Smart Factories for Industry 5.0 Transformation

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.

• Preface xi1 Evolution of Industrial Revolution: Industry 5.0 and Beyond 1S. Balamurugan and B. SuryaBrief History of Industrial Revolution 1Acknowledgement 4Bibliography and Further Reading 42 Personalized Healthcare Transformation via Novel Era of Artificial Intelligence-Based Heuristic Concept 5S. Pradeep, R. Sathish Kumar, M. Jagadesh and A. KarthikeyanNomenclature 62.1 Introduction 72.2 Literature Survey 92.3 Digitization, Data Sources, and AI in Healthcare 132.4 AI Mainstreaming in Healthcare 152.5 Current Status, Integration, and Obstacles to the Usage of Personalized Healthcare Transformation 172.6 Prerequisites for Radical Transformation in Healthcare 252.7 Personalized Healthcare Transformation Using MSOM-Based TOA 292.8 Results 342.9 Conclusion 41References 413 A Survey on Security in Data Transmission Using Wireless Communication Methods for IoT Edge Devices 45V. Maruthi Prasad and B. Bharathi3.1 Introduction 463.2 Literature Survey 473.3 Description of Data Protocols for IoT System 503.4 IoT Communication Parameters 593.5 Comparative of Communication Protocols for IoT Systems 643.6 Conclusion 67References 674 Innovative Application of Conditional Deep Convolutional Generative Adversarial Networks to Enhance Chronic Kidney Disease Diagnosis with Uneven Datasets 71Lakshmi Ramani Burra, Praveen Tumuluru, Janakiramaiah Bonam, S. Hrushikesava Raju, Sunanda Nalajala and Surya Prasada Rao Borra4.1 Introduction 724.2 Literature Survey 764.3 Methodology 784.3.1 Data Preprocessing 794.3.2 Conditional Deep Convolutional Generative Adversarial Network 794.3.3 Bidirectional Long-Term Memory (Bi-LSTM) Method 824.4 Result Analysis 834.5 Conclusion 85References 865 A Comprehensive Hybrid Implicit and Explicit Item-Based Collaborative Filtering Approach with Bayesian Personalized Ranking for Enhancing Book Recommendations 89Adidam Surekha, Radhika Gouni, Satya Keerthi Gorripati, Venubabu Rachapudi, S. Anjali Devi and Anupama Angadi5.1 Introduction 905.2 Related Work 925.3 Methodology 955.4 Experimental Results and Analysis 995.5 Conclusion 102References 1026 An Efficient Cluster-Based Deep Learning Model for Multi-Attack Classification in IDS Across Diverse Datasets 105Rajesh Bingu, G. Harsha Vardhan Reddy, U. Jyothi Naga Pavan, S. Sneha Sai Sri and N. V. Praveen Kumar6.1 Introduction 1066.2 Literature Survey 1076.3 Proposed Model Design 1106.4 Results and Discussion 1156.5 Conclusion 118References 1197 Heart Failure Detection Through SMOTE for Augmentation and Machine Learning Approach for Classification 123G. Kiran Kumar, Anila M., Naga Raju Hari Manikyam, Venkata Nagaraju Thatha, R. Vijaya Kumar Reddy and Krishna Reddy Papana7.1 Introduction 1247.2 Literature Survey 1257.3 Proposed Methodology 1267.4 Results and Discussion 1287.5 Conclusion 132References 1328 Optimal Power Allocation in Cognitive Radio Networks Using Teaching-Learning-Based Optimization 135N. Lakshman Pratap, N. Sunanda and V. Suryanarayana Reddy8.1 Introduction 1368.2 Teaching-Learning-Based Optimization 1378.2.1 Teacher Phase 1388.2.2 Learner Phase 1398.3 Proposed Power Allocation Algorithm 1408.4 Numerical Results 1438.5 Conclusion 145References 1459 Using Historical Pattern Matching and Natural Language Processing in a Hybrid Approach for Stock Market 147K. Sri Niharika, C.H. Srisai Naga Satya Mani Pavan, T. Baby Aparna, Dinesh Kumar Anguraj, S. Saathvik and Hari Kiran Vege9.1 Introduction 1489.1.1 Background 1489.1.2 Problem Description 1489.1.3 Purposes of the Research 1489.1.4 Objectives of the Research 1499.2 Literature Review 1499.2.1 Review Based on Reference Research