The book explores the intersection of cutting-edge technologies and industrial trends. Researching Artificial Intelligence, machine learning, and data analytics, it examines the transformative potential of computational intelligence in shaping the future of manufacturing and services.
The book explores the intersection of cutting-edge technologies and industrial trends. Researching Artificial Intelligence, machine learning, and data analytics, it examines the transformative potential of computational intelligence in shaping the future of manufacturing and services.
Joseph Bamidele Awotunde is a Lecturer II at the Computer Science Department, University of Ilorin, Ilorin, Nigeria. He is the author of more than 40 articles, 30 chapters in books, and more than 25 conference proceedings. Kamalakanta Muduli is an Associate Professor in Papua New Guinea University of Technology. Biswajit Brahma is a Senior Data Engineer at McKesson, USA.
Inhaltsangabe
1. Fundamentals of AI, ML, and Their Relevance to Industry 4.0 and 5.0 2. Deep Learning Architectures in Industrial Automation and Robotics 3. Advancements in Computational Intelligence for Enhanced Big Data Analytics in Industry 4.0 and 5.0: Challenges, Advances, and Future Perspectives 4. Integration of AI- and ML-based Algorithms in Cyber-Physical Systems for Predictive Maintenance 5. Applications and Innovations of Edge Computing in Industry 4.0 and 5.0 6. Integration of Deep Learning and Optimization Techniques for Enhanced Efficiency and Decision-Making in Industry 4.0 and 5.0 7. Fuzzy Logic and Expert Systems for Decision Support in Cyber-Physical Production Systems 8. Industry 4.0: A Review on Energy Conservation in MEMS 9. Enabling Technologies for Seamless Human-Machine Interaction in Industry 5.0 10. Face Recognition Access Control System Using Hidden Markov Model 11. Human-Centric Design Principles in Industry 4.0 and 5.0 12. Failure Prediction Using Machine Learning and Deep Learning in Industry 4.0 and 5.0: A Multi-Instance-Based Case Study 13. The Protection of Industry 4.0 and 5.0: Cybersecurity Strategies and Innovations 14. Privacy and Security Challenges of AI Integration in Industry 4.0 and 5.0 15. Optical and Quantum Computing in Industry 4.0 and 5.0 16. Blockchain Technologies in Industry 5.0: A Review of the Applications, Challenges and Future Prospects 17. Industry 5.0: A New Industrial Revolution and Technological Applications
1. Fundamentals of AI, ML, and Their Relevance to Industry 4.0 and 5.0 2. Deep Learning Architectures in Industrial Automation and Robotics 3. Advancements in Computational Intelligence for Enhanced Big Data Analytics in Industry 4.0 and 5.0: Challenges, Advances, and Future Perspectives 4. Integration of AI- and ML-based Algorithms in Cyber-Physical Systems for Predictive Maintenance 5. Applications and Innovations of Edge Computing in Industry 4.0 and 5.0 6. Integration of Deep Learning and Optimization Techniques for Enhanced Efficiency and Decision-Making in Industry 4.0 and 5.0 7. Fuzzy Logic and Expert Systems for Decision Support in Cyber-Physical Production Systems 8. Industry 4.0: A Review on Energy Conservation in MEMS 9. Enabling Technologies for Seamless Human-Machine Interaction in Industry 5.0 10. Face Recognition Access Control System Using Hidden Markov Model 11. Human-Centric Design Principles in Industry 4.0 and 5.0 12. Failure Prediction Using Machine Learning and Deep Learning in Industry 4.0 and 5.0: A Multi-Instance-Based Case Study 13. The Protection of Industry 4.0 and 5.0: Cybersecurity Strategies and Innovations 14. Privacy and Security Challenges of AI Integration in Industry 4.0 and 5.0 15. Optical and Quantum Computing in Industry 4.0 and 5.0 16. Blockchain Technologies in Industry 5.0: A Review of the Applications, Challenges and Future Prospects 17. Industry 5.0: A New Industrial Revolution and Technological Applications
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