This book presents the role of AI-Driven Digital Twin in the Industry 4.0 ecosystem by focusing on Smart Manufacturing, sustainable development, and many other applications. It also discusses different case studies and presents an in-depth understanding of the benefits and limitations of using AI and Digital Twin for industrial developments.
AI-Driven Digital Twin and Industry 4.0: A Conceptual Framework with Applications introduces the role of Digital Twin in Smart Manufacturing and focuses on the Digital Twin framework throughout. It provides a summary of the various AI applications in the Industry 4.0 environment and emphasizes the role of advanced computational and communication technologies. The book offers demonstrative examples of AI-Driven Digital Twin in various application domains and includes AI techniques used to analyze the environmental impact of industrial operations along with examples. The book reviews the major challenges in the deployment of AI-Driven Digital Twin in the Industry 4.0 ecosystem and presents an understanding of how AI is used in the designing of Digital Twin for various applications. The book also enables familiarity with various industrial applications of computational and communication technologies and summarizes the ongoing research and innovations in the areas of AI, Digital Twin, and Smart Manufacturing while also tracking the various research challenges along with future advances.
This reference book is a must-read and is very beneficial to students, researchers, academicians, industry experts, and professionals working in related fields.
Table of Contents:
1. Industry 4.0: Framework and Applications. 2. Artificial Intelligence Applications in Industry 4.0: Applications and Challenges. 3. Role of Artificial Intelligence in Industry 4.0: Applications and Challenges. 4. Digital Twin Technology: A Review. 5. Digital Twin in Industry 4.0: Application Areas and Challenges. 6. Digital Twin: Enabling Technologies, Applications, and Challenges. 7. Big Data Analytics with Digital Twin for Industrial Applications. 8. AI-Driven Digital Twin: Conceptual Framework and Applications. 9. AI-Driven Digital Twin for Healthcare Applications. 10. Application of Artificial Intelligence in Resource-Poor Health Care. 11. Artificial Intelligence and Internet of Things (IoT) Facilitated Digital Twin for Industry 4.0 Application Domains. 12. AI-Driven Digital Twin and Resource Optimization in Industry 4.0 Ecosystem. 13. Digital Twin for Sustainable Industrial Development. 14. Environmental Impacts of Industrial Processes in Industry 4.0 Ecosystem: Artificial Intelligence Approach. 15. Digital Twin for Sustainable Industrial Development. 16. AI-Driven Digital Twin for Industrial Engineering Applications. 17. Role of Digital Twin in the Design and Development of Smart Cities. 18. Impact of Hybrid [CPU+GPU] HPC Infrastructure on AI/ML Techniques in Industry 4.0. 19. Image Sensing for Industry 4.0 Using Auto Resonance Networks: A Case Study
About the Author :
Dr. Sita Rani is a faculty member of the Dept of Computer Science and Engineering at Guru Nanak Dev Engineering College, Ludhiana. She earned her Ph.D. in Computer Science and Engineering from I.K. Gujral Punjab Technical University, Kapurthala, Punjab in 2018 and has more than 20 years of teaching experience.She completed her Post Graduate Certificate Program in Data Science and Machine Learning from the Indian Institute of Technology, Roorkee in 2023. Dr. Rani also completed her Postdoc from Big Data Mining and Machine Learning Lab, South Ural State University, Russia in August 2023.She is an active member of ISTE, IEEE, and IAEngg and is the recipient of the ISTE Section Best Teacher Award 2020, and the International Young Scientist Award 2021. Dr. Rani has contributed to various research activities while publishing articles in renowned journals and conference proceedings. She has published three international patents and has delivered many expert talks in A.I.C.T.E. sponsored Faculty Development Programs along with organizing many International Conferences. Her research interests include Parallel and Distributed Computing, Machine Learning, the Internet of Things (IoT), Healthcare, and Digital Twin.
