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Drones for Transportation Logistics and Disaster Management

Edited by A. Prasanth, Rajesh Kumar Dhanaraj, Munish Sabharwal, Vandana Sharma, and Seifedine Kadry
Copyright: 2025   |   Expected Pub Date:2025//
ISBN: 9781394386420  |  Hardcover  |  
424 pages
Price: $225 USD
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One Line Description
Explore the future of logistics and disaster management with this essential guide to the design, applications, and challenges of integrating advanced drone technology into intelligent transportation systems.

Audience
Industry specialists, researchers, scientists, and engineers in the fields of computer science, transportation, environmental monitoring, disaster management, cybersecurity, and data science

Description
Drones are quickly becoming an essential technology for navigating inaccessible areas, especially during emergency situations. However, the implementation of these drones requires strict standards, policies, and procedures. Currently, drones are being used in several industrial and service sectors, extending the possibilities of handling transportation and logistics. The future of transportation is based on unmanned vehicles, and it is important to identify their challenges and futuristic applications.
Drones for Transportation Logistics and Disaster Management introduces the essential aspects of the technological advancement of drones, the challenges faced in current practices, and their advanced applications. The book describes future intelligent and resilient transportation systems backed by the Internet of Vehicle Things, the problems of big data analytics, and optimization techniques for in-house supply-chain management. Using a global multi-sector perspective, this volume will comprehensively cover essential components of drone systems, including their modeling, design, and maintenance, making it an essential guide for anyone looking to the future of disaster management.

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Author / Editor Details
A. Prasanth, PhD is an associate professor at Vel Tech Rangarajan Dr. Sagunthala Research and Development Institute of Science and Technology. He has published more than 45 research articles in international journals and conference proceedings, 12 books, and ten patents. His research interests include the Internet of Things, machine learning, wireless sensor networks, ad-hoc networks, and computer networks.

Rajesh Kumar Dhanaraj, PhD is a distinguished professor at Symbiosis International University. He has authored and edited more than 50 books on various cutting-edge technologies, holds 22 patents, and has contributed more than 115 articles to esteemed international journals and conferences. His research interests encompass machine learning, cyber-physical systems, and wireless sensor networks.

Munish Sabharwal, PhD is the Chief Operating Officer and a Professor of Computer Science and Engineering at the Institute of Integrated Learning in Management and an adjunct professor in the School of Digital Technologies at Samarkand State University with more than 25 years of experience. He has published more than 100 research papers in international journals and conferences. His current research interests include data sciences, biometrics, and e-banking.

Vandana Sharma, PhD is an associate professor at CHRIST University. She has published more than 75 research papers in international journals and conferences and is a member of the Women in Engineering Society. Her primary areas of interest include artificial intelligence, blockchain technology, and the Internet of Things.

Seifedine Kadry, PhD is Professor of Data Science at Beirut Arab University. He serves as Editor-in-Chief of the International Journal of Quality Control and Standards in Science and Engineering. He is an IEEE Senior Member, and IET Fellow. His research focuses are Data Science, AI applications, system prognostics, stochastic systems, and probability and reliability analysis.

