- ホーム
- > 洋書
- > 英文書
- > Computer / General
Full Description
This book discusses the use of machine vision and technologies in specific engineering case studies and focuses on how machine vision techniques are impacting every step of industrial processes and how smart sensors and cognitive big data analytics are supporting the automation processes in Industry 4.0 applications.
Industry 4.0, the Fourth Industrial Revolution, combines traditional manufacturing with automation and data exchange. Machine vision is used in the industry for reliable product inspections, quality control, and data capture solutions. It combines different technologies to provide important information from the acquisition and analysis of images for robot-based inspection and guidance.
Features
Presents a comprehensive guide on how to use machine vision for Industry 4.0 applications, such as analysis of images for automated inspections, object detection, object tracking, and more
Includes case studies of Robotics Internet of Things with its current and future applications in healthcare, agriculture, and transportation
Highlights the inclusion of impaired people in the industry, for example, an intelligent assistant that helps deaf-mute individuals to transmit instructions and warnings in a manufacturing process
Examines the significant technological advancements in machine vision for Industrial Internet of Things and explores the commercial benefits using real-world applications from healthcare to transportation
Discusses a conceptual framework of machine vision for various industrial applications
The book addresses scientific aspects for a wider audience such as senior and junior engineers, undergraduate and postgraduate students, researchers, and anyone interested in the trends, development, and opportunities for machine vision for Industry 4.0 applications.
Contents
Chapter 1. Challenges in Industry 4.0 for Machine Vision: A Conceptual Framework, A Review, and Numerous case studies, Chapter 2. Practical issues in robotics internet of things, Chapter 3. Role of sensing techniques in precision agriculture, Chapter 4. Perspectives on Deep Learning Techniques for Industrial IoT, Chapter 5. Missing person locator and identifier using artificial intelligence and supercomputing techniques proposal, Chapter 6. Inclusion of Impaired People in Industry 4.0: An Approach to Recognize Orders of Deaf-mute Supervisors through an Intelligent Sign Language Recognition System, Chapter 7. A Deep Learning Approach to Classify the Causes of Depression from Reddit Posts, Chapter 8. Psychiatric ChatBOT for COVID-19 using Machine Learning Approaches, Chapter 9. An Analysis of Drug - Drug Interaction (DI) using Machine Learning Techniques in Drug Development Process, Chapter 10. Image Processing based Fire Detection using IOT devices, Chapter 11. Crowd Estimation in Train by using Machine Vision, Chapter 12. Analysis of Machine Learning Algorithm to predict Wine Quality, Chapter 13. Machine Vision in Industry 4.0: Applications, Challenges and Future Directions, Chapter 14. Industry 5.0: The Integration of Modern Technologies
