Self-Powered Cyber Physical Systems

Rathishchandra R Gatti, PhD, is a professor and head of the Department of Mechanical Engineering and Robotics and Automation at the Sahyadri College of Engineering and Management, Mangalore, India. He holds four patents, has published over 40 peer-reviewed publications and is the editor of seven books and one journal. He has over 20 years of R&D experience in mechanical engineering and mechatronics. Chandra Singh, MTech, is an assistant professor in the Department of Electronics and Communication Engineering at the Sahyadri College of Engineering and Management, Mangalore, India and is pursuing his PhD. He holds four patents, has written over 25 peer-reviewed publications and is the editor of 7 books. Rajeev Agrawal, PhD, is an associate professor in the Department of Mechanical Engineering, at the Malaviya National Institute of Technology, Jaipur, India. He has more than 24 years of professional experience and serves on the editorial board of three international journals and has guest-edited over 10 journals and books. He has published over 100 research papers. Felcy Jyothi Serrao, PhD, is an associate professor in the Department of Physics at Sahyadri College of Engineering and Management, India. She has 19 years of teaching experience and 12 years of research experience in the field of semiconducting metal oxide nanofilms. She has published more than 18 research articles in peer-reviewed journals and conferences.

• Preface xixAcknowledgements xxiii1 Self-Powered Sensory Transducers: A Way Toward Green Internet of Things 1Rajeev Ranjan1.1 Introduction 11.2 Need of the Work 31.3 Energy Scavenging Schemes in WSAN 41.4 Self Powered Systems and Green IoT (G-IoT) 101.5 Application Area and Scope of Self-Powered System in G-IoT 111.6 Challenges and Future Scope of the Self-Powered G-IoT 221.7 Conclusion 272 Self-Powered Wireless Sensor Networks in Cyber Physical System 41Srividya P.2.1 Introduction 422.2 Wireless Sensor Networks in CPS 432.3 Architecture of WSNs with Energy Harvesting 442.4 Energy Harvesting for WSN 442.5 Energy Harvesting Due to Mechanical Vibrations 452.6 Piezoelectric Generators 462.7 Piezoelectric Materials 472.8 Types of Piezoelectric Structures 482.9 Hybridized Nanogenerators for Energy Harvesting 552.10 Conclusion 563 The Emergence of Cyber-Physical System in the Context of Self-Powered Soft Robotics 57Darwin S. and Fantin Irudaya Raj E.3.1 Introduction 583.2 Actuators and Its Types 593.3 Soft Actuator Electrodes 693.4 Sensors 723.5 Soft Robotic Structures and Control Methods 743.6 Soft Robot Applications 763.7 Future Scope 793.8 Conclusion 824 Dynamic Butterfly Optimization Algorithm-Based Task Scheduling for Minimizing Energy Consumption in Distributed Green Data Centers 91Sengathir Janakiraman and Deva Priya M.4.1 Introduction 924.2 Related Work 944.3 Improved Dynamic Butterfly Optimization Algorithm (IDBOA)-Based Task Scheduling (IDBOATS) 994.4 Results and Discussion 1064.5 Conclusion 1105 Wireless Power Transfer for IoT Applications--A Review 115Sasikala G. and Rajeev Ranjan5.1 Introduction 1165.2 Sensors 1165.3 Actuators 1185.4 Energy Requirement in Wireless Sensor Networks (WSNs) 1195.5 Wireless Sensor Network and Green IoT (G-IoT) 1215.6 Purpose of G-IoT 1225.7 Motivation 1245.8 Contribution 1245.9 Need of the Work 1255.10 Energy Transferring Schemes in WSAN 