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Table of Contents
Preface
1. Journey to Transportation and Logistics Management Using Drone: Digitization and Technological Evolution
Seema Rani, Misbah Anjum, Shivangi Chawla and Vandana Sharma
1.1 Introduction
1.1.1 Drone Development and Advancements
1.1.2 Sustainability Concern
1.2 Literature Review
1.3 Fundamental Elements of Drone Technology
1.4 Evolution of Drone Technology
1.5 Use Case in Various Sectors
1.6 Application in Transportation and Logistics
1.7 Conclusion
References
2. Challenges of Big Data Implementation in Drone-Based Logistics
Mani Deepak Choudhry, M. Sundarrajan, S. Jeevanandham and V. Saravanan
2.1 Introduction
2.2 Related Works
2.3 Big Data in Transit
2.4 Factors Affecting UAV Implementation in Logistics
2.4.1 Legal Factors
2.4.2 Financial Factors
2.4.3 Knowledge and Behavioral Factors
2.4.4 Privacy and Safety Factors
2.5 Conclusion
References
3. Frameworks for Handover Management for the Networks of Future Drones
S. L. Jany Shabu, Xiao-Zhi Gao, J. Refonaa and D. Poornima
3.1 An Overview
3.2 Literature Review
3.3 Handover Management for Future Drone Networks (HOM-FDN)
3.4 Results and Discussion
3.4.1 Accuracy Analysis
3.4.2 Efficiency Analysis
3.4.3 Performance Analysis
3.4.4 Safety Analysis
3.4.5 Prediction Analysis
3.5 Conclusion
References
4. Convergence of Internet of Vehicle Things and Drones: An Interoperability Perspective
V. Yokesh, N. Sathish, S. Lavanya and Pham Chien Thang
4.1 Introduction
4.1.1 Overview of IoT in Vehicles and Drones
4.1.2 Significance of Convergence
4.1.3 Significance of Interoperability
4.2 Communication Standards for Integration
4.2.1 Vehicular Communication Standards
4.2.2 Drone Communication Standards
4.2.3 Cross-Domain Communication Standards
4.2.4 Interoperability Considerations
4.3 Data Exchange Protocols
4.3.1 IoVT Data Exchange Protocols
4.3.2 Drone Data Exchange Protocols
4.3.3 Cross-Domain Data Exchange Protocols
4.3.4 Interoperability Considerations
4.4 Integration with Edge Computing
4.4.1 IoVT Integration with Edge Computing
4.4.2 Drone Integration with Edge Computing
4.5 Security and Privacy Measures
4.5.1 Security Measures
4.5.2 Privacy Measures
4.6 IoVT Regulations
4.6.1 Automotive Industry Standards
4.6.2 Compliance with Road Safety Regulations
4.6.3 Drone Regulations
4.7 Cross-Industry Collaboration
4.7.1 Synergies between IoVT and Drones
4.7.2 Industry Partnerships
4.8 Interoperability Challenges
4.8.1 Technical Challenges
4.8.2 Regulatory Challenges
4.9 Application and Future of IoVT and Drones
4.10 Conclusion
References
5. 5G Communication in Drones for Surveillance in Future Transportation Activities
N. Sathish, V. Yokesh, T. Kuntavai and Mariya Ouaissa
5.1 Introduction
5.2 Overview of 5G Communication
5.2.1 Key Features of 5G Networks
5.3 Drones in Transportation
5.3.1 Surveillance and Inspection
5.3.2 Delivery Services
5.3.3 Current Challenges for the Usage of Drones in Transportation
5.4 Drones and 5G Integration
5.5 Network Architecture for Drone and 5G in Transportation
5.5.1 Infrastructure of 5G Network
5.5.2 Edge Computing and Low Latency
5.5.3 Drone Traffic Management System
5.5.4 Authentication and Security
5.5.5 Analytics and Network Monitoring
5.5.6 Ground Control Stations (GCS)
5.5.7 Regulatory Compliance
5.5.8 Integration with Other Transportation Systems
5.5.9 Redundancy and Scalability
5.6 Security and Privacy Considerations
5.6.1 Security Considerations
