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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Yes, you can access AI-Driven IoT Systems for Industry 4.0 by Deepa Jose, Preethi Nanjundan, Sanchita Paul, Sachi Nandan Mohanty, Deepa Jose,Preethi Nanjundan,Sanchita Paul,Sachi Nanda Mohanty,Sachi Nandan Mohanty in PDF and/or ePUB format, as well as other popular books in Computer Science & Electrical Engineering & Telecommunications. We have over one million books available in our catalogue for you to explore.

Information

Publisher

Year

Print ISBN

eBook ISBN

Edition

Topic

Computer Science

Subtopic

Electrical Engineering & Telecommunications

Index

Computer Science

Cover Page
Half-Title Page
Series Page
Title Page
Copyright Page
Contents
About the Editors
List of Contributors
Preface
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
Index

About this book

Frequently asked questions

Information

Table of contents