Autorentext

Professor Bal Virdee is Director of the Centre for Communications Technology Research Group at London Metropolitan University, london UK. His research is in the area of microwave wireless communications encompassing 5G Mobile phones to satellite technology.

Dr. Ummer Iqbal is presently working as a Scientist-D at NIELIT Srinagar, India. He completed his M.Tech and Ph.D from NIT Srinagar in 2015 and 2022 respectively. His areas of research include IoT Security, information security, and open-source technologies.

Dr. Ashish Khanna is a Professor at Maharaja Agrasen Institute of Technology, India. He received his Ph.D. degree from National Institute of Technology, Kurukshetra in March 201. His research interest includes Distributed Systems and its variants (MANET, FANET, VANET, IoT), Machine learning, and Evolutionary computing.

Dr. Moolchand Sharma is currently an Assistant Professor in the Department of Computer Science and Engineering at the Maharaja Agrasen Institute of Technology, GGSIPU Delhi, India. His research areas include Artificial Intelligence, Nature-Inspired Computing, Security in Cloud Computing, Machine Learning, and Search Engine Optimization. He is associated with various professional bodies like IEEE, ISTE, IAENG, ICSES, UACEE, Internet Society, and life membership of the Universal Innovators Research Lab.

Prof. Roman Danel is a researcher with the Department of Mechanical Engineering, Faculty of Technology, Institute of Technology and Businesses (VTE), eské Bud jovice, Czech Republic. He received his P.Eng. degree in automation and control systems from the VB- Technical University of Ostrava, in 1989, and the Ph.D. degree in automation of technological processes from VB- Technical University of Ostrava, in 2002. His research interests include information systems and automatic control in industry, databases, programming languages, and software.

Klappentext

This book explores the convergence of artificial intelligence (AI) and the Internet of Things (IoT) in transforming healthcare delivery. It provides a comprehensive overview of AIoT healthcare systems, covering concepts, architectures, applications, challenges, and future directions.

Transforming Healthcare with AI and IoT: Intelligent Solutions for a Digital Future delves into core AI and IoT concepts, it explores their integration in healthcare settings, and showcases real-world examples. Readers will gain valuable insights into how AI and IoT are already revolutionizing healthcare delivery, inspiring them with tangible examples of success. Through real-world case studies and practical insights, readers will learn how AI and IoT can optimize resource allocation, improve patient outcomes, and enhance overall system sustainability. It covers topics including big data analytics, personalized medicine, smart hospitals, telehealth, and virtual care. The book also addresses ethical considerations, security concerns, and challenges in deploying AIoT healthcare systems.

The book is primarily written for professionals and researchers involved in healthcare management, information technology, and AI. Additionally, undergraduate and graduate students studying healthcare technology, AI, or related fields would also find it invaluable.

Inhalt

Chapter 1 The Rise of Artificial Intelligence in Healthcare. Chapter 2 Smart Hospitals and IoT-based Healthcare Automation. Chapter 3 Machine Learning Approaches for Air Quality Index (AQI) Prediction: A Comparative Study. Chapter 4 FLAME: A Federated Learning Adaptive Multi-Modal Edge Framework for Real-Time Healthcare Decision Support Systems. Chapter 5 Edge Computing in Healthcare: Enhancing Efficiency and Patient Care. Chapter 6 Adversarial Intelligence in Healthcare: Enhancing Alzheimer's Diagnosis through AI-Driven Innovations. Chapter 7 Sustainable Healthcare Transformation: The Role of AI and IoT in Environmental Efficiency. Chapter 8 An IoT-based Model for Air Quality Monitoring to Enable Telehealth for Asthma Patients: Facilitating a Way to Healthcare 5.0. Chapter 9 Advancements in Generative Adversarial Networks for Synthetic Data Generation: A Comprehensive Analysis. Chapter 10 Using Strategic Operational Research Models for AI-Augmented Healthcare Logistics, Accessibility, and Cost-Cutting Projects. Chapter 11 Cloud Computing: A Practical Framework for Smart City Development as Future Perspective. Chapter 12 Advances in Brain Tumor Segmentation Using Transformer Models. Chapter 13 Enhancing EEG-based Brain Attack Detection Using a Hybrid Genetic Random Forest Classifier. Chapter 14 A Model Utilizing Stacking Classifiers for Identifying Heart Irregularities and Forecasting Cardiovascular Disease. Chapter 15 Role of Machine Learning and Deep Learning in Medical Decision-Making. Chapter 16 Applications of Medical Images and Diagnostics Chapter 17 AI and IoT Integration for Remote Patient Monitoring