5.6.2 Privacy Considerations
5.6.3 Enhanced Security Features in 5G
5.7 Regulatory and Ethical Considerations
5.7.1 Regulatory Considerations
5.7.2 Ethical Considerations
5.8 Future Trends and Innovations
5.9 Conclusion
References
6. Impact and Assessment of Artificial Intelligence-Enabled UAV for Real-Time Data Streaming Application
Gobinath C., Thanjaivadivel M., Sarathkumar Rangarajan and K. Kalaivanan
6.1 Introduction
6.2 Overview of UAVs Powered by AI
6.2.1 Understanding AI-Enabled UAVs: Definition and Features
6.2.2 Capabilities of AI-Enabled UAVs
6.2.3 Advantages of Using UAVs for Data Streaming
6.2.3.1 Quick and Effective Information Gathering
6.2.3.2 Improved Safety Features and Higher Cost-Effectiveness
6.2.3.3 Accuracy and Precision
6.2.3.4 Real-Time Decision Support
6.2.3.5 Access to Remote Regions
6.2.3.6 Enhanced Monitoring and Surveillance
6.2.3.7 Scalability and Flexibility
6.2.4 Most Important Technologies and Components Utilized
6.3 Applications of AI-Enabled UAVs in Real-Time Data Streaming
6.3.1 Environmental Monitoring and Conservation
6.3.1.1 Wildlife Conservation
6.3.1.2 Forestry and Land Governance
6.3.1.3 Marine and Coastal Surveillance
6.3.1.4 Environmental Research
6.3.2 Disaster Management and Response
6.3.2.1 Search and Rescue Operations
6.3.2.2 Damage Assessment
6.3.2.3 Hazard Monitoring
6.3.2.4 Evacuation Planning
6.3.3 Precision Agriculture and Crop Monitoring
6.3.3.1 Crop Health Assessment
6.3.3.2 Irrigation Management
6.3.3.3 Yield Forecasting
6.3.3.4 Soil Analysis
6.3.4 Infrastructure Inspection and Maintenance
6.3.4.1 Bridge and Building Inspections
6.3.4.2 Power Line and Utility Inspections
6.3.4.3 Monitoring Oil and Gas Facilities
6.3.4.4 Railway and Pipeline Inspections
6.3.5 Surveillance and Public Safety
6.4 Case Studies: Real-World Implementations
6.4.1 AI-Enabled UAVs for Monitoring Wildlife Populations
6.4.2 UAV-Based Aerial Imagery for Disaster Assessment
6.4.3 Precision Agriculture Using AI Algorithms and UAVs
6.4.4 Automated Infrastructure Inspection with UAVs
6.4.5 UAVs for Surveillance and Emergency Response
6.4.6 Machine Learning and Deep Learning Techniques
6.4.6.1 Advancements in Machine Learning
6.4.6.2 Reinforcement Learning (RL)
6.4.6.3 Transfer Learning
6.4.6.4 Interpretable Models
6.4.6.5 Advancements in Deep Learning
6.4.6.6 Convolutional Neural Networks
6.4.6.7 Recurrent Neural Networks (RNNs) and Long Short-Term Memory (LSTM)
6.4.6.8 Generative Adversarial Networks (GANs)
6.4.7 Object Detection and Recognition
6.4.7.1 Single-Stage Object Detectors
6.4.7.2 Two-Stage Object Detectors
6.4.7.3 Optimal Object Detection
6.4.7.4 Fine-Grained Object Recognition
6.4.8 Image and Video Processing
6.4.8.1 Real-Time Image Segmentation
6.4.8.2 Image and Video Signature
6.4.8.3 Video Analysis
6.4.8.4 Model Generation for Creativity and Art
6.4.9 Sensor Fusion and Data Integration
6.4.9.1 Multimodal Sensor Fusion
6.4.9.2 Healthcare Data Integration
6.4.9.3 Environmental Monitoring
6.4.9.4 Industrial Automation
6.4.9.5 Smart Cities
6.5 Challenges and Considerations in AI-Enabled UAVs for Real-Time Data Streaming Applications
6.5.1 Data Privacy and Security
6.5.2 Regulatory Frameworks and Airspace Management
6.5.3 Technical Constraints and Limitations
6.5.4 Ethical Considerations and Societal Impact
6.6 Future Directions and Opportunities
6.6.1 Integration of AI and UAV Technologies
6.6.2 Collaborative Research and Development
6.6.3 Policy Implications and Standardization
