Edge AI for Industry 5.0 and Healthcare 5.0 Applications

Auteur

Pethuru Raj is a chief architect at Reliance Jio Platforms Ltd. (JPL) Bangalore. Previously. worked in IBM global Cloud centre of Excellence (CoE), Wipro consulting services (WCS), and Robert Bosch Corporate Research (CR). He has more than 22 years of IT industry experience and 8 years of research experience.

B. Sundaravadivazhagan obtained PhD in computer science from Anna University, Chennai India. Currently, he is a faculty member of the Department of Information Technology at the University of Technology and Applied Science-AL Mussanah in Oman He has professional memberships in ISACA and ISTE and is a senior member of IEEE. His academic and research background spans more than 21 years at many institutions.

Saleem Raja is an associate professor in the department of information technology at the Shinas University of Technology and Applied Sciences in the Sultanate of Oman. He obtained a Ph.D. in 2017 in the general field of data mining as well as my M.Tech. in information technology from Bharathidasan University in Tamil Nadu, India. He has published more than 25 research papers published in national and international journals, conferences, and book chapters.

Mohammed M. Alani holds a PhD in Computer Engineering with specialization in network security. He has worked as a professor, and a cybersecurity expert in many countries around the world. His experience includes serving as VP of Academic Affairs in the United Arab Emirates, network and security consultancies in the Middle East, and Cybersecurity Program Manager in Toronto Canada. He currently works as a Cybersecurity Professor at Seneca College, and a Research Fellow at Toronto Metropolitan University, Toronto, Canada.

Texte du rabat

This book looks at the unique contributions of edge AI for envisaging and implementing sophisticated business solutions for Industry 5.0 and Healthcare 5.0. It explains how Industry 5.0 fine tunes the human-machine connection and leverages tiny, high-performance AI-centric processors in IoT edge devices for real-time application processing.

Contenu

1 Digital Twins for Smart Grids 2 Delineating the Healthcare 5.0 3 Virus Dispersion in Environment: Fuzzy Approach for Infectious Diseases 4 Revolutionizing COVID-19 Diagnosis: A Hybrid Quantum Neural Network-based Framework for Accurate Detection of Lung Abnormalities from CT Scans using a Custom Computer Vision Model and AI Edge Device 5 The Role of Explainable AI for Healthcare 5.0: Best Practices, Challenges, and Opportunities 6 Explainable AI for Healthcare 5.0: Enhancing Transparency and Trust 7 A Complete Analysis of Explainable AI and its methods for Healthcare Prediction 8 Artificial Intelligence (AI) Algorithms and Approaches for Edge AI 9 Integrating Fuzzy Clustering into CNN for Improved Brain Tumour Detection 10 Leveraging Edge AI for Real-Time Detection and Prevention of Online Harassment and Cyberbullying: Enhancing Women's Safety and Mental Health 11 Leveraging Artificial Intelligence and IoT for Health Care 5.0: Use Cases, Applications, and Challenges 12 Unleashing Patient Insights: Leveraging Edge AI in Sentiment Analysis for Enhanced Healthcare Experiences 13 Edge AI in LoRa-Based Health Monitoring 14 IoT Based Smart Health Monitoring with Convulational Neural Network (CNN) Using Edge Computing 15 Enhancing Healthcare Monitoring through IoT, CNN, and Edge Computing Technologies 16 Delineating the Need of 5G Communication Networks 17 The Fusion of IoT, AI, Edge Cloud, and Blockchain 18 Trustworthiness of Blockchain Technology in Healthcare 5.0 and Industry 5.0 19 The Future of Trust: Exploring the Potential of Blockchain Technology 20 Demystifying the Industry 5.0 Version 21 Edge-AI for Connected Healthcare in Internet of Medical Things for Smart Cities