Overview

This book serves as a comprehensive guide, exploring the technologies, design principles, and operational strategies behind smart factories. 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.

Full Product Details

Author:   R. Nidhya (Madanapalle Institute of Technology & Science, Madanapalle, India) ,  Manish Kumar (Thapar Institute of Engineering and Technology, Patiala, India) ,  S. Karthik (SNS College of Technology, Coimbatore, India) ,  Rishabh Anand (Global Institute of Technology & Management, Gurugram, India)
Publisher:   John Wiley & Sons Inc
Imprint:   Wiley-Scrivener
Weight:   0.680kg
ISBN:  

9781394199952

ISBN 10:   1394199953
Pages:   368
Publication Date:   07 February 2025
Audience:   Professional and scholarly ,  Professional & Vocational
Format:   Hardback
Publisher's Status:   Active
Availability:   Out of stock  
The supplier is temporarily out of stock of this item. It will be ordered for you on backorder and shipped when it becomes available.

Table of Contents

Preface xi 1 Evolution of Industrial Revolution: Industry 5.0 and Beyond 1 S. Balamurugan and B. Surya 1.1 Brief History of Industrial Revolution 1 1.2 Acknowledgement 4 1.3 Bibliography and Further Reading 4 2 Personalized Healthcare Transformation via Novel Era of Artificial Intelligence-Based Heuristic Concept 5 S. Pradeep, R. Sathish Kumar, M. Jagadesh and A. Karthikeyan 2.1 Introduction 7 2.2 Literature Survey 9 2.3 Digitization, Data Sources, and AI in Healthcare 13 2.4 AI Mainstreaming in Healthcare 15 2.5 Current Status, Integration, and Obstacles to the Usage of Personalized Healthcare Transformation 17 2.6 Prerequisites for Radical Transformation in Healthcare 25 2.7 Personalized Healthcare Transformation Using MSOM-Based TOA 29 2.8 Results 34 2.9 Conclusion 41 3 A Survey on Security in Data Transmission Using Wireless Communication Methods for IoT Edge Devices 45 V. Maruthi Prasad and B. Bharathi 3.1 Introduction 46 3.2 Literature Survey 47 3.3 Description of Data Protocols for IoT System 50 3.4 IoT Communication Parameters 59 3.5 Comparative of Communication Protocols for IoT Systems 64 3.6 Conclusion 67 4 Innovative Application of Conditional Deep Convolutional Generative Adversarial Networks to Enhance Chronic Kidney Disease Diagnosis with Uneven Datasets 71 Lakshmi Ramani Burra, Praveen Tumuluru, Janakiramaiah Bonam, S. Hrushikesava Raju, Sunanda Nalajala and Surya Prasada Rao Borra 4.1 Introduction 72 4.2 Literature Survey 76 4.3 Methodology 78 4.4 Result Analysis 83 4.5 Conclusion 85 5 A Comprehensive Hybrid Implicit and Explicit Item-Based Collaborative Filtering Approach with Bayesian Personalized Ranking for Enhancing Book Recommendations 89 Adidam Surekha, Radhika Gouni, Satya Keerthi Gorripati, Venubabu Rachapudi, S. Anjali Devi and Anupama Angadi 5.1 Introduction 90 5.2 Related Work 92 5.3 Methodology 95 5.4 Experimental Results and Analysis 99 5.5 Conclusion 102 6 An Efficient Cluster-Based Deep Learning Model for Multi-Attack Classification in IDS Across Diverse Datasets 105 Rajesh Bingu, G. Harsha Vardhan Reddy, U. Jyothi Naga Pavan, S. Sneha Sai Sri and N. V. Praveen Kumar 6.1 Introduction 106 6.2 Literature Survey 107 6.3 Proposed Model Design 110 6.4 Results and Discussion 115 6.5 Conclusion 118 7 Heart Failure Detection Through SMOTE for Augmentation and Machine Learning Approach for Classification 123 G. Kiran Kumar, Anila M., Naga Raju Hari Manikyam, Venkata Nagaraju Thatha, R. Vijaya Kumar Reddy and Krishna Reddy Papana 7.1 Introduction 124 7.2 Literature Survey 125 7.3 Proposed Methodology 126 7.4 Results and Discussion 128 7.5 Conclusion 132 8 Optimal Power Allocation in Cognitive Radio Networks Using Teaching-Learning-Based Optimization 135 N. Lakshman Pratap, N. Sunanda and V. Suryanarayana Reddy 8.1 Introduction 136 8.2 Teaching-Learning-Based Optimization 137 8.3 Proposed Power Allocation Algorithm 140 8.4 Numerical Results 143 8.5 Conclusion 145 9 Using Historical Pattern Matching and Natural Language Processing in a Hybrid Approach for Stock Market 147 K. Sri Niharika, C.H. Srisai Naga Satya Mani Pavan, T. Baby Aparna, Dinesh Kumar Anguraj, S. Saathvik and Hari Kiran Vege 9.1 Introduction 148 9.2 Literature Review 149 9.3 Methodology 153 9.4 Data Sources and Collection 156 9.5 Experimental Setup 158 