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Submit a ProposalDigital Convergence in Intelligent Mobility Systems
 | Edited by Rathishchandra R. Gatti & Chandra Singh Copyright: 2025 | Expected Pub Date:2025// ISBN: 9781394275243 | Hardcover | 404 pages Price: $225 USD  |
One Line Description
Digital Convergence in Intelligent Mobility Systems gives a comprehensive understanding of how digital technologies are revolutionizing transportation, equipping you with the insights needed to navigate the future of intelligent mobility systems.
Audience
Researchers, academics, students, faculty, and industry professionals in the fields of transportation engineering, computer science, and electrical engineering
Researchers, academics, students, faculty, and industry professionals in the fields of transportation engineering, computer science, and electrical engineering
Description
The rapid evolution of digital technologies has transformed the landscape of intelligent mobility systems, ushering in a new era of innovation and convergence. The integration of digital technologies into various aspects of mobility systems, such as autonomous vehicles, smart transportation networks, and advanced traffic management systems, has the potential to revolutionize how we move people and goods.
Digital Convergence in Intelligent Mobility Systems is a comprehensive guide that explores the intersection of digital convergence and intelligent mobility systems. This book aims to provide an in-depth understanding of the state-of-the-art technologies, methodologies, and applications that are reshaping the future of transportation. It will serve as a valuable resource for researchers, engineers, policymakers, and students interested in the field of intelligent mobility.
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The rapid evolution of digital technologies has transformed the landscape of intelligent mobility systems, ushering in a new era of innovation and convergence. The integration of digital technologies into various aspects of mobility systems, such as autonomous vehicles, smart transportation networks, and advanced traffic management systems, has the potential to revolutionize how we move people and goods.
Digital Convergence in Intelligent Mobility Systems is a comprehensive guide that explores the intersection of digital convergence and intelligent mobility systems. This book aims to provide an in-depth understanding of the state-of-the-art technologies, methodologies, and applications that are reshaping the future of transportation. It will serve as a valuable resource for researchers, engineers, policymakers, and students interested in the field of intelligent mobility.
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Author / Editor Details
Rathishchandra R. Gatti, PhD is a professor and Head of the Department of Mechanical and Robotics Engineering at Sahyadri College of Engineering and Management with over 23 years of experience. He has published over seven books, 30 papers in international journals, and 15 patents. His research interests include AI in engineering, machine data analytics, and robotics.
Rathishchandra R. Gatti, PhD is a professor and Head of the Department of Mechanical and Robotics Engineering at Sahyadri College of Engineering and Management with over 23 years of experience. He has published over seven books, 30 papers in international journals, and 15 patents. His research interests include AI in engineering, machine data analytics, and robotics.
Chandra Singh is an assistant professor in the Department of Electronics and Communications Engineering at the Nitte Mahalinga Adyantaya Memorial Institute of Technology. He has published over eight books, 30 papers in international journals, and five patents. His research interests include optical and wireless communication, machine learning, and cyber physical systems.
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Table of Contents
