Adaptive Artificial Intelligence

Series Preface xxi Preface xxiii Acknowledgements xxvii Part 1: Adaptive Artificial Intelligence: Fundamentals 1 1 From Data to Diagnosis—Integrating Adaptive AI in Reshaping Healthcare 3 Kumar Saurabh and Raghuraj Singh Suryavanshi 1.1 Introduction 3 1.2 Literature Review 5 1.3 Benefits of Adaptive AI in Health Diagnostic 9 1.4 Challenges and Limitations of Adaptive AI in Health Diagnostic 11 1.5 Current Applications of Adaptive AI in Health Diagnostic 12 1.6 Future Prospects of Adaptive AI in Health Diagnostic 15 1.7 Conclusion 15 2 Transfer Learning in Adaptive AI 19 Pradumn Kumar and Praveen Kumar Shukla 2.1 Introduction: The Evolution of Adaptive Intelligence 20 2.2 Theoretical Foundations of Transfer Learning 21 2.3 Adaptive AI: Concepts and Challenges 28 2.4 Transfer Learning Techniques for Adaptive AI 38 2.5 Applications of Transfer Learning in Adaptive AI 40 2.6 Conclusion 42 3 Beyond Prediction: Adaptive AI as a Catalyst for Climate Change Mitigation and Understanding 45 Deepak Gupta and Satyasundara Mahapatra 3.1 Introduction 46 3.2 Foundations of Adaptive AI in Climate Science 48 3.3 Adaptive AI Frameworks for Climate Change Modeling 54 3.4 Real-World Applications of Adaptive AI in Climate Resilience 57 3.5 Challenges and Limitations in Adaptive AI for Climate Science 61 3.6 The Future of Adaptive AI in Climate Change Mitigation 65 3.7 Conclusion 68 4 Adaptive AI: Transforming Natural Language Processing and Industry Applications 73 Meena Kumari P., Ramakrishna Reddy K. and Manikandakumar M. 4.1 Introduction 74 4.2 Adaptive AI 78 4.3 Adaptive AI Use Cases with NLP 84 4.4 Adaptive AI Use Cases in Other Industry 90 4.5 Ethical Considerations and Challenges 96 4.6 Conclusion 97 5 Optimizing Networking Systems with Machine Learning Approach 101 Cherukuri Gaurav Sushant, Tanishq Kumar, Lakshmi Ajay Veeramraju, Yuvraj Singh and Sandeep Kumar Panda 5.1 Introduction 102 5.2 Networks 102 5.3 Computer Networks 102 5.4 Networking Software’s 103 5.5 Hardware Devices 105 5.6 Software-Defined Networks (SDN) 107 5.7 Machine Learning 108 5.8 Deep Learning 117 5.9 Applications of Machine Learning 121 5.10 Traditional Load Balancing Techniques 123 5.11 SDN Decision Making 124 5.12 Conclusion 126 Part 2: Adaptive Artificial Intelligence: Applications 135 6 Assessment of the Recurrent RBF Long-Range Forecasting Model for Estimating Net Asset Value 137 Minakhi Rout, Anjishnu Saw, Ajay Kumar Jena and Ajaya Kumar Parida 6.1 Introduction 137 6.2 Design of a Forecasting Model Using the Recurrent Radial Basis Function (RRBF) Neural Network 140 6.3 Extraction of Features and Construction of Input Data 143 6.4 Simulation Based Experiments 144 6.5 Conclusion 154 7 Reinforcement Learning in Network Optimization 157 M. Sandhya, L. Lakshmi and L. Anjaneyulu 7.1 Introduction 158 7.2 Related Works 160 7.3 Key Concepts of Network Optimization 161 7.4 Key Concepts of RL 163 7.5 Importance of RL in Network Optimization 175 7.6 Performance Evaluation and Benchmarking 179 7.7 Challenges and Future Directions in RL for Network Optimization 181 7.8 Conclusions 184 8 A Study on AI Adoption Methods in Industry 189 E. Sudarshan, K.S.R.K. Sarma and Karra Kishore 8.1 Types of Adaptive AI Techniques for Industrial Automation 190 8.2 Study: Predictive Maintenance in Industrial Automation 193 8.3 Study: Process Optimization in Industrial Automation 197 8.4 Study: Robotics and Autonomous Systems in Industrial Automation 201 8.5 Study: