The book examines leading Industry 4.0 and 5.0 and Industrial Internet of Things technologies enhanced with computational intelligence (CI) techniques. The book covers modelling, controls, estimations, applications, and systems. It considers this multi-disciplinary domain that is based on data collected from smart sensors.
The book examines leading Industry 4.0 and 5.0 and Industrial Internet of Things technologies enhanced with computational intelligence (CI) techniques. The book covers modelling, controls, estimations, applications, and systems. It considers this multi-disciplinary domain that is based on data collected from smart sensors.Hinweis: Dieser Artikel kann nur an eine deutsche Lieferadresse ausgeliefert werden.
Joseph Bamidele Awotunde is a Lecturer with the Computer Science Department, University of Ilorin, Ilorin, Nigeria. He has to his credit over 200 publications in reputable outlets such as Elsevier, Springer, Hindawi, and Taylor & Francis, among others, covering journals, edited conference proceedings, and chapters in books. He is also the editor of four books. Kamalakanta Muduli is an Associate Professor and Head of the School of Mechanical Engineering at Papua New Guinea University of Technology. Biswajit Brahma is a Senior Data and Visualization Engineer at McKesson, USA. His expertise is demonstrated by more than 50 publications in prestigious SCI/Scopus journals, showcasing his dedication to advancing knowledge in the fields of AI/ML and deep learning.
Inhaltsangabe
1. Industry 4.0: Challenges and Issues Encountered in Manufacturing and Testing of MEMS Devices. 2. The Industrial Internet of Things (IIoT): Overview, Architecture, Challenges, and Possible Solutions. 3. Artificial Intelligence in Industry 5.0: Transforming Manufacturing through Machine Learning and Robotics in Collaborative Age. 4. Computational Intelligence in the Industrial Internet of Things. 5. Security, Privacy, Trust, and Other Issues in Industries 4.0 and 5.0. 6. Fine-Tuning for a Deep Learning Model in Optimizing Ransomware Attack Detection in the Industry 4.0 and 5.0 Era. 7. Blockchain in Industry 4.0 and Industry 5.0: A Paradigm Shift towards Decentralized Efficiency and Autonomous Ecosystems. 8. Integration of Digital of Twins in Industries 4.0 and 5.0. 9. Computational Intelligence in Big Data Analytics. 10. The Role of Augmented Reality, Virtual Reality, and Mixed Reality in Industries 4.0 and 5.0. 11. Industry 4.0 Design Principles, Technologies, and Applications. 12. Industry 4.0 and Computational Intelligence for Fighting COVID-19: A Case Study.
1. Industry 4.0: Challenges and Issues Encountered in Manufacturing and Testing of MEMS Devices. 2. The Industrial Internet of Things (IIoT): Overview, Architecture, Challenges, and Possible Solutions. 3. Artificial Intelligence in Industry 5.0: Transforming Manufacturing through Machine Learning and Robotics in Collaborative Age. 4. Computational Intelligence in the Industrial Internet of Things. 5. Security, Privacy, Trust, and Other Issues in Industries 4.0 and 5.0. 6. Fine-Tuning for a Deep Learning Model in Optimizing Ransomware Attack Detection in the Industry 4.0 and 5.0 Era. 7. Blockchain in Industry 4.0 and Industry 5.0: A Paradigm Shift towards Decentralized Efficiency and Autonomous Ecosystems. 8. Integration of Digital of Twins in Industries 4.0 and 5.0. 9. Computational Intelligence in Big Data Analytics. 10. The Role of Augmented Reality, Virtual Reality, and Mixed Reality in Industries 4.0 and 5.0. 11. Industry 4.0 Design Principles, Technologies, and Applications. 12. Industry 4.0 and Computational Intelligence for Fighting COVID-19: A Case Study.
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