AI-Driven IoT Systems for Industry 4.0 (inbunden)
Inbunden (Hardback)
Antal sidor
CRC Press
Jose, Deepa (ed.), Nanjundan, Preethi (ed.), Mohanty, Sachi Nanda (ed.), Paul, Sanchita (ed.)
28 Tables, black and white; 59 Line drawings, black and white; 47 Halftones, black and white; 106 Il
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AI-Driven IoT Systems for Industry 4.0

Inbunden,  Engelska, 2024-07-30
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The purpose of this book is to discuss the trends and key drivers of Internet of Things (IoT) and artificial intelligence (AI) for automation in Industry 4.0. IoT and AI are transforming the industry thus accelerating efficiency and forging a more reliable automated enterprise. AI-driven IoT systems for Industry 4.0 explore current research to be carried out in the cutting-edge areas of AI for advanced analytics, integration of industrial IoT (IIoT) solutions and Edge components, automation in cyber-physical systems, world leading Industry 4.0 frameworks and adaptive supply chains, etc. A thorough exploration of Industry 4.0 is provided, focusing on the challenges of digital transformation and automation. It covers digital connectivity, sensors, and the integration of intelligent thinking and data science. Emphasizing the significance of AI, the chapter delves into optimal decision-making in Industry 4.0. It extensively examines automation and hybrid edge computing architecture, highlighting their applications. The narrative then shifts to IIoT and edge AI, exploring their convergence and the use of edge AI for visual insights in smart factories. The book concludes by discussing the role of AI in constructing digital twins, speeding up product development lifecycles, and offering insights for decision-making in smart factories. Throughout, the emphasis remains on the transformative impact of deep learning and AI in automating and accelerating manufacturing processes within the context of Industry 4.0. This book is intended for undergraduates, postgraduates, academicians, researchers, and industry professionals in industrial and computer engineering.
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Dr. Deepa Jose works as Head of Department of Sponsored Research and Consultancy and Professor of ECE at KCG College of Technology, Chennai, India, and is an IEEE Senior Member and IEEE Women in Engineering Chair. She has done various outreach activities for women empowerment through IEEE WIE. She has completed Ph.D. in VLSI Design from College of Engineering Guindy, Anna University Chennai in the year 2015. She is a life time member of IEI and IET. She has more than 18 years of teaching experience. She has Guideship from Anna University and produced one Ph.D. student and currently guiding eight Ph.D. students. She has Indian Patent Granted, two FER completed and one International Patent Grant. She has published more than 60 research papers in Journals, International Conferences in India and abroad. She is a member of Technical Committees of conferences and journals. Her areas of research interest include VLSI for wireless communication, deep learning, biomedical signal processing, IoT for healthcare, GIS initiatives, soft computing, and AI. She is recipient of Best Academic Practitioner Award from IET Chennai and IEEE Award for Professional Achievement. Deepa Jose has conducted 3 International Conferences and more than 30 Fdps/workshops/webinars. She has won three Best Paper awards. She has won two Best Research Paper Awards in the Fifth International Congress and Expo on Biotechnology and Bioengineering held in the United Kingdom and at IEEE INDISCON 2023 conducted by IEEE India Council. Dr. Preethi Nanjundan is an Associate Professor (SRG) in the Department of Data Science at Christ University, Pune, Lavasa campus, Maharashtra, India. She received her Doctorate degree from Bharathiar University, Coimbatore, in 2014. She received her Master of Philosophy in computer science from Bharathiar University in 2007 and earned Masters degree in Computer Applications from Bharathidasan University in 2004. Her research and teaching experience spans 18 years. Besides publishing over 20 papers in international refereed journals, she has contributed chapters to various books and published 5 books. Four of her patents have also been granted. In 2020, she received the Best Professor award from Lead India and Vision Digital India. Her contributions to a book titled Covid 19 and its Impact have been inducted into the Indian and Asian books of records. Her research area includes machine learning, natural language processing, and neural network. She is a lifetime member of professional societies, including Computer Society of India (CSI), International Association of Computer Science and Information Technology (IACSIT), Computer Science Teachers Association, and Indian Society for Technical Education (ISTE). Dr. Sanchita Paul is presently working as Associate Professor in BIT Mesra, Ranchi, Jharkhand. She received her Ph.D. Degree from BIT Mesra, Ranchi, Jharkhand, in the year January 2012. She received her M. Tech Degree from BIT Mesra, Ranchi, Jharkhand, in the year 2006 and BE Degree from Burdwan University, West Bengal, in the year of 2004. Her research areas include artificial intelligence, cloud computing, Internet of Things, machine learning and deep learning. She has guided five Ph.D. Scholars. She has published 60 International Journals of International repute. She also has six patents in area of health informatics, IoT and Cloud Computing. She has acted as session chair and editorial member of many international journals and conferences. She has published one book on cloud computing in Scholars Press, Germany and five book chapters. She has completed two projects and one ISRO-funded project is ongoing. She is life member of CSI. She is principal investigator in setting of cloud computing lab at BIT Mesra, Ranchi. Dr. Sachi Nandan Mohanty received his PostDoc from IIT Kanpur in the year 2019 and Ph.D. from IIT Kharagpur, India, in the year 2015, with MHRD scholarship from Govt of India. He has authored/edited 28 books,


Chapter 1 A Novel Hybrid Approach Based on Attribute-Based Encryption for Secured Message Transmittal for Sustainably Smart Networks Chapter 2 Object Detection Using Deep Learning (DL) and OpenCV Approach Chapter 3 Enhancing Industrial Operations through AI-Driven Decision-Making in the Era of Industry 4.0 Chapter 4 Acne Detection Using Convolutional Neural Networks and Image-Processing Technique Chapter 5 Key Driving Technologies for Industry 4.0 Chapter 6 Opportunities and Challenges of Digital Connectivity for Industrial Internet of Things Chapter 7 Malicious QR Code Detection and Prevention Chapter 8 Integration of Advanced Technologies for Industry 4.0 Chapter 9 Challenges in Digital Transformation and Automation for Industry 4.0 Chapter 10 Design and Analysis of Embedded Sensors for IIoT: A Systematic Review Chapter 11 AI for Optimal Decision-Making in Industry 4.0 Chapter 12 Challenges in Lunar Crater Detection for TMC-2 Obtained DEM Image Using Ensemble Learning Techniques Chapter 13 A Framework of Intelligent Manufacturing Process by Integrating Various Function Chapter 14 Adaptive Supply Chain Integration in Smart Factories Chapter 15 Implementation of Intelligent CPS for Integrating the Industry and Manufacturing Process Chapter 16 Machine-Learning-Enabled Stress Detection in Indian Housewives Using Wearable Physiological Sensors Chapter 17 Rising of Dark Factories due to Artificial Intelligence Chapter 18 Deep Learning for Real-Time Data Analysis from Sensors Chapter 19 Blockchain as a Controller of Security in Cyber-Physical Systems: A Watchdog for Industry 4.0 Chapter 20 Energy Management in Industry 4.0 Using AI Chapter 21 Deployment of IoT with AI for Automation Chapter 22 A Comparison of the Performance of Different Machine Learning Algorithms for Detecting Face Masks