1265.11 Electromagnetic Induction 1275.12 Inductive Coupling 1315.13 Resonance Inductive Coupling 1325.14 Wireless Power Transmission Using Microwaves 1335.15 Electromagnetic Radiations 1355.16 Conclusion 1356 Adaptive Energy Intelligence Using AI/ML Techniques 141Gowthamani R., Sasi Kala Rani K., Manikandan M. and Rohini M.6.1 Introduction 1426.2 Evolution of Cyber Physical System 1446.3 Relationship With Internet of Things 1466.4 Challenges in Design and Integration of Cyber Physical Systems 1476.5 Future Challenges and Promises 1496.6 Machine Learning Models 1496.7 Estimation of Building Energy Consumption 1506.8 Development of Artificial Intelligence 1506.9 Usage of AI/ML in Adaptive Energy Management 1516.10 Use of Hybrid/Ensemble Machine Learning Algorithm for Better Prediction 1526.11 Conclusion 1557 Renewable Energy Smart Grids for Electric Vehicles 159Vishal H. Kanchan, Preethesh B., Hithesh Alen D'Costa, Sohan R. Alva and Rathishchandra Ramachandra Gatti7.1 Introduction 1607.2 Integration of Electric Vehicles (EVs) into the Power Grid 1617.3 EV Charging and Electric Grid Interaction 1617.4 EVs with V2G System Architecture 1637.5 EVs and Smart Grid Infrastructure 1647.6 Renewable Energy Sources Integration With EVs 1657.7 Application in Transport Sector 1677.8 Application in Micro-Grid 1697.9 State-of-the-Art Review 1707.10 Future Trends 1728 Recent Advances in Integrating Renewable Energy Micro-Grid Systems With Electric Vehicles 177Hithesh Alen D'Costa, Sohan R. Alva, Vishal H. Kanchan, Preethesh B. and Rathishchandra R. Gatti8.1 Introduction 1788.2 Electric Vehicles and Renewable Energy Sources: A General Overview 1798.3 Microgrid 1838.4 Interactions Between Cost-Conscious EVs and RESs 1868.5 Interaction Between Efficiency-Conscious EVs and RESs 1888.6 Open Problems 1908.7 Conclusion 1919 Overview of Fast Charging Technologies of Electric Vehicles 193Sohan R. Alva, Vishal H. Kanchan, Preethesh B., Hithesh Alen D'Costa and Rathishchandra Ramachandra Gatti9.1 Introduction 1949.2 Different Levels of Charging Electric Vehicles 1949.3 State-of-the-Art Fast-Charging Implementation 1979.4 DC Fast-Charging Structure 1999.5 Fast Chargers 2009.6 Today's Situation and Future Needs 2019.7 Fast-Charging Point Power Requirements 2029.8 Recent Technologies in Fast Charging, Machine Learning, and Artificial Intelligence 2039.9 Effect of Fast Charging on EV Powertrain Systems 2059.10 Grid Impacts Caused by EV Charging 2079.11 Fast-Charging Technologies on the Self-Powered Automotive Cyber-Physical Systems 2089.12 Conclusions 20910 A Survey of VANET Routing Attacks and Defense Mechanisms in Intelligent Transportation System 213Allam Balaram, P. Chandana, Shaik Abdul Nabi and M. SilpaRaj10.1 Introduction 21410.2 Attacks in VANET 21510.3 Impacts of Attacks on VANET Routing 21610.4 Nonintentional Misbehavior 21710.5 Intentional Misbehavior 21710.6 Defence Mechanism of Routing Attacks in VANET Routing 21810.7 Intrusion Detection Techniques in VANETs 22010.8 Anonymous Routing in VANETs 22110.9 Challenges and Future Directions 22210.10 Conclusion 22311 ANN-Based Cracking Model for Flexible Pavement in the Urban Roads 227Athiappan K., Kandasamy A., Karthik C. and Rajalakshmi M.11.1 Introduction 22811.2 Literature Review 22911.3 Methodology 23011.4 Structural Number 23411.5 Modeling Methodology 23511.6 Model Validation 23811.7 Sensitivity