Preface
1. Arduino-Based Battery-Operated Multi-Purpose Portable Seed-Sowing Machine
K. Raju, M. Ajay Kumar and Canute Sherwin
1.1 Introduction
1.2 Background
1.3 Design Details of Seed-Sowing Machine
1.3.1 Selection of DC Motor
1.3.1.1 Rolling Resistance
1.3.1.2 Grade Resistance
1.3.1.3 Acceleration Force
1.3.1.4 Total Tractive Effort
1.3.1.5 Torque
1.3.1.6 Output Speed
1.3.1.7 Power
1.3.1.8 Battery Capacity Calculation
1.3.1.9 Run Time of the Battery
1.3.1.10 Battery Stand-By Time
1.4 Details of Components of Seed-Sowing Machine
1.4.1 Mechanical Components
1.4.1.1 Hopper
1.4.1.2 Wheel
1.4.1.3 Shaft and Bearing
1.4.1.4 Chain Drive and Sprocket Assembly
1.4.1.5 Tilling Tool
1.4.1.6 Trenching Tool
1.4.1.7 Leveling Tool
1.4.2 Electrical and Electronic Components
1.4.2.1 Battery
1.4.2.2 DC Motor
1.4.2.3 Servo Motor
1.4.2.4 Relay
1.4.2.5 Arduino
1.5 Methodology
1.5.1 Block Diagram of the Proposed Seed-Sowing Machine
1.5.2 CAD Modeling of Seed-Sowing Machine
1.5.3 The Working Principle of the Seed-Sowing Machine
1.6 Results and Discussion
1.7 Scope for Future Work
1.8 Conclusions
References
2. An Overview of Intelligent Mobility of Agricultural Drones
Prasad G., Sukumar Dhanapalan, Brandon Bernard Chiripanyanga, Trycene Tadiwanashe Tsabora and Felix Mwiya
Introduction
Background of the Research
Technology in Agriculture
Using Unmanned Aerial Vehicles in Animal Farming
Design Flow Process
Management Team, GTM Strategy, and Competitive Landscape
Design Constraints
Conclusion
References
3. Simulation of Proportional-Integral and Derivative (PID) Based Traction and Speed Control System for a Four-Wheel Electric Vehicle Using MATLAB Simulink
Canute Sherwin, Christina Sundari, Aryan Bakle and Mahijit Dodiya
3.1 Introduction
3.2 Literature Review
3.3 Methodology
3.4 Results and Analysis
3.5 Conclusion
References
4. A Case Study on Electric Vehicles (EV)
Sumiksha Shetty, Smitha A. B., Manjunatha Badiger and Chandra Singh
4.1 Introduction
4.2 Literature Survey
4.3 Government Initiatives
4.3.1 Faster Adoption and Manufacturing of Hybrid and Electric Vehicles (FAME II) Scheme
4.3.2 National Electric Mobility Mission Plan (NEMMP) 2020
4.3.3 Charging Infrastructure for Electric Vehicles—Guidelines and Standards of the Ministry of Power
4.3.4 State Government Initiatives
4.3.5 Public Sector Undertakings (PSUs) and Private Sector Collaboration
4.3.6 Smart Cities Mission
4.3.7 National Electric Mobility Infrastructure (NEMI) Guidelines
4.4 Challenges
4.4.1 Capital Intensive Investments
4.4.2 Power Supply and Grid Stability
4.4.3 The Issue of Uniformity in Charging Infrastructure
4.4.4 Space and Land Constraints
4.4.5 Legal and Bureaucratic Obstacles
4.4.6 Technology and Maintenance
4.4.7 Adoption Rate of EVs
4.4.8 Integration with Renewable Energy
4.5 Important Factors
4.6 Infrastructure
4.6.1 Charging Stations
4.6.2 Grid Upgrades
4.6.3 Battery Swapping Stations
4.6.4 Software Systems
4.7 Applications
4.8 Conclusion
References
5. Accelerating Connections with 5G and Evolution of Vehicle Communication Technology
Dankan Gowda V., Chippy T., V. Nuthan Prasad, Belsam Jeba Ananth M. and K.D.V. Prasad
5.1 Introduction
5.2 Historical Evolution of Vehicle Communication Technology
5.3 Foundations of 5G Technology
5.4 Integration of 5G in Vehicular Networks
5.5 Benefits of 5G in Automotive Communication
5.6 V2X Communication and 5G
5.7 Case Studies
5.8 Challenges and Future Directions
5.9 Conclusion
References
6. Predicting the Flow with Machine Learning Algorithms for Advanced Traffic Management
Dankan Gowda V., Rupali Suraskar, Ridhi Rani, K.D.V. Prasad and Ved Srinivas
6.1 Introduction
6.2 Fundamentals of Machine Learning in Traffic Management
6.3 Applications of ML in Traffic Prediction and Management
6.4 Case Studies
6.5 Challenges and Limitations
6.6 Future Trends and Innovations
6.7 Conclusion
References
7. Secure Routes and Cybersecurity Challenges in Autonomous Mobility Systems
Dankan Gowda V., Ribhu Abhusan P., V. Nuthan Prasad, K.D.V. Prasad and P. Vishnu Prasanth
