Kolla Bhanu Prakash, PhD, is a professor and associate dean and R & D head for A.I. & Data Science Research Group at K L University, Vijayawada, Andhra Pradesh, India. He is also an adjunct professor atTaylors University, Malaysia. He has published 150+ research papers in international and national journals and conferences. He has authored two and edited 12 books as well as published 15 patents. His research interests include deep learning, data science, and quantum computing. Satish Kumar Peddapelli, PhD, is the Director at the Rajiv Gandhi University of Knowledge Technologies, IIIT-Basara, and Professor of Electrical Engineering, University College of Engineering, Osmania University, Hyderabad, India. His areas of interest are power electronics, drives, multi-level inverters, special machines and renewable energy systems. Ivan C.K. Tam, PhD, is an associate professor in the Dept. of Marine Engineering Design & Technology, as well as the Director of Innovation & Engagement at the University of Newcastle in Singapore. He has a wealth of experience in multi-disciplinary research and a strong track record of leading innovative projects. His research interests are in the clean fuel combustion process, exhaust emission control, energy management and renewable energy technology. Wai Lok Woo, PhD, received his doctorate in statistical machine learning from Newcastle University, UK. Prof Woo currently holds the Chair in Machine Learning with Northumbria University, UK. He is the Faculty Director of Research (Engineering and Environment), and Head of Research for Data Science and Artificial Intelligence. He was previously the Director of Research for Newcastle Research and Innovation Institute, and Director of Operations of Newcastle University. His major research is in mathematical theory and algorithms for data science and analytics. Vishal Jain, PhD, is an associate professor in the Department of Computer Science and Engineering, Sharda School of Engineering and Technology, Sharda University, Greater Noida, India. He has more than 16 years of experience in academics and has authored more than 100 research papers in reputed journals and conferences as well as edited several books with the Wiley-Scrivener imprint.

• Preface xxi1 AI in Mechatronics 1Vansh Gehlot and Prashant Singh Rana1.1 Introduction to AI Techniques for Mechatronics 21.2 Machine Learning for Mechatronic Systems 51.3 Computer Vision for Mechatronic Perception 91.4 Soft Computing Techniques 131.5 AI Planning and Decision-Making 161.6 Natural Language Interaction 191.7 AI in Mechatronic System Design 211.8 Challenges and Future Outlook 261.9 Artificial General Intelligence (AGI) 301.10 Conclusion 35References 382 Thermodynamics for Mechatronics 41Yadav Krishnakumar Rajnath, Shrikant Tiwari and Virendra Kumar2.1 Introduction 422.2 Defining Mechatronics and Its Interdisciplinary Nature 432.3 Fundamentals of Thermodynamics for Mechatronics 462.4 Enhancing Efficiency in Mechatronics Through Thermodynamics 522.5 Sustainability and Thermodynamics in Mechatronics 582.6 Innovative Applications and Future Trends 662.7 Educational and Professional Implications 72References 793 Role of Data Acquisition, Sensors, and Actuators in Mechatronics Industry 83Harpreet Kaur Channi3.1 Introduction 843.2 Literature Survey 863.3 Fundamentals of Data Acquisition 873.4 Coordination and Synchronization in Mechatronic Systems 943.5 Industrial Automation and Robotics 953.6 Technical Challenges in Integration and Compatibility 973.7 Future Trends and Implications 1003.8 Conclusion 102References 1034 Optimization Techniques for Mechatronics: A Comprehensive Review and Future Directions 109Ikvinderpal Singh and Sapandeep Kaur Dhillon4.1 Introduction 1104.2 Related Work 1114.3 Optimization in Mechatronics Design 1134.4 Optimization in Mechatronics Control 1164.5 Optimization in Mechatronics Manufacturing 1184.6 Multi-Objective Optimization in Mechatronics 1214.7 Real-Time Optimization for Mechatronics 1234.8 Challenges in Optimization for Mechatronics 1264.9 Opportunities in Optimization for Mechatronics 1274.10 Future Directions in Optimization for Mechatronics 1284.11 Conclusion 130References 1325 Reinforcement Learning for Adaptive Mechatronics Systems 135D. Sathya, G. Saravanan and R. Thangamani5.1 Introduction to Adaptive Mechatronics Systems 1365.2 Fundamentals of Reinforcement Learning 1395.3 Reinforcement Learning Algorithms for Mechatronics 1425.4 Adaptive Control Strategies in Mechatronics 1445.5 Autonomous Decision-Making in Mechatronics 1475.6 Optimization and Energy Efficiency in Mechatronics 1495.7 Safety and Robustness in Reinforcement Learning 1535.8 Real-World Applications and Case Studies 1555.9 Challenges and Future Directions 1745.10 Ethical and Societal Implications 1765.11 Conclusion 178References 179Further Reading 1816 Application of PLC in the Mechatronics Industry 185Harpreet Kaur Channi, Pulkit Kumar and Arvind Dhingra6.1 Introduction 1866.2 Role of PLC in Mechatronics System Integration 