6.6.4 Advancements in Hardware and Software Solutions
6.7 Conclusion and Future Enhancements
References
7. Blockchain-Based Security and Privacy Solutions for Drones Systems
Sugandhi Malhotra, Gaganjot Kaur, K. Saranya and Anu Sayal
7.1 Introduction
7.1.1 Principle Functionality of the Blockchain
7.1.2 Foundation of Drones
7.1.3 Blockchain and Drones Security
7.1.4 Related Work
7.2 Drones – The New Network Architecture
7.2.1 Components and Parameters
7.2.2 Drone Parameters
7.2.3 Drones Network Topology Architecture
7.3 Drones Privacy Solutions
7.4 Integration of Blockchain Functioning with Drones
7.5 Security Challenges and the Road Ahead
7.6 Conclusion
References
8. Design and Development of Modular and Multifunctional UAV for Amphibious Landing and Surround Sense Module
Surendar G., Balasubramanian E., Choi Jae-Sung and C.H. Nirmal Prabhath
8.1 Introduction
8.2 UAV Design Considerations
8.2.1 Design Parameters and Features
8.2.2 Aerodynamic Characteristics
8.2.3 Power Requirements
8.3 Development of Modular UAV
8.4 Surround Sense Module
8.5 Integration and Testing
8.6 Conclusion
Acknowledgement
References
9. Implementing Mission Critical Public Safety Using Communication in Drones Network
V. Nithya, Mani Deepak Choudhry, M. Parimala Devi and S. Jayachitra
9.1 Introduction
9.2 Related Work
9.3 UAV – Characteristics and Strategies
9.3.1 What is UAV?
9.3.2 How Does UAV Work?
9.3.3 UAV Categorization
9.3.4 Drones for Public Security
9.3.5 UAV Placement Strategies
9.4 Communication Framework Support by UAVs
9.4.1 Potential Roles
9.5 Conclusion
References
10. Assessing the Impact of Drones on Students’ Engagement and Learning Outcomes
M. Narendran, S. Surendiran, Alamgir Khan and Mahender Singh
10.1 Introduction
10.1.1 Background and Context of the Study
10.1.2 Significance of Exploring Drone-Assisted Learning
10.1.3 Research Objectives
10.2 Literature Review
10.2.1 Overview of Drones in Education
10.2.2 Previous Research on Student Engagement and Learning Outcomes with Technology Integration
10.2.3 Theoretical Frameworks Supporting the Use of Drones in Education
10.3 Methodology
10.3.1 Research Design and Approach
10.3.2 Participant Selection and Sampling Strategy
10.3.3 Data Collection Methods
10.3.4 Data Analysis Plan
10.4 Implementation of Drone-Assisted Learning Activities
10.4.1 Design of Curriculum-Aligned Drone Activities
10.4.2 Integration Across Different Subjects and Disciplines
10.4.3 Logistical Considerations and Safety Measures
10.5 Results and Analysis
10.5.1 Quantitative Analysis of Pre- and Post-Assessment Data
10.5.2 Examination of Survey and Questionnaire Responses
10.5.3 Thematic Analysis of Interview and Focus Group Data
10.6 Discussion
10.6.1 Interpretation of Findings in Relation to Research Objectives
10.6.2 Comparison with Existing Literature and Theoretical Frameworks
10.6.3 Implications for Student Engagement and Learning Outcomes
10.6.4 Addressing Limitations and Potential Challenges
10.7 Recommendations
10.7.1 Practical Implications for Educators and Policymakers
10.7.2 Guidance for Successful Integration of Drones in Education
10.7.3 Future Research Directions
10.8 Conclusion
References
11. Implementation of Delivery Drones in the Logistics Business Process
Jeevitha D., S. Venkatesh, R. Sathya and Raffaele Mascella
11.1 Introduction
11.1.1 Logistics Industry Background
11.1.2 Emergence of Drones
11.2 Logistics Advantages of Delivery Drones
11.3 Challenges and Considerations
11.3.1 Technical Limitations and Reliability