7.1 Introduction
7.2 The Landscape of Autonomous Mobility
7.3 Cybersecurity Challenges
7.4 Secure Routes: Ensuring Safety in Navigation and Control
7.5 Defensive Technologies and Strategies
7.6 Regulatory and Standardization Efforts
7.7 Ethical and Privacy Considerations
7.8 Case Studies of Secure Autonomous Mobility Implementations
7.9 Future Directions and Research Opportunities
7.10 Conclusion
References
8. Green Routes Building the Backbone for Electric Vehicle Charging
Dankan Gowda V., Sadashiva V. Chakrasali, Ved Srinivas, K.D.V. Prasad and Saptarshi Mukherjee
8.1 Introduction
8.2 Current State of EV Charging Infrastructure
8.3 Technological Innovations in EV Charging
8.4 Designing Sustainable Charging Networks
8.5 Integration with Renewable Energy Sources
8.6 Economic and Business Models
8.7 Policy, Regulations, and Standards
8.8 Public Perception and Adoption
8.9 Future Directions and Innovations
8.10 Conclusion
References
9. Vehicular Power Line Communication
Smitha Gayathri D., K.R. Usha Rani and Yasha Jyothi Shirur
9.1 Introduction
9.2 Review and Categorization of Impedance Matching Techniques in Existing Literature
9.2.1 Impedance Matching: Concept and Classification
9.2.2 Related Works and Developments
9.3 Model of Vehicular Power Line Communication
9.3.1 The Resonance and Absorption Technique for Advanced Impedance Matching
9.3.1.1 Matching the Impedance to Access Inductive Impedance
9.3.1.2 System Structure
9.4 Simulation Results besides Analysis
9.5 Conclusion
References
10. Future Trends in V2X Communication and Interoperability
Dankan Gowda V., D. Palanikkumar, Satish Dekka, K.D.V. Prasad and Shivoham Singh
10.1 Introduction
10.2 Emerging Technologies in V2X Communication
10.3 Autonomous Vehicles and V2X Integration
10.4 Edge Intelligence and Decentralized Communication
10.5 Interoperability in a Multi-Vendor Ecosystem
10.6 Cybersecurity in Future V2X Systems
10.7 Environmental and Sustainability Considerations
10.8 User Experience and Human-Machine Interaction
10.9 Conclusion
References
11. Toward Smarter Streets: Leveraging Machine Learning, 5G, and V2X Communication for Traffic Insights
Smitha A. B., Manjunatha Badiger, Sumiksha Shetty, Chinmaya H., Sanketh C. Naik, Sujan R. Arasa, Ajay Deepak Lobo and Shreyas K.
11.1 Introduction
11.2 Literature Survey
11.3 5G Technology and Its Role in Transportation
11.4 Vehicular Communication and V2X Standards
11.4.1 Overview of Vehicular-to-Everything (V2X) Communication Technologies
11.4.2 V2X Communication Standards and Protocols
11.4.3 Importance of Interoperability for Seamless Communication between Vehicles and Infrastructure
11.5 Integration of Machine Learning with 5G and V2X Communication
11.5.1 Introduction to Machine Learning Algorithms Used in Traffic Prediction
11.5.2 Overview of Data Sources and Features Used for Training Traffic Prediction Models
11.5.3 Challenges and Opportunities in Integrating Machine Learning with 5G and V2X Communication
11.5.4 Potential Applications of Machine Learning in Optimizing Traffic Flow and Management
11.6 Dynamic Traffic Prediction and Management
11.6.1 Real-Time Data Utilization for Dynamic Traffic Prediction
11.6.2 Techniques for Route Optimization and Vehicle Rerouting
11.6.3 Machine Learning and V2X in Dynamic Traffic Signal Optimization
11.6.4 Benefits of Adaptive Traffic Signal Control in Improving Traffic Flow and Reducing Congestion
11.6.5 Safety Applications and Collision Avoidance Systems
11.7 Future Directions and Challenges
11.7.1 Emerging Trends and Future Directions in the Integration of Machine Learning, 5G, and V2X Communication
11.7.2 Addressing Challenges
11.7.3 Opportunities for Further Research and Development in the Field of Intelligent Transportation Systems
11.8 Conclusion
References
12. Empowering Healthcare through Mobility as a Service: A Comprehensive Review
Manjunatha Badiger, Thrisha B., Kshithij H. S., Sathwik M. S. and Rakshitha N.