1916.3 PLC Applications in Mechatronics Industry 1956.4 PLC in Mechatronics System Design 1976.5 Safety in Mechatronics Systems 1996.6 Case Studies for Mechatronics Systems Using PLCs 2026.7 Challenges and Future Trends 2046.8 Conclusion 206References 2077 Fuzzy Logic and Its Applications in Mechatronic Control Systems 211D. Sathya, G. Saravanan and R. Thangamani7.1 Introduction 2127.2 Fuzzy Control Systems 2157.3 Fuzzy Logic Applications in Mechatronic Control Systems 2207.4 Fuzzy Expert Systems in Mechatronics 2217.5 Fuzzy Logic and Machine Learning in Mechatronics 2237.6 Fuzzy Control in Multivariable Mechatronic Systems 2277.7 Industrial Automation and Fuzzy Logic 2307.8 Challenges and Future Directions 2337.9 Conclusion 235References 236Further Reading 2378 Drones and Autonomous Robotics Incorporating Computational Intelligence 243R. Thangamani, R. K. Suguna and G. K. Kamalam8.1 Introduction 2448.2 Literature Review 2488.3 Navigation and Path Planning 2528.4 Perception and Object Detection 2588.5 Adaptive Control and Decision-Making 2658.6 Swarm Robotics and Multi-Agent Systems 2668.7 Autonomous Drone Delivery Systems 2708.8 Human–Robot Interaction and Collaboration 2778.9 Future Trends and Challenges 2848.10 Ethical Implications of Autonomous Robotics and Drones 2898.11 Conclusion 293References 2949 Exploring the Convergence of Artificial Intelligence and Mechatronics in Autonomous Driving 297Ritika Wason, Parul Arora, Vishal Jain, Devansh Arora and M. N. Hoda9.1 Introduction 2979.2 Key Components of Advanced Driver Systems 3019.3 Current State of AI-Enabled Self-Driving Mechatronics 3039.4 Challenges in Self-Driving Mechatronics 3059.5 Advantages of Self-Driving Mechatronics 3079.6 Self-Driving and Environmental Sustainability 3089.7 Legal and Safety Issues in Autonomous Driving 3109.8 Conclusion 3109.9 Future Directions in Self-Driving Mechatronics 313References 31310 Improving Power Quality for Industry Control Using Mechatronics Devices 317Pulkit Kumar, Harpreet Kaur Channi and Surbhi Gupta10.1 Introduction 31810.2 Power Quality in Industrial Settings 32210.3 Mechatronics Devices for Power Quality Improvement 32410.4 Case Studies of Mechatronics Devices in Industry Control 33010.5 Integration of Mechatronics Devices in Industrial Control Systems 33310.6 Future Trends and Innovations in Mechatronics for Power Quality Improvement 33710.7 Conclusion 342References 34211 Study on Integrated Neural Networks and Fuzzy Logic Control for Autonomous Electric Vehicles 347S. Boopathi11.1 Introduction 34811.2 Fundamentals of Neural Networks and Fuzzy Logic 35111.3 Autonomous Electric Vehicles: Challenges and Control Requirements 35411.4 Neural Network–Based Control for Autonomous Electric Vehicles 35711.5 Fuzzy Logic Control for Energy-Efficient Driving 36111.6 Integration of Neural Networks and Fuzzy Logic for Enhanced Autonomy 36711.7 Case Studies and Applications 37211.8 Future Prospects and Challenges 37411.9 Conclusions 375List of Abbreviations 375References 37512 Advancing Mechatronics Through Artificial Intelligence 381Pawan Whig, Jhansi Bharathi Madavarapu, Venugopal Reddy Modhugu, Balaram Yadav Kasula and Ashima Bhatnagar Bhatia12.1 Introduction 38112.2 Foundations of Mechatronics and Artificial Intelligence 38612.3 Synergies Between Artificial Intelligence and Mechatronics 38812.4 Case Studies: AI-Driven Advances in Mechatronics 39012.5 Challenges and Opportunities 39212.6 Future Directions and Trends 39512.7 Conclusion 39712.8 Future Scope 398References 39813 Computational Intelligent Techniques in Mechatronics: Emerging Trends and Case Studies 401Anita Mohanty, Ambarish G. Mohapatra, Subrat Kumar Mohanty, Bright Keswani and Sasmita Nayak13.1 Introduction to Mechatronics and Computational Intelligence 40213.2 Artificial Neural Networks (ANNs) in Mechatronics 40313.3 Reinforcement Learning in Mechatronics 40713.4 Evolutionary Algorithms for Mechatronic System Design 41213.5 Emerging Trends in Mechatronics with Computational Intelligence 41913.6 Real-World Case Studies 42713.7 Conclusion 439References 44114 Advanced Sensing Systems in Automobiles: Computational Intelligence Approach 445Mamta B. Savadatti and Ajay Sudhir Bale14.1 Introduction 44514.2 Computational Intelligence Approach 44714.3 Methodology 46314.4 Conclusions 466References 46715 Design of Arduino UNO–Based Novel Multi-Featured Robot 471Jaspinder Kaur, Rohit Anand, Nidhi Sindhwani, Ajay Kumar Sharma and Vishal Jain15.1 Introduction 47215.2 Design Implementation 47315.3 Proposed Model 47715.4 Process and Working Methodology 47815.5 Experiment and Applications 48215.6 Conclusion 48415.7 Future Scope 485Acknowledgments 485References 48516 Integrating Mechatronics in Autonomous Agricultural Machinery: A Case Study 491N. V. Suresh, Ananth Selvakumar, Gajalakshmi Sridhar and Vishal Jain16.1 Introduction 49216.2 Case Background 49316.3 Literature Review 49516.4 Methodology 49616.5 Implementation 49816.6 Findings 50116.7 Suggestion 50216.8 Conclusion 504References 505Index 509