Description
The text emphasizes the need for data pre-processing, classification and prediction, cluster analysis, mining multimedia, and advanced machine learning techniques for scientific programming in Industry 5.0.
- Addresses how the convergence of intelligent systems and 5G wireless systems will solve industrial problems such as autonomous robots, and self-driving cars
- Highlights the methods of smart things in collaborative autonomous fleets and platforms for integrating applications across different business and industry domains
- Discusses important topics such as the Internet of robotic things, cloud robotics, and cognitive architecture for cyber-physical robotics
- Explains image compression, and advanced machine learning techniques for scientific programming in Industry 5.0
- Presents a detailed discussion of smart manufacturing techniques, industrial Internet of things, and supply chain management in Industry 5.0
The text is primarily written for graduate students and academic researchers in the fields of industrial engineering, manufacturing engineering, electrical engineering, production engineering, and mechanical engineering.
Table of Contents
1. From Industry 4.0 to Industry 5.0. 2. Assessing the Impact of Industry 5.0 on Sustainability Strategies. 3. Digital Industrial Revolution: From Sustainability Perspective. 4. Machine Learning for Supply Chain Management in Industrial 4.0 Era: A Bibliometric Analytics. 5. Transforming Industry 5.0: Real-Time Monitoring and Decision-Making with IIoT. 6. Sustainable Transformation: Energy Efficiency and Renewable Energy in Industry 5.0. 7. A study of Cloud of Things enabled Machine learning based Smart health monitoring system. 8. Lung Cancer Classification using CNN: Addressing Class Imbalance and Model Performance Analysis. 9. Water Quality forecasting using Deep Learning: Astudy of the Brahmaputra Basin. 10. Multimodal Fusion Techniques for Enhanced Fake News Detection: A Robustly Optimized BERT and Vision Transformer Approach.
