6G-Enabled IoT and AI for Smart Healthcare

Description:

In today’s era, there is a need for a system that can automate the process of treatment for the patient if medical facilities are out of reach. Smart healthcare can step in to make the patient more self-dependent. 6G with its features can be seen as the future of smart healthcare with IoT and AI.

6G-Enabled IoT and AI for Smart Healthcare: Challenges, Impact, and Analysis offers the fundamentals, history, reality, and challenges faced in the smart healthcare industry today. It discusses the concepts, tools, and techniques of smart healthcare as well as the analysis used. The book details the role that machine learning-based deep learning and 6G-enabled IoT concepts play in the automation of smart healthcare systems. The book goes on to presents applications of smart healthcare through various real-world examples and includes chapters on security and privacy in the 6G-enabled and IoT environment, as well as research on the future prospects of the smart healthcare industry.

This book:

• Offers the fundamentals, history, reality, and the challenges faced in the smart healthcare industry
• Discusses the concepts, tools, and techniques of smart healthcare as well as the analysis used
• Details the role that machine learning-based deep learning and 6G-enabled IoT concepts play in the automation of smart healthcare systems
• Presents applications of smart healthcare through various real-world examples
• Includes topics on security and privacy in 6G-enabled IoT, as well as research and future prospectus of the smart healthcare industry

Interested readers of this book 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.

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Preface

With the development of information technology, smart healthcare has become imperative for the new generation. Smart healthcare incorporated technologies like IoT, machine learning, and deep learning to transform the traditional medical system. Smart healthcare aims to make the healthcare system more efficient, convenient, and personalized for each user. The key to success is addressing the existing system’s problems and providing a solution that can be implemented in real-time scenarios. Enhancing healthcare quality and improving access to health records while maintaining reasonable costs is challenging for healthcare organizations globally. An aging population implies an increase in chronic diseases requiring frequent visits to healthcare providers and increased hospitalization needs. The rise in the number of patients requiring constant care significantly increases medical treatment costs. Over the past few decades, Information and Communication Technologies (ICT) have been widely adopted in the healthcare environment to make healthcare access and delivery more accessible and cost-effective. The use of ICT has led to the development of electronic health record (EHR) systems. EHRs contain complete patient health history (current medications, immunizations, laboratory results, current diagnosis, and so on) and can be easily shared among various providers. The adoption of ICT in the health sector is generally referred to as digital healthcare.

Over the years, digital healthcare has extended from maintaining electronic patient data and providing patient web portals to allowing further flexibility and convenience in healthcare management. It is commonly referred to as connected health, such as smartphones, mobile applications, and wireless technologies, allowing patients to connect readily with their providers without visiting them frequently. Conventional mobile devices (such as smartphones) are used together with wearable medical devices (such as blood pressure monitors, glucometers, smart watches) and Internet of Things (IoT) gadgets to enable continuous patient monitoring and treatment at their homes. Smart health is expected to keep hospitalization expenses low and provide timely treatment for various medical ailments by placing IoT sensors on health monitoring equipment. The information collected by these microchips can then be sent to any remote destination. The collected data are then forwarded to a local gateway server via a Wi-Fi network so end systems (such as a physician’s laptop) can retrieve the collected data from the gateway server. Regular server updates allow physicians access to real-time patient data. These devices work together to create a unified medical report that various providers can access.

This book aims to publish original and innovative research works focusing on smart healthcare challenges using 6G and IoT. This book discusses the 6G-enabled IoT with AI and machine learning-based medical facilities to provide a solution that can be implemented in real-time scenarios. Also, the sensors can be integrated with 6G to give the regular server update, allowing physicians access to real-time patient

data is incorporated. These devices will create a unified medical report that various providers can access. Smart healthcare aims to make the healthcare system more efficient, convenient, and personalized for each user. Smart healthcare incorporated technologies like IoT, machine learning, and deep learning to transform the traditional medical system. This book is a result of the handwork of many researchers around the globe. The book contains theoretical and practical knowledge of state-ofthe-art IoT, 6G technologies, and their applications that introduce the readers to how these applications can apply to smart healthcare.

Ashish Kumar, Rachna Jain, Meenu Gupta, and Sardar M.N. Islam

Table of contents :
Cover
Half Title
Series Page
Title Page
Copyright Page
Contents
Preface
Editors
Contributors
Chapter 1: Introduction to Smart Healthcare: Healthcare Digitization
Chapter 2: AI and IoT for Smart Healthcare: Background and Preliminaries
Chapter 3: Security and Privacy Issues in Smart Healthcare Using Machine-Learning Perspectives
Chapter 4: A Framework for Virtual Reality in Healthcare: Insight for Disaster Preparation
Chapter 5: Mobile Healthcare Applications: Critical Privacy and Security Issues, Challenges, and Solutions
Chapter 6: 6G-Enabled IoT for e-Healthcare Systems: Emergence and Upgradation
Chapter 7: Machine Learning in Healthcare Cybersecurity: Role of Human Activity Recognition and Impact of 6G in Smart Healthcare
Chapter 8: 6G-Enabled IoT Wearable Devices for Elderly Healthcare
Chapter 9: 6G-Based Smart Healthcare Solutions: Beyond Industry 4.0 Trends and Products
Chapter 10: Influence of AI and 6G-Enabled IoT in Smart Healthcare: Challenges and Solutions
Chapter 11: Success Stories for IoT-Enabled 6G for Prediction and Monitoring of Infectious Diseases with Artificial Intelligence
Chapter 12: Emerging Internet of Things (IoTs) Scenarios Using Machine Learning for 6G Over 5G-Based Communications
Chapter 13: 6G: Technology, Advancement, Barriers, and the Future
Index