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Computational Intelligence in Industry 4.0 and 5.0 Applications: Trends, Challenges and Applications: Advances in Computational Collective Intelligence

Editat de JOSEPH BAMIDELE AWOTUNDE, Kamalakanta Muduli, BISWAJIT BRAHMA
en Limba Engleză Hardback – 6 feb 2025
Industry 4.0 and 5.0 applications will revolutionize production, enabling smart manufacturing machines to interact with their environments. These machines will become self-aware, self-learning, and capable of real-time data interpretation for self-diagnosis and prevention of production issues. They will also self-calibrate and prioritize tasks to enhance production quality and efficiency.
Computational Intelligence in Industry 4.0 and 5.0 Applications examines applications that merge three key disciplines: Computational Intelligence (CI), Industry 4.0, and Industry 5.0. It presents solutions using Industrial Internet of Things (IIoT) technologies, augmented by CI-based techniques, modeling, controls, estimations, applications, systems, and future scopes. These applications use data from smart sensors, processed through enhanced CI methods, to make smart automation more effective.
Industry 4.0, integrates data and intelligent automation into manufacturing, using technologies like CI, IoT, IIoT, and Cloud Computing. It transforms data into actionable insights for decision-making and process optimization, essential for modern competitive businesses managing high-speed data integration in production processes. Currently, Industry 4.0 and 5.0 are undergoing significant transformations due to advances in applying AI, big data analytics, telecommunication technologies, and control theory. These applications are increasingly multidisciplinary, integrating mechanical, control, and information technologies. However, they face such technical challenges as parametric uncertainties, external disturbances, sensor noise, and mechanical failures. To address these, this book examines such CI technologies as fuzzy logic, neural networks, and reinforcement learning and their application to modeling, control, and estimation. It also covers recent advancements in IIoT sensors, microcontrollers, and Big Data Analytics that further enhance CI-based solutions in Industry 4.0 and 5.0 systems.
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Specificații

ISBN-13: 9781032539225
ISBN-10: 1032539224
Pagini: 360
Ilustrații: 120
Dimensiuni: 156 x 234 mm
Ediția:1
Editura: CRC Press
Colecția Auerbach Publications
Seria Advances in Computational Collective Intelligence

Locul publicării:Boca Raton, United States

Public țintă

Academic

Cuprins

1. Industry 4.0: Challenges and Issues Encountered in Manufacturing and Testing of MEMS Devices 2. The Industrial Internet of Things (IIoT): Overview, Architecture, and Challenges 3. Artificial Intelligence in Industry 5.0: Transforming Manufacturing through Machine Learning and Robotics in Collaborative age 4. Computational Intelligence in Industrial Internet of Things 5. Security, Privacy, Trust, and Other Issues in Industries 4.0 and 5.0 6. Fine-Tuning for Deep Learning Model in Optimizing Ransomware Attack Detection on 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 Industry 4.0 and 5.0 9. Computational Intelligence in Big Data Analytics 10. The Role of Augmented Reality, Virtual Reality, and Mixed Reality in Industry 4.0 and 5.0 11. Industry 4.0 Design Principles

Notă biografică

Joseph Bamidele Awotunde is  Lecturer II at the Computer Science Department, University of Ilorin, Ilorin, Nigeria. He is the author of more than 40 articles, 30 chapters in book, 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.

Descriere

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.