Digital Convergence in Intelligent Mobility Systems

Preface xv 1 Arduino-Based Battery-Operated Multi-Purpose Portable Seed-Sowing Machine 1 K. Raju, M. Ajay Kumar and Canute Sherwin 1.1 Introduction 2 1.2 Background 4 1.3 Design Details of Seed-Sowing Machine 8 1.3.1 Selection of DC Motor 8 1.3.1.1 Rolling Resistance 8 1.3.1.2 Grade Resistance 9 1.3.1.3 Acceleration Force 9 1.3.1.4 Total Tractive Effort 9 1.3.1.5 Torque 10 1.3.1.6 Output Speed 10 1.3.1.7 Power 10 1.3.1.8 Battery Capacity Calculation 10 1.3.1.9 Run Time of the Battery 11 1.3.1.10 Battery Stand-By Time 11 1.4 Details of Components of Seed-Sowing Machine 11 1.4.1 Mechanical Components 11 1.4.1.1 Hopper 11 1.4.1.2 Wheel 12 1.4.1.3 Shaft and Bearing 12 1.4.1.4 Chain Drive and Sprocket Assembly 12 1.4.1.5 Tilling Tool 13 1.4.1.6 Trenching Tool 13 1.4.1.7 Leveling Tool 13 1.4.2 Electrical and Electronic Components 14 1.4.2.1 Battery 14 1.4.2.2 dc Motor 15 1.4.2.3 Servo Motor 15 1.4.2.4 Relay 16 1.4.2.5 Arduino 16 1.5 Methodology 16 1.5.1 Block Diagram of the Proposed Seed-Sowing Machine 16 1.5.2 CAD Modeling of Seed-Sowing Machine 17 1.5.3 The Working Principle of the Seed-Sowing Machine 17 1.6 Results and Discussion 19 1.7 Scope for Future Work 20 1.8 Conclusions 20 References 21 2 An Overview of Intelligent Mobility of Agricultural Drones 25 Prasad G., Sukumar Dhanapalan, Brandon Bernard Chiripanyanga, Trycene Tadiwanashe Tsabora and Felix Mwiya Introduction 26 Background of the Research 26 Technology in Agriculture 29 Using Unmanned Aerial Vehicles in Animal Farming 31 Design Flow Process 32 Management Team, GTM Strategy, and Competitive Landscape 33 Design Constraints 34 Conclusion 35 References 36 3 Simulation of Proportional-Integral and Derivative (PID) Based Traction and Speed Control System for a Four-Wheel Electric Vehicle Using MATLAB Simulink 39 Canute Sherwin, Christina Sundari, Aryan Bakle and Mahijit Dodiya 3.1 Introduction 40 3.2 Literature Review 41 3.3 Methodology 44 3.4 Results and Analysis 51 3.5 Conclusion 55 References 56 4 A Case Study on Electric Vehicles (EV) 59 Sumiksha Shetty, Smitha A. B., Manjunatha Badiger and Chandra Singh 4.1 Introduction 60 4.2 Literature Survey 61 4.3 Government Initiatives 63 4.3.1 Faster Adoption and Manufacturing of Hybrid and Electric Vehicles (FAME II) Scheme 63 4.3.2 National Electric Mobility Mission Plan (nemmp) 2020 63 4.3.3 Charging Infrastructure for Electric Vehicles— Guidelines and Standards of the Ministry of Power 64 4.3.4 State Government Initiatives 64 4.3.5 Public Sector Undertakings (PSUs) and Private Sector Collaboration 64 4.3.6 Smart Cities Mission 65 4.3.7 National Electric Mobility Infrastructure (NEMI) Guidelines 65 4.4 Challenges 66 4.4.1 Capital Intensive Investments 66 4.4.2 Power Supply and Grid Stability 66 4.4.3 The Issue of Uniformity in Charging Infrastructure 67 4.4.4 Space and Land Constraints 68 4.4.5 Legal and Bureaucratic Obstacles 68 4.4.6 Technology and Maintenance 69 4.4.7 Adoption Rate of EVs 70 4.4.8 Integration with Renewable Energy 70 4.5 Important Factors 71 4.6 Infrastructure 72 4.6.1 Charging Stations 72 4.6.2 Grid Upgrades 73 4.6.3 Battery Swapping Stations 74 4.6.4 Software Systems 74 4.7 Applications 75 4.8 Conclusion 76 References 76 5 Accelerating Connections with 5G and Evolution of Vehicle Communication Technology 79 Dankan Gowda V., Chippy T., V. Nuthan Prasad, Belsam Jeba Ananth M. and K.D.V. Prasad 5.1 Introduction 80 5.2 Historical Evolution of Vehicle Communication Technology 83 5.3 Foundations of 5G Technology 85 5.4 Integration of 5G in Vehicular Networks 87 5.5 Benefits of 5G in Automotive Communication 90 5.6 V2X Communication and 5G 92 5.7 Case Studies 93 5.8 Challenges and Future Directions 95 5.9 Conclusion 97 References 98 6 Predicting the Flow with Machine Learning Algorithms for Advanced Traffic Management 101 Dankan Gowda V., Rupali Suraskar, Ridhi Rani, K.D.V. Prasad and Ved Srinivas 6.1 Introduction 102 6.2 Fundamentals of Machine Learning in Traffic Management 105 6.3 Applications of ML in Traffic Prediction and Management 107 6.4 Case Studies 110 6.5 Challenges and Limitations 112 6.6 Future Trends and Innovations 