12.1 Introduction
12.2 Mobility as a Service (MaaS) in Healthcare
12.2.1 Overview of Healthcare Access Challenges
12.2.2 Enhancing Medical Access with Mobility as a Service
12.3 Low-Cost Generic Medicine Dispensers
12.4 Regulatory and Infrastructure Considerations
12.4.1 Challenges and Solutions
12.4.2 Strategic Partnerships and Stakeholder Engagement
12.4.3 Funding and Sustainability Models
12.4.4 Technology Integration and Digital Connectivity
12.4.5 User Education, Community Engagement, and Security Measures
12.5 Assessing Impact: Benefits to Healthcare, Economy, and Society
12.5.1 Environmental Considerations
12.5.2 Improved Public Health Outcomes
12.5.3 Enhanced Data Analytics and Health Insights
12.6 Future Perspective Empowering Healthcare MAAS to Support Healthcare
12.6.1 Environmental Considerations
12.7 Cost Reduction and Efficiency in Healthcare Delivery
References
13. An Enhanced Sustainable Mobility as a Service Based on 5G Network for Human-Centric Mobile Network in Smart City
Senthil G. A., R. Prabha, D. Roopa and S. Sridevi
13.1 Introduction
13.1.1 Objective and Benefits
13.2 Proposed Enhanced MaaS Framework
13.2.1 System Architecture
13.2.2 Service Components
13.2.3 Human-Centric Design
13.2.4 Mobility Analysis
13.3 Sustainability Analysis
13.3.1 Environmental Impact
13.3.2 Social Impact
13.3.3 Economic Impact
13.4 Challenges and Solutions
13.4.1 Technological Challenges
13.4.2 Communication Network and Bandwidth
13.4.3 Enabling Critical Infrastructures
13.4.4 Social and Regulatory Challenges
13.4.5 Quality of Service
13.5 Conclusion
13.6 Future Work
References
14. Design and Development of Foldable Electric Vehicle
Akshay S. Bhat, Puneeth H. S., P. Aniketh Solanki, Karthik P., Prajwal K. Kalal and Manoj S.
14.1 Introduction
14.2 Problem Formulation
14.3 Methodology and Material
14.3.1 Material Selection Process
14.3.2 Working
14.3.3 Electrical Components
14.4 Static Analysis
14.5 Results
14.6 Conclusion
References
15. Design and Development of Ultrasonic Assisted Collision Detection and Blind-Spot Reduction
Puneeth H. S., Akshay S. Bhat, Bhavani A., Lalit V., Sathyarjun A. B. and Vishnu K.J.
15.1 Introduction
15.1.1 Head-Up Display
15.1.2 Elements That Control IC Engine Vehicles’ Speed
15.1.2.1 Electronic Control Unit
15.1.2.2 Sensors Operated by ECU
15.1.2.3 Air–Fuel Ratio
15.1.2.4 Air–Fuel Ratio and Engine Performance
15.1.2.5 Throttle Body
15.1.3 Components Associated with the Vehicle Speed in EVs
15.1.3.1 Throttle
15.1.3.2 Motor
15.1.3.3 Controller
15.2 Problem Formulation
15.2.1 Integration of Head-Up Display
15.2.2 Vehicle Speed Controller
15.3 Methodology
15.3.1 Components Used
15.3.2 Construction and Working
15.4 Scope of the Project
15.4.1 Implementation in IC Engines
15.4.2 Implementation in Electric Vehicle
15.4.3 Head-Up Display
15.5 Results and Discussions
15.5.1 Results
15.5.2 Discussions
15.6 Conclusion
References
16. Voting Classifier-Based Machine Learning Technique for the Prediction of the Traffic Flow for the Intelligent Transportation System
Sandeep Kumar Hegde, Rajalaxmi Hegde and Thangavel Murugan
16.1 Introduction
16.2 Literature Review
16.3 Methodology
16.4 Experimental Results
16.5 Conclusion
References
17. Influence of Feature Selection Techniques for Social Media Data Analysis (Text and Image)
Aruna Bajpai and Yogesh Kumar Gupta
17.1 Introduction
17.2 Literature Review
17.3 Proposed Work
17.3.1 Text Feature Analysis
17.3.2 Image Feature Analysis
17.4 Results Analysis
17.5 Conclusions
Bibliography
About the Editors
Index
Back to Top
Preface
1. Arduino-Based Battery-Operated Multi-Purpose Portable Seed-Sowing Machine
K. Raju, M. Ajay Kumar and Canute Sherwin
1.1 Introduction
1.2 Background
1.3 Design Details of Seed-Sowing Machine
1.3.1 Selection of DC Motor
1.3.1.1 Rolling Resistance
1.3.1.2 Grade Resistance