9.6 Discussion 160 9.7 Results 161 9.8 Conclusion 163 10 An Intelligent Framework for IoT-Based Health Care Monitoring Using Fuzzy-Supported Machine Learning Algorithm 167 Mohanapriya M., Bharanidharan R., R. Santhosh and R. Reshma 10.1 Introduction 168 10.2 Literature Analysis 170 10.3 Integrated IoT-Based Healthcare Decision Making Model Using Machine Learning (IHM-ML) 172 10.4 Result and Discussion 180 10.5 Conclusion and the Future Scope 184 11 Design Strategy for Narrowband Internet of Things with Its Scope and Challenges of Security Solutions 187 R. Reshma, N. Mohanasundaram and R. Santhosh 11.1 Prologue Study 188 11.2 Fundamentals of NB-IoT Network Design 190 11.3 Security Challenges and Vulnerabilities in NB-IoT Systems 216 11.4 Scope of Machine Intelligence in NB-IoT Security 218 11.5 Conclusion and the Future Scope 220 12 Machine Learning in Healthcare: Unlocking Precision Diagnosis and Continuous Monitoring Through Voice Analysis 229 Smilarubavathy G., Keerthana S. M., Nidhya R., Thanga Priscilla and Pavithra D. 12.1 Introduction 230 12.2 Background 232 12.3 Methodology 232 12.4 Results 242 12.5 Discussion 243 13 Introduction of Advanced and Improved Transposition Algorithm 247 Dipesh Kumar, Nirupama Mandal and Yugal Kumar 13.1 Introduction 248 13.2 Literature Study 249 13.3 Implementation 257 13.4 Result 264 13.5 Conclusion and Future Direction 266 14 Performance Evaluation of Children at Risk for Schizophrenia Using Ensemble Learning 269 Rathiya R., Kalamani M., Narmadha R. P., Sreenivasa Perumal L. and Kalpana R. 14.1 Introduction 270 14.2 Literature Review 271 14.3 Methodology 274 14.4 Performance Analysis 276 14.5 Result Analysis 279 14.6 Conclusion 279 14.7 Future Work 280 15 Advanced Aquaculture Management: A Smart System for Optimizing Oxygen Levels, Shrimp Health Monitoring 283 Prathyusha Kuncha, J. Manoranjini, Sirisha J., Suneetha Bandeela, Naveen Kumar Penjarla and Simhadri Subhash Goud 15.1 Introduction 284 15.2 Literature Survey 286 15.3 System Model 288 15.4 Results and Discussion 292 15.5 Conclusion 296 16 Farming Revolution: Precision Agriculture and IoT for Sustainable Growth 299 Arepalli Gopi, Sudha L. R. and Iwin Thanakumar Joseph S. 16.1 Introduction 300 16.2 Data Storage and Analysis on Cloud Data 304 16.3 Architecture IoT with Agriculture 306 16.4 Results and Performance Validation 311 16.5 Conclusion 317 17 Comparative Analysis of the Identification and Categorization of the Malaria Parasite Employing Recent Amalgamated Machine Learning Methodologies 321 Tamal Kumar Kundu, Dinesh Kumar Anguraj, R. Nidhya and V. Maruthi Prasad Introduction 322 17. Dataset Acquisition 325 17.2 Methodology 325 17.3 Literature Survey 326 17.4 Methodology 328 17.5 Results and Discussion 328 17.6 Conclusion 332 References 334 Index 337

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Author Information

R. Nidhya, PhD, is an assistant professor in the Department of Computer Science & Engineering at the Madanapalle Institute of Technology & Science, affiliated with Jawaharlal Nehru Technical University, Anantapuram, India. Her research interests include wireless body area networks, machine learning, and IoT. Manish Kumar, PhD, is an assistant professor in the Department of Computer Science & Engineering at the Thapar Institute of Engineering and Technology, Patiala, Punjab, India. His research interests include soft computing applications for bioinformatics problems and computational intelligence. S. Karthik, PhD, is a professor and dean in the Department of Computer Science & Engineering at SNS College of Technology, Coimbatore, Tamil Nadu, India. His research interests include network security, web services, and wireless systems. Rishabh Anand, PhD, is a Global Service Delivery Manager with HCL Technologies Ltd. He earned his MBA in 2020 and is a certified DevOps project manager. S. Balamurugan, PhD, is the Director of Research and Development, Intelligent Research Consultancy Services (iRCS), Coimbatore, Tamilnadu, India. He is also Director of the Albert Einstein Engineering and Research Labs (AEER Labs), as well as Vice-Chairman, Renewable Energy Society of India (RESI), India. He has published 50+ books, 200+ international journals/conferences, and 35 patents.

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