
Computational Intelligence in the Industry 4.0
- 262 pages
- English
- ePUB (mobile friendly)
- Available on iOS & Android
Computational Intelligence in the Industry 4.0
About this book
This book discusses the importance of using industrial intelligence in collaboration with computational intelligence in forming a smart system for diverse applications. It further illustrates the challenges and deployment issues in industrial resolution. The text highlights innovation and applications of computational agents and the industrial intelligence era to automate the requirements as per Industry 4.0.
This book:
- Discusses computational agents for handling automation issues and the role of ethics in industrial resolution
- Presents intelligence approaches for products, operations, systems, and services
- Illustrates the fundamentals of computational intelligence to forecast and analyze the requirements of society for automation as well as recent innovations and applications
- Highlights computation intelligence approaches in reducing human effort and automating the analysis of the production unit
- Showcases current innovation and applications of computational agents and industrial intelligence as per Industry 4.0
The text is primarily written for senior undergraduate and graduate students, and academic researchers in diverse fields including electrical engineering, electronics, and communication engineering, industrial engineering, manufacturing engineering and computer science, and engineering.
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Information
Table of contents
- Cover
- Half Title
- Series Page
- Title Page
- Copyright Page
- Table of Contents
- Preface
- About the editors
- Contributors
- 1 Introduction to automation
- 2 RPA and test automation
- 3 Intelligent computing relating to cloud computing
- 4 Communication protocols used for industrial automation
- 5 Market Watch
- 6 Study on cybersecurity: Trending challenges, emerging trends, and threats
- 7 Intelligence approaches for products, operations, systems, and services
- 8 Parkinson’s disease detection using machine learning models
- 9 A comparison between nonlinear mapping and high-resolution image
- 10 Deployment issues in industrial resolution
- 11 Hate speech detection using machine learning models
- 12 Digital twin technology for industrial automation
- 13 A theoretical analysis of simple retrieval engine
- Index
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