1.3.1.3 Acceleration Force
1.3.1.4 Total Tractive Effort
1.3.1.5 Torque
1.3.1.6 Output Speed
1.3.1.7 Power
1.3.1.8 Battery Capacity Calculation
1.3.1.9 Run Time of the Battery
1.3.1.10 Battery Stand-By Time
1.4 Details of Components of Seed-Sowing Machine
1.4.1 Mechanical Components
1.4.1.1 Hopper
1.4.1.2 Wheel
1.4.1.3 Shaft and Bearing
1.4.1.4 Chain Drive and Sprocket Assembly
1.4.1.5 Tilling Tool
1.4.1.6 Trenching Tool
1.4.1.7 Leveling Tool
1.4.2 Electrical and Electronic Components
1.4.2.1 Battery
1.4.2.2 DC Motor
1.4.2.3 Servo Motor
1.4.2.4 Relay
1.4.2.5 Arduino
1.5 Methodology
1.5.1 Block Diagram of the Proposed Seed-Sowing Machine
1.5.2 CAD Modeling of Seed-Sowing Machine
1.5.3 The Working Principle of the Seed-Sowing Machine
1.6 Results and Discussion
1.7 Scope for Future Work
1.8 Conclusions
References
2. An Overview of Intelligent Mobility of Agricultural Drones
Prasad G., Sukumar Dhanapalan, Brandon Bernard Chiripanyanga, Trycene Tadiwanashe Tsabora and Felix Mwiya
Introduction
Background of the Research
Technology in Agriculture
Using Unmanned Aerial Vehicles in Animal Farming
Design Flow Process
Management Team, GTM Strategy, and Competitive Landscape
Design Constraints
Conclusion
References
3. Simulation of Proportional-Integral and Derivative (PID) Based Traction and Speed Control System for a Four-Wheel Electric Vehicle Using MATLAB Simulink
Canute Sherwin, Christina Sundari, Aryan Bakle and Mahijit Dodiya
3.1 Introduction
3.2 Literature Review
3.3 Methodology
3.4 Results and Analysis
3.5 Conclusion
References
4. A Case Study on Electric Vehicles (EV)
Sumiksha Shetty, Smitha A. B., Manjunatha Badiger and Chandra Singh
4.1 Introduction
4.2 Literature Survey
4.3 Government Initiatives
4.3.1 Faster Adoption and Manufacturing of Hybrid and Electric Vehicles (FAME II) Scheme
4.3.2 National Electric Mobility Mission Plan (NEMMP) 2020
4.3.3 Charging Infrastructure for Electric Vehicles—Guidelines and Standards of the Ministry of Power
4.3.4 State Government Initiatives
4.3.5 Public Sector Undertakings (PSUs) and Private Sector Collaboration
4.3.6 Smart Cities Mission
4.3.7 National Electric Mobility Infrastructure (NEMI) Guidelines
4.4 Challenges
4.4.1 Capital Intensive Investments
4.4.2 Power Supply and Grid Stability
4.4.3 The Issue of Uniformity in Charging Infrastructure
4.4.4 Space and Land Constraints
4.4.5 Legal and Bureaucratic Obstacles
4.4.6 Technology and Maintenance
4.4.7 Adoption Rate of EVs
4.4.8 Integration with Renewable Energy
4.5 Important Factors
4.6 Infrastructure
4.6.1 Charging Stations
4.6.2 Grid Upgrades
4.6.3 Battery Swapping Stations
4.6.4 Software Systems
4.7 Applications
4.8 Conclusion
References
5. Accelerating Connections with 5G and Evolution of Vehicle Communication Technology
Dankan Gowda V., Chippy T., V. Nuthan Prasad, Belsam Jeba Ananth M. and K.D.V. Prasad
5.1 Introduction
5.2 Historical Evolution of Vehicle Communication Technology
5.3 Foundations of 5G Technology
5.4 Integration of 5G in Vehicular Networks
5.5 Benefits of 5G in Automotive Communication
5.6 V2X Communication and 5G
5.7 Case Studies
5.8 Challenges and Future Directions
5.9 Conclusion
References
6. Predicting the Flow with Machine Learning Algorithms for Advanced Traffic Management
Dankan Gowda V., Rupali Suraskar, Ridhi Rani, K.D.V. Prasad and Ved Srinivas
6.1 Introduction
6.2 Fundamentals of Machine Learning in Traffic Management
6.3 Applications of ML in Traffic Prediction and Management
6.4 Case Studies
6.5 Challenges and Limitations
6.6 Future Trends and Innovations
6.7 Conclusion
References
7. Secure Routes and Cybersecurity Challenges in Autonomous Mobility Systems
Dankan Gowda V., Ribhu Abhusan P., V. Nuthan Prasad, K.D.V. Prasad and P. Vishnu Prasanth
7.1 Introduction
7.2 The Landscape of Autonomous Mobility
7.3 Cybersecurity Challenges
