Machine Vision for Industry 4.0 : Applications and Case Studies book cover
1st Edition

Machine Vision for Industry 4.0
Applications and Case Studies

  • Available for pre-order. Item will ship after January 18, 2022
ISBN 9780367637125
January 18, 2022 Forthcoming by CRC Press
336 Pages 124 B/W Illustrations

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Book 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 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.

Table of 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 Direction’s

    Chapter 14. Industry 5.0: The Integration of Modern Technologies

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Dr. Roshani Raut is an Associate Professor in the Department of Computer Engineering at Vishwakarma Institute of Information Technology, Pune, India. In 2016 she received her PhD in Computer Science and Engineering from Amravati University, India. She has been a reviewer for various journals and conferences papers like Pattern Recognition, Elsevier, ASTESJ, IEEE-ICCUBEA-2016, IEEE-ICCUBEA-2017, ICSPC-2019, SPPU Symposium etc. She has been working as a TPC member for various international conferences. She is a PG recognized faculty of Pune University and guided more than 23 Master of Engineering Dissertations in the field of Data Mining, Machine Learning, Deep Learning software engineering, Incremental learning etc. She has published 7 patents. She has authored and co-authored more than 60 research articles published in national and international journals. Dr. Salah-ddine Krit is an Associate Professor at the Polydisciplinary Faculty of Ouarzazate, Ibn Zohr University Agadir Morocco, He is currently the Director of Engineering Science and Energies Laboratory and the Chief of Department of Mathematics, Informatics and Management. He received his PhD in Software Engineering from Sidi Mohammed Ben Abdellah University, Fez, Morroco. He worked as an Engineer Team Leader in audio and power management integrated circuits research, design, simulation and layout of analog and digital blocks dedicated for mobile and satellite communication systems. He authored and co-authored over 130 journal articles, proceedings, and book chapters published by reputable publishers Dr. Prasenjit Chatterjee is an Associate Professor of Mechanical Engineering Department at MCKV Institute of Engineering, India. He has published over 80 research papers in various international journals and has received numerous awards including Outstanding Researcher Award and University Gold Medal. He has been the Guest Editor of several special issues and has edited and authored several books on decision-making approaches and sustainability. He is the Lead Series Editor of International Perspectives on Decision Analysis and Operations Research, Emerald Group Publishing. Dr. Chatterjee is one of the developers of a new data-driven multiple-criteria decision-making method called Measurement of Alternatives and Ranking according to Compromise Solution (MARCOS).