11.3.2 Weather Regulations and Safety Issues
11.3.3 Environmental Factors
11.4 Integration Strategies
11.4.1 Last-Mile Deliveries
11.4.2 Warehouse-to-Warehouse Transport
11.4.3 Remote Area Accessibility
11.4.4 Emergency and Medical Supply Delivery
11.5 Technical Components of Delivery Drones
11.5.1 Communication Systems
11.5.2 Sensors and Navigation
11.6 Data Management and Analytics
11.7 Environmental and Social Impact
11.7.1 Carbon Footprint Reduction
11.7.2 Employment Opportunities
11.7.3 Public Perception and Acceptance
11.8 Case Study
11.9 Conclusion
References
12. Social and Ethical Issues of Using Drones in Logistics and Disaster Management
M. Nalini, N. Prashithaa, Rajesh Kumar Dhanaraj and F.H.A. Shibly
12.1 Introduction
12.1.1 An Overview of Drones for Disaster Relief and Logistics
12.1.2 Importance of Addressing Social and Ethical Issues
12.2 The Role of Drones in Logistics and Disaster Management
12.2.1 Utilizations and Benefits
12.2.2 Current Drone Usage Trends
12.3 Privacy Concerns
12.3.1 Observation and Data Collection
12.3.2 Legal Frameworks for Privacy Protection
12.4 Challenges and Considerations
12.4.1 Safety and Security
12.4.2 Risk of Accidents and Collisions
12.4.3 Unauthorized Drone Use and Security Risks
12.4.4 Environmental Impact
12.4.5 Ethical Dilemmas
12.4.6 Community Engagement
12.5 Regulatory Frameworks
12.5.1 A Brief Overview of the Drone Regulations
12.5.2 Issues and Changing Policies
12.6 Case Studies
12.6.1 Best Practices for Addressing Ethical Concerns
12.6.2 Technological Solutions for Safer and More Ethical Operations
12.6.3 Future Directions
12.7 Conclusion
References
13. Regulatory Overview and Challenges of Drone Technology in Safety Regulation
S. Vijayanand, T.S. Pradeepkumar, M. Annalakshmi and Azween Bin Abdullah
13.1 Introduction
13.1.1 Need for Regulation to Ensure Safe and Responsible Use
13.1.2 Objectives and Scope
13.1.3 Regulatory Bodies and Framework
13.2 FAA Oversight and Authority Over US Airspace
13.2.1 FAA Drone Regulations – Part 107, COAs, Recreational Use Rules
13.2.2 Role of State and Local Laws Related to Privacy and Data Collection
13.2.3 International Regulations and Bodies Like EASA, ICAO, and Individual Country Rules
13.3 Key Regulatory Challenges
13.3.1 Safety – Collision Avoidance, Flight Over People, Certification
13.3.2 Privacy and Data Protection Laws
13.3.3 Security – Geo-Fencing, Tampering, Cybersecurity
13.3.4 Enforcement and Identification – Registration, Remote ID
13.3.5 Urban Air Mobility and Autonomous Operations
13.3.6 Environmental Impact – Noise, Emissions, Wildlife
13.4 Industry Standards and Best Practices
13.4.1 Consensus Safety Standards – ASTM, ISO
13.4.2 Industry Knowledge Sharing Programs and Partnerships
13.4.3 Operator Certification Programs and Training Requirements
13.4.4 Insurance Requirements and Risk Management
13.5 Regulatory Outlook and Future Needs
13.5.1 Projected Regulatory Changes and Updates
13.5.1.1 Speed of Regulatory Innovation
13.5.2 Streamlining and Harmonizing Global Regulations
13.5.3 Performance and Risk-Based Regulations Using Industry Data
13.5.4 Automated Enforcement and Monitoring Technology
13.5.5 Regulatory Gaps and Challenges for Advanced Operations Like UAM
13.6 Conclusions and Recommendations
13.6.1 Conclusions
13.6.2 Recommendations
References
14. Drone-Based Application of Warehouse Logistics – A Case Study
Sangeetha Radhakrishnan, A. Prasanth, K.K. Devi Sowndarya and Ahmed A. Elngar
