Covering, methodologies, technologies, approaches, models, frameworks, theory, and practice, this book examines how to meet the challenges associated with applying AI-collaborative IoT technology as well as Big Data in the design and implementation of advanced infrastructure for the smart healthcare system.

Dr. Alex Khang, is a professor in information technology, D.Sc. D.Litt., AI and data scientist, software industry expert, and the chief of technology officer (AI and Data Science Research Center) at the Global Research Institute of Technology and Engineering, North Carolina, United States. He has over 28 years of teaching and research experience in information technology at the Universities of Science and Technology in Vietnam, India, and USA. He has published 52 authored books (in computer science 2000-2010), 2 authored books (software development), and 20 book chapters. He has published 10 edited books, and 11 edited books (calling for book chapters) in the fields of AI ecosystem (AI, ML, DL, IoT, Robotics, Data science, Big data, and Quantum computing), smart city ecosystem, healthcare ecosystem, Fintech technology, and blockchain technology (since 2020). He has over 28 years of working experience as a software product manager, data engineer, AI engineer, cloud computing architect, solution architect, software architect, database expert in the foreign corporations of Germany, Sweden, the United States, Singapore, and multinationals (former CEO, former CTO, former Engineering Director, Product Manager, and Senior Software Production Consultant). ORCID: 0000-0001-8379-4659.

Preface. Acknowledgments. About the Editor. List of Contributors. Chapter 1 The Era of the Digital Healthcare System and Its Impact on Human Psychology. Chapter 2 Factors Influencing Mental Health and the Role of Artificial Intelligence (AI) in the Era of Climate Change. Chapter 3 Role of IoT and AI in Sustainable Management of the Pharmaceutical Industry. Chapter 4 AI-Integrated IoT in Healthcare Ecosystem: Opportunities, Challenges, and Future Directions. Chapter 5 IoT-Based Classification of COVID-19 Using Feature Extraction and Hybrid Architectures of Convolutional Neural Network (CNN). Chapter 6 Revolutionizing Healthcare Delivery: Applications and Impact of Cutting-Edge Technologies. Chapter 7 Utilizing Artificial Neural Networks (ANN) and Deep Learning (DL) in Extended Reality Environments for Addressing Psychological Issues. Chapter 8 Augmented Reality (AR) and Virtual Reality (VR) Technologies in Surgical Operating Systems. Chapter 9 Sensor Scheduling in an IoT Health Monitoring System with Interference Awareness. Chapter 10 Cardiovascular Disease Detection Using Deep Learning and Nature-Inspired Optimization Algorithm. Chapter 11 Internet of Things (IoT) Smart Wearable Sensors in Healthcare. Chapter 12 Preventing Sepsis in ICU by Analyzing Patients with Big Data Using Tableau Application. Chapter 13 Revolutionizing Healthcare with IoT: Connecting the Dots for Better Patient Outcomes. Chapter 14 Diabetes and Machine Learning: A Mathematical Perspective. Chapter 15 Disease Detection for Herbal Plants Using ResNet Algorithm. Chapter 16 Robotics in Real-Time Applications in Healthcare Systems. Chapter 17 Healthcare Internet of Things (HIoT) Technologies and Implementation. Chapter 18 Healthcare Data Analytics, Visualization Tools, and Applications. Chapter 19 Applications of Internet of Things (IoT) Technologies in the Fields of Business and Healthcare. Chapter 20 Internet of Things (IoT) Case Studies and Application. Chapter 21 Cybersecurity Infrastructure and Solutions for Healthcare Systems. Chapter 22 Securing the Internet of Things (IoT) Environment Using Bio-Inspired Meta-Heuristic Methodologies . Chapter 23 Internet of Things (IoT)-Based Technologies for Reliability Evaluation with Artificial Intelligence (AI). Index.