Dr. Pankaj Bhambri is working in the Department of Information Technology at Ludhiana’s Guru Nanak Dev Engineering College. He also serves as the Institute’s Coordinator, Skill Enhancement Cell, and has almost 20 years of experience as a teacher. Dr. Bhambri earned his M.Tech. (CSE) and his B.E. (IT) with honors from the I.K.G. Punjab Technical University, Jalandhar, India, and the Dr. B.R. Ambedkar University, Agra, India, respectively. He earned a doctorate in computer science and engineering from the I.K.G. Punjab Technical University, Jalandhar, India, and for a long span, he served the additional duties of an Assistant Registrar (Academic), Member (Academic Council), Member (BoS), Member (RAC), Hostel Warden, APIO, and NSS Coordinator for his institute. His research has appeared in a variety of prestigious international/national journals and conference proceedings. Dr. Bhambri has contributed to numerous textbooks as an editor/author and filed several patents. As a result of his outstanding social and academic/research accomplishments over the past two decades, Dr. Bhambri has been awarded the ISTE Best Teacher Award 2022 and 2023, I2OR National Award 2020, Green ThinkerZ Top 100 International Distinguished Educators – 2020, I2OR Outstanding Educator Award – 2019, as well as other prestigious awards in previous years and countless other accolades from various government and non-profit organizations. He has supervised many undergraduate/postgraduate research projects/dissertations and is now supervising multiple Ph.D. research work. He organized numerous courses while receiving funding from the AICTE, TEQIP, and others. His current research and expertise are in Machine Learning, Bioinformatics, Wireless Sensor Networks, and Network Security.
Dr. Sachin Kumar earned his Ph.D. at IIT Roorkee in 2017 in Data Mining. He is working as a Leading Researcher at the Big Data and Machine Learning Research Lab at South Ural State University, Chelyabinsk, Russia. Additionally, He is the Head of the Data Mining and Virtualization Laboratory and an Associate Professor in the Computer Science Department. He has 12 years of teaching and 8 years of research experience in international institutions of repute. Dr. Kumar served as a guest editor in a reputed journal and is an active member of the reviewer committee in several international journals. He has also delivered several talks at the international conference and FDP programs sponsored by AICTE India. His research areas are IoT, Computer Vision, Smart City, Intelligent Transportation Systems, Smart Healthcare, Internet of Medical Things.
Dr. Piyush Kumar Pareek, B.E, M.Tech, Ph.D, (PostDoc), MIE&SMIEE, is working as a Professor and Department Head at Nitte Meenakshi Institute of Technology, Bengaluru. He has an interest in continuous Learning and Teaching and completed his B.E, M.Tech., and Ph.D. in the field of Computer Science Engineering. Dr. Pareek has experienced close to a decade in teaching and has published 100 plus research articles and 10 plus textbooks. He has also 15 design patents granted along with 18 Australian Innovation patents and has filed and published 50 plus Indian Utility patents. Dr. Pareek is a reviewer in many international refereed journals of repute and serves as Assistant Director in Social Service Cell Bengaluru North.
Dr. Ahmed A. Elngar is an Associate Professor of Computer Science at the Faculty of Computers and Artificial Intelligence, Beni-Suef University, Egypt. Dr. Elngar is also, an Associate Professor of Computer Science at the College of Computer Information Technology, American University in the Emirates, United Arab Emirates. He is also Adjunct Professor the at School of Technology, Woxsen University, India, and the Founder and Head of the Scientific Innovation Research Group (SIRG). Dr. Elngar is a Director of the Technological and Informatics Studies Center (TISC) and Faculty of Computers and Artificial Intelligence, Beni-Suef University. Dr. Elngar has more than 106 scientific research papers published in prestigious international journals and over 25 books covering such diverse topics as data mining, intelligent systems, social networks, and smart environment. He is a collaborative researcher and a member of the Egyptian Mathematical Society (EMS) and the International Rough Set Society (IRSS). His other research areas include the Internet of Things (IoT), Network Security, Intrusion Detection, Machine Learning, Data Mining, and Artificial Intelligence, Big Data, Authentication, Cryptology, Healthcare Systems, and Automation Systems. He is an Editor and Reviewer of many international journals around the world and has won several awards including “Young Researcher in Computer Science Engineering”, from Global Outreach Education Summit and Awards 2019, on 31 January 2019 in Delhi, India. He also received the Best Young Researcher Award and the Global Education and Corporate Leadership Award (GECL-2018).