14.1 Introduction
14.1.1 Warehouse Logistics
14.1.2 Challenges of Warehouse Logistics
14.1.3 Improving Warehouse Logistics
14.1.4 Advantages of Warehouse Logistics
14.1.5 Cogitation of Warehouse Influencing the Warehouse Logistics
14.1.6 Importance of Warehousing in Logistics
14.1.7 Aspects of Warehouse in a Logistics System
14.1.8 Purpose of Logistical Warehousing
14.1.9 Kinds of Warehouse Logistics
14.2 Drones
14.2.1 Classification of Drones
14.2.2 Application Areas of Drones
14.2.3 Areas of Indoor Drone Use Cases
14.2.4 State of Drone Technology
14.3 Usage of Drones in Inventory Management
14.3.1 Challenges in Drone Technology Implementation in Warehouses
14.3.2 How Drones can Simplify Inventory Management
14.3.3 Drones Impact in the Product Delivery Ecosystem
14.3.4 Technical Challenges
14.4 Application of Drone in Warehouse Logistics
14.4.1 Simulation Environment and Data Collection
14.4.2 Identification and Positioning of Fiducial Markers in the Simulation Environment
14.4.3 Machine Learning Techniques
14.4.4 Regression Algorithms
14.5 Conclusion
References
15. Data Driven Emergency Response Management for UAV-Based Future Transportation – A Case Study
D. Vinodha, J. Jenefa, E.A. Mary Anita and Sameer Al-Dahidi
15.1 Scope
15.2 Applications of UAV During Emergency Response Management
15.2.1 Remote Monitoring
15.2.2 UAV Mapping
15.2.3 Delivering Emergency Products
15.2.4 Forest Fire Rescue Operation
15.3 Challenges and Solutions
15.3.1 Data Security and Privacy Concerns
15.3.2 Integration of Diverse Data Sources
15.3.3 Real-Time Data Processing
15.3.4 Regulatory Compliance and Legal Frameworks
15.3.5 Data Accuracy and Reliability
15.3.6 UAV Operational Challenges
15.3.6.1 Collision Avoidance
15.3.6.2 Air Traffic Management
15.3.6.3 Weather Conditions
15.3.6.4 Cybersecurity
15.3.6.5 Human Error
15.3.6.6 Battery Life and Range
15.3.6.7 Mechanical Failures
15.3.7 Interoperability and Communication
15.3.7.1 System Integration
15.3.7.2 Standardized Communication Protocols
15.3.7.3 Communication Between UAVs
15.3.7.4 Communication with Ground Control Stations
15.3.7.5 Data Exchange for Traffic Management
15.3.7.6 Interagency Collaboration
15.3.7.7 Remote Pilot Interfaces
15.3.7.8 Secure Communication
15.3.7.9 Adaptability to Changing Environments
15.3.7.10 Updates and Compatibility
15.3.8 Ethical and Social Implications
15.4 Learning and Knowledge Outcomes
15.5 Conclusion
References
16. Remote Assessments and Aerial Imaging Using UAV for Disaster Management and Precision Agriculture with Immediate Response – A Case Study
Kalaivanan Karunanithy, Bhanumathi Velusamy and A. Prasanth
16.1 Introduction
16.2 Various Types of Cameras Used in Remote Sensing
16.2.1 RGB Camera in Remote Sensing
16.2.2 Thermal Camera in Remote Sensing
16.2.3 Hyper, Multi-Spectral Camera in Remote Sensing
16.2.4 LiDAR in Remote Sensing
16.3 Machine Learning-Based Object Identification
16.3.1 Support Vector Machine
16.3.2 Decision Tree
16.3.3 Random Forest
16.3.4 K-Nearest Neighbor
16.3.5 Naive-Bayes Classifier
16.3.6 Convolutional Neural Networks (CNN)
16.3.7 K-Means Clustering
16.4 Challenges and Limitations of Technology Deployment in Disaster Management
16.5 Case Studies
16.5.1 Cyclone Triggered Landslide – Ischia (2022)
16.5.2 Forest Fire - Spain (2022), Argentina (2021) and Portuguese (2023)
16.5.3 Volcano Eruption – Andaman Territory (2022)
16.6 Conclusion
References
Index

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