7.4 Secure Routes: Ensuring Safety in Navigation and Control
7.5 Defensive Technologies and Strategies
7.6 Regulatory and Standardization Efforts
7.7 Ethical and Privacy Considerations
7.8 Case Studies of Secure Autonomous Mobility Implementations
7.9 Future Directions and Research Opportunities
7.10 Conclusion
References
8. Green Routes Building the Backbone for Electric Vehicle Charging
Dankan Gowda V., Sadashiva V. Chakrasali, Ved Srinivas, K.D.V. Prasad and Saptarshi Mukherjee
8.1 Introduction
8.2 Current State of EV Charging Infrastructure
8.3 Technological Innovations in EV Charging
8.4 Designing Sustainable Charging Networks
8.5 Integration with Renewable Energy Sources
8.6 Economic and Business Models
8.7 Policy, Regulations, and Standards
8.8 Public Perception and Adoption
8.9 Future Directions and Innovations
8.10 Conclusion
References
9. Vehicular Power Line Communication
Smitha Gayathri D., K.R. Usha Rani and Yasha Jyothi Shirur
9.1 Introduction
9.2 Review and Categorization of Impedance Matching Techniques in Existing Literature
9.2.1 Impedance Matching: Concept and Classification
9.2.2 Related Works and Developments
9.3 Model of Vehicular Power Line Communication
9.3.1 The Resonance and Absorption Technique for Advanced Impedance Matching
9.3.1.1 Matching the Impedance to Access Inductive Impedance
9.3.1.2 System Structure
9.4 Simulation Results besides Analysis
9.5 Conclusion
References
10. Future Trends in V2X Communication and Interoperability
Dankan Gowda V., D. Palanikkumar, Satish Dekka, K.D.V. Prasad and Shivoham Singh
10.1 Introduction
10.2 Emerging Technologies in V2X Communication
10.3 Autonomous Vehicles and V2X Integration
10.4 Edge Intelligence and Decentralized Communication
10.5 Interoperability in a Multi-Vendor Ecosystem
10.6 Cybersecurity in Future V2X Systems
10.7 Environmental and Sustainability Considerations
10.8 User Experience and Human-Machine Interaction
10.9 Conclusion
References
11. Toward Smarter Streets: Leveraging Machine Learning, 5G, and V2X Communication for Traffic Insights
Smitha A. B., Manjunatha Badiger, Sumiksha Shetty, Chinmaya H., Sanketh C. Naik, Sujan R. Arasa, Ajay Deepak Lobo and Shreyas K.
11.1 Introduction
11.2 Literature Survey
11.3 5G Technology and Its Role in Transportation
11.4 Vehicular Communication and V2X Standards
11.4.1 Overview of Vehicular-to-Everything (V2X) Communication Technologies
11.4.2 V2X Communication Standards and Protocols
11.4.3 Importance of Interoperability for Seamless Communication between Vehicles and Infrastructure
11.5 Integration of Machine Learning with 5G and V2X Communication
11.5.1 Introduction to Machine Learning Algorithms Used in Traffic Prediction
11.5.2 Overview of Data Sources and Features Used for Training Traffic Prediction Models
11.5.3 Challenges and Opportunities in Integrating Machine Learning with 5G and V2X Communication
11.5.4 Potential Applications of Machine Learning in Optimizing Traffic Flow and Management
11.6 Dynamic Traffic Prediction and Management
11.6.1 Real-Time Data Utilization for Dynamic Traffic Prediction
11.6.2 Techniques for Route Optimization and Vehicle Rerouting
11.6.3 Machine Learning and V2X in Dynamic Traffic Signal Optimization
11.6.4 Benefits of Adaptive Traffic Signal Control in Improving Traffic Flow and Reducing Congestion
11.6.5 Safety Applications and Collision Avoidance Systems
11.7 Future Directions and Challenges
11.7.1 Emerging Trends and Future Directions in the Integration of Machine Learning, 5G, and V2X Communication
11.7.2 Addressing Challenges
11.7.3 Opportunities for Further Research and Development in the Field of Intelligent Transportation Systems
11.8 Conclusion
References
12. Empowering Healthcare through Mobility as a Service: A Comprehensive Review
Manjunatha Badiger, Thrisha B., Kshithij H. S., Sathwik M. S. and Rakshitha N.
