-edge methodologies, enabling readers to apply theoretical knowledge in real-world situations effectively.

By bridging the gap between technology and healthcare, this book makes complex concepts understandable to a wide audience, including healthcare professionals, researchers, technology enthusiasts, and policymakers.

Data Analytics using Machine Learning Techniques on Cloud Platforms examines how machine learning and cloud computing combine to drive data-driven decision-making across industries. Covering ML techniques, cloud-based analytics tools, and security concerns, this book provides theoretical foundations and real-world applications in fields like healthcare, logistics, and e-commerce. It also addresses security challenges, privacy concerns, and compliance frameworks, ensuring a comprehensive understanding of cloud-based analytics.

This book is an essential resource for students, researchers, and professionals who seek to understand and apply ML-driven cloud analytics in real-world scenarios.

Data Analytics using Machine Learning Techniques on Cloud Platforms examines how machine learning and cloud computing combine to drive data-driven decision-making across industries. Covering ML techniques, cloud-based analytics tools, and security concerns, this book provides theoretical foundations and real-world applications in fields like healthcare, logistics, and e-commerce. It also addresses security challenges, privacy concerns, and compliance frameworks, ensuring a comprehensive understanding of cloud-based analytics.

This book is an essential resource for students, researchers, and professionals who seek to understand and apply ML-driven cloud analytics in real-world scenarios.