Edge AI for Industry 5.0 and Healthcare 5.0 Applications (eBook, ePUB)

Redaktion: Raj, Pethuru; Alani, Mohammed M.; Raja, A. Saleem; Sundaravadivazhagan, B.

• Format: ePub

Produktbeschreibung

Edge AI is the seamless and spontaneous combination of Edge or Fog computing and AI. It enables acquiring real-time insights, which, in turn, leads to the realization of real-time, people-centric, event-driven, business-critical, process-aware, and knowledge-filled software services and applications.

Edge AI for Industry 5.0 and Healthcare 5.0 Applications looks at the unique contributions of Edge AI for developing 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 decision-making and application processing.

Focusing on Explainable AI (XAI), the book discusses:

• The role of XAI in Healthcare 5.0
• Best practices, challenges, and opportunities of applying XAI in healthcare setting
• How to enhance transparency and trust of XAI in Healthcare 5.0
• XAI and its methods in predicting healthcare outcomes

Other highlights of the book include:

• 5G communication networks requirements
• The fusion of IoT, AI, Edge, Cloud, and blockchain
• Trustworthiness of blockchain technology in healthcare 5.0 and Industry 5.0
• The future of trust and the potential of blockchain technology

By explaining how Edge AI can transform healthcare and industry, this book empowers researchers and professionals to envisage and implement sophisticated and smart digital solutions.

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Produktdetails

• Verlag: Taylor & Francis eBooks
• Erscheinungstermin: 4. April 2025
• Englisch
• ISBN-13: 9781040312124
• Artikelnr.: 73379504

Autorenporträt

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.

Inhaltsangabe

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