115 6.7 Conclusion 118 References 120 7 Secure Routes and Cybersecurity Challenges in Autonomous Mobility Systems 125 Dankan Gowda V., Ribhu Abhusan P., V. Nuthan Prasad, K.D.V. Prasad and P. Vishnu Prasanth 7.1 Introduction 126 7.2 The Landscape of Autonomous Mobility 129 7.3 Cybersecurity Challenges 132 7.4 Secure Routes: Ensuring Safety in Navigation and Control 135 7.5 Defensive Technologies and Strategies 138 7.6 Regulatory and Standardization Efforts 141 7.7 Ethical and Privacy Considerations 144 7.8 Case Studies of Secure Autonomous Mobility Implementations 147 7.9 Future Directions and Research Opportunities 150 7.10 Conclusion 153 References 155 8 Green Routes Building the Backbone for Electric Vehicle Charging 159 Dankan Gowda V., Sadashiva V. Chakrasali, Ved Srinivas, K.D.V. Prasad and Saptarshi Mukherjee 8.1 Introduction 160 8.2 Current State of EV Charging Infrastructure 163 8.3 Technological Innovations in EV Charging 166 8.4 Designing Sustainable Charging Networks 169 8.5 Integration with Renewable Energy Sources 172 8.6 Economic and Business Models 176 8.7 Policy, Regulations, and Standards 178 8.8 Public Perception and Adoption 182 8.9 Future Directions and Innovations 185 8.10 Conclusion 187 References 189 9 Vehicular Power Line Communication 193 Smitha Gayathri D., K.R. Usha Rani and Yasha Jyothi Shirur 9.1 Introduction 194 9.2 Review and Categorization of Impedance Matching Techniques in Existing Literature 197 9.2.1 Impedance Matching: Concept and Classification 198 9.2.2 Related Works and Developments 199 9.3 Model of Vehicular Power Line Communication 200 9.3.1 The Resonance and Absorption Technique for Advanced Impedance Matching 201 9.3.1.1 Matching the Impedance to Access Inductive Impedance 201 9.3.1.2 System Structure 204 9.4 Simulation Results besides Analysis 208 9.5 Conclusion 213 References 213 10 Future Trends in V2X Communication and Interoperability 217 Dankan Gowda V., D. Palanikkumar, Satish Dekka, K.D.V. Prasad and Shivoham Singh 10.1 Introduction 218 10.2 Emerging Technologies in V2X Communication 221 10.3 Autonomous Vehicles and V2X Integration 223 10.4 Edge Intelligence and Decentralized Communication 226 10.5 Interoperability in a Multi-Vendor Ecosystem 229 10.6 Cybersecurity in Future V2X Systems 231 10.7 Environmental and Sustainability Considerations 232 10.8 User Experience and Human-Machine Interaction 234 10.9 Conclusion 236 References 237 11 Toward Smarter Streets: Leveraging Machine Learning, 5G, and V2X Communication for Traffic Insights 241 Smitha A. B., Manjunatha Badiger, Sumiksha Shetty, Chinmaya H., Sanketh C. Naik, Sujan R. Arasa, Ajay Deepak Lobo and Shreyas K. 11.1 Introduction 242 11.2 Literature Survey 242 11.3 5G Technology and Its Role in Transportation 249 11.4 Vehicular Communication and V2X Standards 250 11.4.1 Overview of Vehicular-to-Everything (V2X) Communication Technologies 250 11.4.2 V2X Communication Standards and Protocols 252 11.4.3 Importance of Interoperability for Seamless Communication between Vehicles and Infrastructure 254 11.5 Integration of Machine Learning with 5G and V2X Communication 255 11.5.1 Introduction to Machine Learning Algorithms Used in Traffic Prediction 255 11.5.2 Overview of Data Sources and Features Used for Training Traffic Prediction Models 256 11.5.3 Challenges and Opportunities in Integrating Machine Learning with 5G and V2X Communication 257 11.5.4 Potential Applications of Machine Learning in Optimizing Traffic Flow and Management 258 11.6 Dynamic Traffic Prediction and Management 259 11.6.1 Real-Time Data Utilization for Dynamic Traffic Prediction 259 11.6.2 Techniques for Route Optimization and Vehicle Rerouting 260 11.6.3 Machine Learning and V2X in Dynamic Traffic Signal Optimization 260 11.6.4 Benefits of Adaptive Traffic Signal Control in Improving Traffic Flow and Reducing Congestion 261 11.6.5 Safety Applications and Collision Avoidance Systems 261 11.7 Future Directions and Challenges 262 11.7.1 Emerging Trends and Future Directions in the Integration of Machine Learning, 5G, and V2X Communication 262 11.7.2 Addressing Challenges 263 11.7.3 Opportunities for Further Research and