Sarvesh Tanwar – författare

Machine Learning, Cyber Security, and Blockchain in Smart Environment: Application and Challenges provides far-reaching insights into the recent techniques forming the backbone of smart environments, and addresses the vulnerabilities that give rise to the challenges in real-word implementation. The book focuses on the benefits related to the emerging applications such as machine learning, blockchain and cyber security.

Key Features:

This book is primarily aimed at graduates, researchers, and professionals working in the areas of machine learning, blockchain, and cyber security.

Machine Learning, Cyber Security, and Blockchain in Smart Environment: Application and Challenges provides far-reaching insights into the recent techniques forming the backbone of smart environments, and addresses the vulnerabilities that give rise to the challenges in real-word implementation. The book focuses on the benefits related to the emerging applications such as machine learning, blockchain and cyber security.

Key Features:

This book is primarily aimed at graduates, researchers, and professionals working in the areas of machine learning, blockchain, and cyber security.

Offering a holistic view of the pioneering trends and innovations in smart healthcare management, this book focuses on the methodologies, frameworks, design issues, tools, architectures, and technologies necessary to develop and understand intelligent healthcare systems and emerging applications in the present era.

Smart Technologies in Healthcare Management: Pioneering Trends and Applications provides an overview of various technical and innovative aspects, challenges, and issues in smart healthcare, along with recent and novel findings. It highlights the latest advancements and applications in the field of intelligent systems and explores the importance of cloud computing and the design of sensors in an IoT system. The book offers algorithms and a framework with models in machine learning and AI for smart healthcare management. A detailed flow chart and innovative and modified methodologies related to intelligent computing in healthcare are discussed, as well as real-world-based examples so that readers can compare technical concepts with daily life concepts.

This book will be a useful reference for academicians and the healthcare industry, along with professionals interested in exploring innovations in varied applicational areas of AI, IoT, and machine learning. Researchers, startup companies, and entrepreneurs will also find this book of interest.

Offering a holistic view of the pioneering trends and innovations in smart healthcare management, this book focuses on the methodologies, frameworks, design issues, tools, architectures, and technologies necessary to develop and understand intelligent healthcare systems and emerging applications in the present era.

Smart Technologies in Healthcare Management: Pioneering Trends and Applications provides an overview of various technical and innovative aspects, challenges, and issues in smart healthcare, along with recent and novel findings. It highlights the latest advancements and applications in the field of intelligent systems and explores the importance of cloud computing and the design of sensors in an IoT system. The book offers algorithms and a framework with models in machine learning and AI for smart healthcare management. A detailed flow chart and innovative and modified methodologies related to intelligent computing in healthcare are discussed, as well as real-world-based examples so that readers can compare technical concepts with daily life concepts.

This book will be a useful reference for academicians and the healthcare industry, along with professionals interested in exploring innovations in varied applicational areas of AI, IoT, and machine learning. Researchers, startup companies, and entrepreneurs will also find this book of interest.

This book comprehensively discusses the role of cloud computing in artificial intelligence‑based data‑driven systems and hybrid cloud computing for large data‑driven applications. It further explores new approaches, paradigms, and frameworks to meet societal challenges by providing solutions for critical insights into data. The text provides Internet of Things‑based frameworks and advanced computing techniques to deal with online/virtual systems.

This book:

• Covers the aspects of security, authentication, and prediction for data‑driven systems in heterogeneous environments.

• Provides data‑driven frameworks in combination with the Internet of Things, artificial intelligence, and computing to provide critical insights and decision‑making for real‑time problems.

• Showcases deep learning‑based computer vision algorithms for enhanced pattern detection in different domains based on data‑centric approaches.

• Examines the role of the Internet of Things and machine learning algorithms for data‑driven systems.

• Highlights the applications of data‑driven systems and cloud computing in enhancing network performance.

This book is primarily written for senior undergraduates, graduate students, and academic researchers in diverse fields including electrical engineering, electronics and communications engineering, and computer science engineering.

This book comprehensively discusses the role of cloud computing in artificial intelligence‑based data‑driven systems and hybrid cloud computing for large data‑driven applications. It further explores new approaches, paradigms, and frameworks to meet societal challenges by providing solutions for critical insights into data. The text provides Internet of Things‑based frameworks and advanced computing techniques to deal with online/virtual systems.

This book:

• Covers the aspects of security, authentication, and prediction for data‑driven systems in heterogeneous environments.

• Provides data‑driven frameworks in combination with the Internet of Things, artificial intelligence, and computing to provide critical insights and decision‑making for real‑time problems.

• Showcases deep learning‑based computer vision algorithms for enhanced pattern detection in different domains based on data‑centric approaches.

• Examines the role of the Internet of Things and machine learning algorithms for data‑driven systems.

• Highlights the applications of data‑driven systems and cloud computing in enhancing network performance.

This book is primarily written for senior undergraduates, graduate students, and academic researchers in diverse fields including electrical engineering, electronics and communications engineering, and computer science engineering.

Augmented and Virtual Reality are revolutionizing present and future technologies: these are the fastest growing and most fascinating areas of technologies at present. This book aims to provide insight into the theory and applications of Augmented and Virtual Reality to multiple technologies such as IoT (Internet of Things), ML (Machine Learning), AI (Artifi cial Intelligence), Healthcare and Education.