In an era where industrial expertise meets digital innovation, the "smart factory" symbolizes a new wave of efficiency and advancement. Industry 5.0 represents a paradigm shift, integrating technologies like robotics, AI, IoT, and big data to enhance human-machine collaboration while improving sustainability, quality, and efficiency. It offers businesses valuable insights and real-world examples to navigate the opportunities and challenges of Industry 5.0.

This book goes beyond technical explanations to examine the broader impact of the Industry 5.0 revolution on global supply chains and socioeconomic change, encouraging readers to view technology as a force for good. It appeals to all levels of expertise, providing valuable insights for experienced professionals while serving as an introduction for newcomers. Above all, it invites readers to embrace the collaborative spirit and creativity of Industry 5.0, joining in the effort to build the smart factories that will drive the future of innovation.

Audience

Researchers, industry engineers, and technologists working in artificial intelligence and Industry 5.0 application areas such as healthcare, transportation, manufacturing, and more.

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Yes, you can access Smart Factories for Industry 5.0 Transformation by R. Nidhya,Manish Kumar,S. Karthik,Rishabh Anand,S. Balamurugan in PDF and/or ePUB format, as well as other popular books in Technology & Engineering & Industrial Engineering. We have over one million books available in our catalogue for you to explore.

Information

Publisher

Year

Print ISBN

eBook ISBN

Edition

Topic

Technology & Engineering

Subtopic

Industrial Engineering

Index

Technology & Engineering

Cover
Series Page
Title Page
Copyright Page
Contents
Preface
Chapter 1 Evolution of Industrial Revolution: Industry 5.0 and Beyond
Chapter 2 Personalized Healthcare Transformation via Novel Era of Artificial Intelligence-Based Heuristic Concept
Chapter 3 A Survey on Security in Data Transmission Using Wireless Communication Methods for IoT Edge Devices
Chapter 4 Innovative Application of Conditional Deep Convolutional Generative Adversarial Networks to Enhance Chronic Kidney Disease Diagnosis with Uneven Datasets
Chapter 5 A Comprehensive Hybrid Implicit and Explicit Item-Based Collaborative Filtering Approach with Bayesian Personalized Ranking for Enhancing Book Recommendations
Chapter 6 An Efficient Cluster-Based Deep Learning Model for Multi-Attack Classification in IDS Across Diverse Datasets
Chapter 7 Heart Failure Detection Through SMOTE for Augmentation and Machine Learning Approach for Classification
Chapter 8 Optimal Power Allocation in Cognitive Radio Networks Using Teaching-Learning-Based Optimization
Chapter 9 Using Historical Pattern Matching and Natural Language Processing in a Hybrid Approach for Stock Market
Chapter 10 An Intelligent Framework for IoT-Based Health Care Monitoring Using Fuzzy-Supported Machine Learning Algorithm
Chapter 11 Design Strategy for Narrowband Internet of Things with Its Scope and Challenges of Security Solutions
Chapter 12 Machine Learning in Healthcare: Unlocking Precision Diagnosis and Continuous Monitoring Through Voice Analysis
Chapter 13 Introduction of Advanced and Improved Transposition Algorithm
Chapter 14 Performance Evaluation of Children at Risk for Schizophrenia Using Ensemble Learning
Chapter 15 Advanced Aquaculture Management: A Smart System for Optimizing Oxygen Levels, Shrimp Health Monitoring
Chapter 16 Farming Revolution: Precision Agriculture and IoT for Sustainable Growth
Chapter 17 Comparative Analysis of the Identification and Categorization of the Malaria Parasite Employing Recent Amalgamated Machine Learning Methodologies
Index
Also of Interest
EULA

About this book

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Table of contents