Paper 1499.3 Methodology 1539.3.1 Overview of the Hybrid Method 1539.3.2 Sentiment Analysis 1549.3.3 News Classification Using NLP Techniques 1549.3.4 Algorithms for Historical Pattern Matching 1559.3.5 Integration 1569.4 Data Sources and Collection 1569.4.1 Sources of Financial News 1569.4.2 Market Data Historical Overview 1579.4.3 Cleaning and Pre-Processing Data 1579.5 Experimental Setup 1589.5.1 Datasets for Training and Testing 1589.5.2 Metrics for Evaluation 1589.5.3 Optimization and Tuning of Hyperparameters 1599.6 Discussion 1609.6.1 Comparison of Model Performance 1609.6.2 NLP and Pattern Matching’s Effectiveness 1609.6.3 Restrictions and Perspectives 1609.6.4 Consequences and Prospective Courses 1619.7 Results 1619.8 Conclusion 163References 16410 An Intelligent Framework for IoT-Based Health Care Monitoring Using Fuzzy-Supported Machine Learning Algorithm 167Mohanapriya M., Bharanidharan R., R. Santhosh and R. Reshma10.1 Introduction 16810.2 Literature Analysis 17010.3 Integrated IoT-Based Healthcare Decision Making Model Using Machine Learning (IHM-ML) 17210.4 Result and Discussion 18010.5 Conclusion and the Future Scope 184References 18411 Design Strategy for Narrowband Internet of Things with Its Scope and Challenges of Security Solutions 187R. Reshma, N. Mohanasundaram and R. Santhosh11.1 Prologue Study 18811.2 Fundamentals of NB-IoT Network Design 19011.3 Security Challenges and Vulnerabilities in NB-IoT Systems 21611.4 Scope of Machine Intelligence in NB-IoT Security 21811.5 Conclusion and the Future Scope 220References 22012 Machine Learning in Healthcare: Unlocking Precision Diagnosis and Continuous Monitoring Through Voice Analysis 229Smilarubavathy G., Keerthana S. M., Nidhya R., Thanga Priscilla and Pavithra D.12.1 Introduction 23012.2 Background 23212.3 Methodology 23212.4 Results 24212.5 Discussion 243Conclusion 243References 24413 Introduction of Advanced and Improved Transposition Algorithm 247Dipesh Kumar, Nirupama Mandal and Yugal Kumar13.1 Introduction 24813.2 Literature Study 24913.3 Implementation 25713.3.1 Algorithm for Encryption 25813.3.2 Algorithm for Decryption 26113.4 Result 26413.4.1 Experimental Setup 26413.4.2 Experiment Result 26513.4.2.1 Encryption Process 26513.4.2.2 Decryption Process 26513.5 Conclusion and Future Direction 266References 26614 Performance Evaluation of Children at Risk for Schizophrenia Using Ensemble Learning 269Rathiya R., Kalamani M., Narmadha R. P., Sreenivasa Perumal L. and Kalpana R.14.1 Introduction 27014.2 Literature Review 27114.3 Methodology 27414.4 Performance Analysis 27614.5 Result Analysis 27914.6 Conclusion 27914.7 Future Work 280References 28015 Advanced Aquaculture Management: A Smart System for Optimizing Oxygen Levels, Shrimp Health Monitoring 283Prathyusha Kuncha, J. Manoranjini, Sirisha J., Suneetha Bandeela, Naveen Kumar Penjarla and Simhadri Subhash Goud15.1 Introduction 28415.2 Literature Survey 28615.3 System Model 28815.4 Results and Discussion 29215.5 Conclusion 296References 29716 Farming Revolution: Precision Agriculture and IoT for Sustainable Growth 299Arepalli Gopi, Sudha L. R. and Iwin Thanakumar Joseph S.16.1 Introduction 30016.2 Data Storage and Analysis on Cloud Data 30416.3 Architecture IoT with Agriculture 30616.4 Results and Performance Validation 31116.5 Conclusion 317References 31817 Comparative Analysis of the Identification and Categorization of the Malaria Parasite Employing Recent Amalgamated Machine Learning Methodologies 321Tamal Kumar Kundu, Dinesh Kumar Anguraj, R. Nidhya and V. Maruthi PrasadIntroduction 322Dataset Acquisition 325Methodology 325Literature Survey 326Methodology 328Results and Discussion 328Conclusion 332References 334Index 337