Quality Control and Inspection Systems in Industrial Automation 205 8.6 Study: Supply Chain Optimization in Industrial Automation 210 8.7 Study: Energy Management System (EMS) in Industrial Automation 215 8.8 Study: Human-Machine Collaboration System in Industrial Automation 220 8.9 Study: Fault Detection and Recovery System in Industrial Automation 224 8.10 Study: Intelligent Scheduling System in Industrial Automation 230 8.11 Study: Safety Systems in Industrial Automation 236 8.12 Study: Customisation and Flexibility in Industrial Automation 242 8.13 Study: Real-Time Monitoring and Analytics in Industrial Automation 249 9 Role of Artificial Intelligence for Real‑Time Systems and Smart Solutions 261 Gundala Jhansi Rani, Naresh Kumar Sripada, Sirikonda Shwetha and Erukala Sudarshan 9.1 Introduction 262 9.2 AI Techniques for Real-Time Systems 265 9.3 Applications of AI in Real-Time Systems 268 9.4 Challenges in AI for Real-Time Systems 278 9.5 Future Research Directions 278 9.6 Conclusion 279 10 Behavioral Analysis for Operational Efficiency in Coal Mines 285 Arunima Asthana and Tanmoy Kumar Banerjee 10.1 Introduction 285 10.2 Methodology 289 10.3 Rationale 292 10.4 Analysis and Future Research 301 10.5 Conclusion 302 Part 3: Adaptive Artificial Intelligence: Novel Practices 307 11 Society 5.0 – Study of Modern Smart Cities 309 Akash Raghuvanshi and Ravi Krishan Pandey 11.1 Introduction 310 11.2 Methods 317 11.3 What Exactly is the Smart City? 317 11.4 Energy Management System in Smart Cities 319 11.5 Citizen-Led Smart City to Society 5.0 322 11.6 Discussion: Risks and Challenges in Society 5.0 326 11.7 Conclusion 327 12 Artificial Intelligence Applications in Healthcare 329 Dileep Kumar Murala, Sandeep Kumar Panda, V.A. Sankar Ponnapalli and Pradosh Kumar Gantayat 12.1 Introduction 330 12.2 Literature Review 333 12.3 Role of AI in Healthcare 341 12.4 Examples and Applications of AI in Healthcare 346 12.5 Challenges, Advantages, & Feature Directions of AI in Healthcare 349 13 Cloud Manufacturing and Focus on Future Trends and Directions in Health Care Applications 359 Ravi Prasad Thati and Pranathi Kakaraparthi 13.1 Introduction 359 13.2 Challenges and Considerations in Cloud Manufacturing for Healthcare 364 13.3 Future Trends and Directions in Cloud Manufacturing for Healthcare 369 13.4 Conclusion 375 14 GAN Based Encryption to Secure Electronic Health Record 381 Alakananda Tripathy and Alok Ranjan Tripathy 14.1 Introduction 382 14.2 Background Study 383 14.3 Materials and Method 384 14.4 Result Analysis 389 14.5 Conclusion 393 15 Innovative AI-Driven Data Annotation Techniques 397 G. Viswanath, G. Kiran Kumar Reddy, K. Srinivasa Rao and C. Rambabu 15.1 Introduction 398 15.2 Machine Learning (ML): The Skeleton of AI-Driven Analytics 399 15.3 Knowledge-Based and Reasoning Methods 400 15.4 Decision-Making Algorithms 401 15.5 Search and Optimization Theory 401 15.6 Challenges in Text Annotation for Big Data 403 15.7 Related Work Comparison 404 15.8 Graph Descriptions 406 15.9 Conclusion 408 16 Empowering Sustainable Finance Through Education and Awareness: Fostering Responsible AI and Quantum Computing Usage for Enhanced ESG Analysis 411 Geetha N., Byreddy Sumanth Reddy, Valluri Hari Hara Teja, Keshav Khemka and U. M. Gopal Krishna 16.1 Introduction 412 16.2 Literature Review 416 16.3 Research Methodology 423 16.4 Interpretation and Analysis of Data 424 16.5 Conclusion 428 16.6 Limitation 428 16.7 Future Research 429 References 429 Index 433