12.1 Introduction
12.2 Mobility as a Service (MaaS) in Healthcare
12.2.1 Overview of Healthcare Access Challenges
12.2.2 Enhancing Medical Access with Mobility as a Service
12.3 Low-Cost Generic Medicine Dispensers
12.4 Regulatory and Infrastructure Considerations
12.4.1 Challenges and Solutions
12.4.2 Strategic Partnerships and Stakeholder Engagement
12.4.3 Funding and Sustainability Models
12.4.4 Technology Integration and Digital Connectivity
12.4.5 User Education, Community Engagement, and Security Measures
12.5 Assessing Impact: Benefits to Healthcare, Economy, and Society
12.5.1 Environmental Considerations
12.5.2 Improved Public Health Outcomes
12.5.3 Enhanced Data Analytics and Health Insights
12.6 Future Perspective Empowering Healthcare MAAS to Support Healthcare
12.6.1 Environmental Considerations
12.7 Cost Reduction and Efficiency in Healthcare Delivery
References
13. An Enhanced Sustainable Mobility as a Service Based on 5G Network for Human-Centric Mobile Network in Smart City
Senthil G. A., R. Prabha, D. Roopa and S. Sridevi
13.1 Introduction
13.1.1 Objective and Benefits
13.2 Proposed Enhanced MaaS Framework
13.2.1 System Architecture
13.2.2 Service Components
13.2.3 Human-Centric Design
13.2.4 Mobility Analysis
13.3 Sustainability Analysis
13.3.1 Environmental Impact
13.3.2 Social Impact
13.3.3 Economic Impact
13.4 Challenges and Solutions
13.4.1 Technological Challenges
13.4.2 Communication Network and Bandwidth
13.4.3 Enabling Critical Infrastructures
13.4.4 Social and Regulatory Challenges
13.4.5 Quality of Service
13.5 Conclusion
13.6 Future Work
References
14. Design and Development of Foldable Electric Vehicle
Akshay S. Bhat, Puneeth H. S., P. Aniketh Solanki, Karthik P., Prajwal K. Kalal and Manoj S.
14.1 Introduction
14.2 Problem Formulation
14.3 Methodology and Material
14.3.1 Material Selection Process
14.3.2 Working
14.3.3 Electrical Components
14.4 Static Analysis
14.5 Results
14.6 Conclusion
References
15. Design and Development of Ultrasonic Assisted Collision Detection and Blind-Spot Reduction
Puneeth H. S., Akshay S. Bhat, Bhavani A., Lalit V., Sathyarjun A. B. and Vishnu K.J.
15.1 Introduction
15.1.1 Head-Up Display
15.1.2 Elements That Control IC Engine Vehicles’ Speed
15.1.2.1 Electronic Control Unit
15.1.2.2 Sensors Operated by ECU
15.1.2.3 Air–Fuel Ratio
15.1.2.4 Air–Fuel Ratio and Engine Performance
15.1.2.5 Throttle Body
15.1.3 Components Associated with the Vehicle Speed in EVs
15.1.3.1 Throttle
15.1.3.2 Motor
15.1.3.3 Controller
15.2 Problem Formulation
15.2.1 Integration of Head-Up Display
15.2.2 Vehicle Speed Controller
15.3 Methodology
15.3.1 Components Used
15.3.2 Construction and Working
15.4 Scope of the Project
15.4.1 Implementation in IC Engines
15.4.2 Implementation in Electric Vehicle
15.4.3 Head-Up Display
15.5 Results and Discussions
15.5.1 Results
15.5.2 Discussions
15.6 Conclusion
References
16. Voting Classifier-Based Machine Learning Technique for the Prediction of the Traffic Flow for the Intelligent Transportation System
Sandeep Kumar Hegde, Rajalaxmi Hegde and Thangavel Murugan
16.1 Introduction
16.2 Literature Review
16.3 Methodology
16.4 Experimental Results
16.5 Conclusion
References
17. Influence of Feature Selection Techniques for Social Media Data Analysis (Text and Image)
Aruna Bajpai and Yogesh Kumar Gupta
17.1 Introduction
17.2 Literature Review
17.3 Proposed Work
17.3.1 Text Feature Analysis
17.3.2 Image Feature Analysis
17.4 Results Analysis
17.5 Conclusions
Bibliography
About the Editors
Index
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