Development in the Field of Intelligent Transportation Systems 264 11.8 Conclusion 264 References 265 12 Empowering Healthcare through Mobility as a Service: A Comprehensive Review 271 Manjunatha Badiger, Thrisha B., Kshithij H. S., Sathwik M. S. and Rakshitha N. 12.1 Introduction 272 12.2 Mobility as a Service (MaaS) in Healthcare 274 12.2.1 Overview of Healthcare Access Challenges 274 12.2.2 Enhancing Medical Access with Mobility as a Service 275 12.3 Low-Cost Generic Medicine Dispensers 277 12.4 Regulatory and Infrastructure Considerations 279 12.4.1 Challenges and Solutions 279 12.4.2 Strategic Partnerships and Stakeholder Engagement 280 12.4.3 Funding and Sustainability Models 280 12.4.4 Technology Integration and Digital Connectivity 281 12.4.5 User Education, Community Engagement, and Security Measures 281 12.5 Assessing Impact: Benefits to Healthcare, Economy, and Society 282 12.5.1 Environmental Considerations 282 12.5.2 Improved Public Health Outcomes 283 12.5.3 Enhanced Data Analytics and Health Insights 283 12.6 Future Perspective Empowering Healthcare MAAS to Support Healthcare 284 12.6.1 Environmental Considerations 285 12.7 Cost Reduction and Efficiency in Healthcare Delivery 287 References 288 13 An Enhanced Sustainable Mobility as a Service Based on 5G Network for Human-Centric Mobile Network in Smart City 293 Senthil G. A., R. Prabha, D. Roopa and S. Sridevi 13.1 Introduction 294 13.1.1 Objective and Benefits 295 13.2 Proposed Enhanced MaaS Framework 297 13.2.1 System Architecture 297 13.2.2 Service Components 298 13.2.3 Human-Centric Design 300 13.2.4 Mobility Analysis 300 13.3 Sustainability Analysis 301 13.3.1 Environmental Impact 301 13.3.2 Social Impact 302 13.3.3 Economic Impact 303 13.4 Challenges and Solutions 304 13.4.1 Technological Challenges 304 13.4.2 Communication Network and Bandwidth 305 13.4.3 Enabling Critical Infrastructures 306 13.4.4 Social and Regulatory Challenges 307 13.4.5 Quality of Service 308 13.5 Conclusion 309 13.6 Future Work 310 References 311 14 Design and Development of Foldable Electric Vehicle 315 Akshay S. Bhat, Puneeth H. S., P. Aniketh Solanki, Karthik P., Prajwal K. Kalal and Manoj S. 14.1 Introduction 315 14.2 Problem Formulation 317 14.3 Methodology and Material 318 14.3.1 Material Selection Process 319 14.3.2 Working 320 14.3.3 Electrical Components 320 14.4 Static Analysis 327 14.5 Results 328 14.6 Conclusion 329 References 330 15 Design and Development of Ultrasonic Assisted Collision Detection and Blind-Spot Reduction 331 Puneeth H. S., Akshay S. Bhat, Bhavani A., Lalit V., Sathyarjun A. B. and Vishnu K. J. 15.1 Introduction 332 15.1.1 Head-Up Display 333 15.1.2 Elements That Control IC Engine Vehicles’ Speed 333 15.1.2.1 Electronic Control Unit 333 15.1.2.2 Sensors Operated by ECU 334 15.1.2.3 Air–Fuel Ratio 334 15.1.2.4 Air–Fuel Ratio and Engine Performance 335 15.1.2.5 Throttle Body 335 15.1.3 Components Associated with the Vehicle Speed in EVs 335 15.1.3.1 Throttle 336 15.1.3.2 Motor 336 15.1.3.3 Controller 336 15.2 Problem Formulation 337 15.2.1 Integration of Head-Up Display 337 15.2.2 Vehicle Speed Controller 337 15.3 Methodology 338 15.3.1 Components Used 338 15.3.2 Construction and Working 338 15.4 Scope of the Project 341 15.4.1 Implementation in IC Engines 341 15.4.2 Implementation in Electric Vehicle 342 15.4.3 Head-Up Display 343 15.5 Results and Discussions 343 15.5.1 Results 343 15.5.2 Discussions 343 15.6 Conclusion 344 References 345 16 Voting Classifier-Based Machine Learning Technique for the Prediction of the Traffic Flow for the Intelligent Transportation System 347 Sandeep Kumar Hegde, Rajalaxmi Hegde and Thangavel Murugan 16.1 Introduction 348 16.2 Literature Review 350 16.3 Methodology 353 16.4 Experimental Results 355 16.5 Conclusion 360 References 360 17 Influence of Feature Selection Techniques for Social Media Data Analysis (Text and Image) 363 Aruna Bajpai and Yogesh Kumar Gupta 17.1 Introduction 364 17.2 Literature Review 364 17.3 Proposed Work 369 17.3.1 Text Feature Analysis 369 17.3.2 Image Feature Analysis 370 17.4 Results Analysis 373 17.5 Conclusions 375 Bibliography 376 About the Editors 379 Index 381