Analysis 23811.8 Conclusions 24111.9 Limitations 24111.10 Future Scope of Study 24112 A Review of Autonomous Vehicles 243Joyston J. D'Costa and Ajith B.S.12.1 Introduction 24412.2 History 24512.3 Degrees in Automation 24612.4 Benefits and Drawbacks 24712.5 Working Principle of Autonomous Vehicles 24912.6 Mechanics Involved 25012.7 Conclusion 25213 Meeting Privacy Concerns in Intelligent Transportation Systems 255Sharon D. John13.1 Introduction 25513.2 Synopsis of ITS 25713.3 Future Research Direction 26013.4 Contributions to this Research 26113.5 Conclusions 26214 Feasibility Study of Digital Twin in Automotive Industry--Trends and Challenges 265Preethesh B., Hithesh Alen D'Costa, Sohan R. Alva, Vishal H. Kanchan and Rathishchandra R. Gatti14.1 Introduction 26614.2 Industrial Evolution 26714.3 Influence of IoT on Digital Twin 26814.4 Digital Twin in CPS Applications 26914.5 Digital Twin Types 27014.6 Levels of Digital Twin 27114.7 Digital Thread 27214.8 State-of-the-Art Digital Twin Deployment 27314.9 Benefits of Digital Twin 27414.10 Digital Twin Life Cycle 27514.11 Digital Twin in Automotive Industry 27614.12 Applications of Digital Twinning Technology in the Automotive Industry 27714.13 Role of Digital Twins in Addressing Current Automotive Challenges 27914.14 Challenges for Implementing Digital Twin in Automotive Industry 28014.15 Bridging the Gap 28015 State-of-the-Art and Future Applications of Farming Robotics 283Badrinath A.R., Abhishek Kamath, Veerishetty Arun Kumar, Nishan Rai and Rathishchandra R. Gatti15.1 Introduction 28315.2 Components of Agricultural Robots 28515.3 Types of Agricultural Robots 28815.4 Implementation of Robotics in the Agricultural Process 29015.5 Challenges 29415.6 Conclusions 29516 Review on Robot Operating System 297G. Vijeth and Rathishchandra R. Gatti16.1 Introduction 29716.2 Nomenclature 30116.3 ROS Implementation 30316.4 Conclusion 30617 An Overview of Collaborative Robots and Their Applications 309Rao S. Krishna and Lawrence J. Fernandes17.1 Introduction 30917.2 Art of Study 31017.3 Implementation of Collaborative Robots 31417.4 Conclusion 31818 State-of-the-Art and Future Applications of Powered Exoskeleton 321C.P. Dheeshith, K. Abhijith, A. Shahaas, Rithin B. Nambiar and Rathishchandra R. Gatti18.1 Introduction 32118.2 Powered Exoskeleton 32318.3 State of the Art 32418.4 Design Parameters to be Considered 32518.5 Challenges to Tackle 32818.6 Applications of Powered Exoskeleton 32818.7 Conclusion 33019 An Overview of Recent Trends in Consumer Robotics 333Pramod Rao M., Shrihari P.C., Manoj, Shankar Gouda S. and Rathishchandra R. Gatti19.1 Introduction 33319.2 Entertainment Robot 33419.3 Educational Robot 33519.4 Social Robot 33619.5 Toy Robot 33719.6 Conclusion 33820 Soft Robotics in Waste Management 341S. Rithvik, Vijith Rai, Surya Dornal, Deepak J. and B.C. Pramod20.1 Introduction 34120.2 Soft Robotics Insights 34220.3 Soft Robots in Waste Management 34320.4 Are Soft Robots the First Step for a Sustainable Future? 34620.5 Conclusions 34721 State-of-the-Art Review of Robotics in Crop Agriculture 349A. Shahaas, Rithin, B. Nambiar, C.P. Dheeshith, K. Abhijith and Rathishchandra R. Gatti21.1 Introduction 34921.2 Scope 35021.3 Advantages 35121.4 Disadvantages 35221.5 Applications 35221.6 Automation in Agriculture 35421.7 Precision Agriculture 35621.8 Conclusion 357References 357Index 359