Drones for Transportation Logistics and Disaster Management

• Autore: Prasanth A
• Pubblicazione: Newark : , : John Wiley & Sons, Incorporated, , 2025; ©2026
• Edizione: 1st ed.
• Descrizione fisica: 1 online resource (430 pages)
• Altri autori: DhanarajRajesh Kumar SabharwalMunish SharmaVandana KadrySeifedine
• Nota di contenuto: Cover -- Series Page -- Title Page -- Copyright Page -- Contents -- Preface -- Chapter 1 Journey to Transportation and Logistics Management Using Drone: Digitization and Technological Evolution -- 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 -- Chapter 2 Challenges of Big Data Implementation in Drone-Based Logistics -- 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 -- Chapter 3 Frameworks for Handover Management for the Networks of Future Drones -- 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 -- Chapter 4 Convergence of Internet of Vehicle Things and Drones: An Interoperability Perspective -- 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 -- Chapter 5 5G Communication in Drones for Surveillance in Future Transportation Activities -- 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. ; Chapter 6 Impact and Assessment of Artificial Intelligence-Enabled UAV for Real-Time Data Streaming Application -- 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 -- Chapter 7 Blockchain-Based Security and Privacy Solutions for Drones Systems -- 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 -- Chapter 8 Design and Development of Modular and Multifunctional UAV for Amphibious Landing and Surround Sense Module -- 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 -- Chapter 9 Implementing Mission Critical Public Safety Using Communication in Drones Network -- 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 -- Chapter 10 Assessing the Impact of Drones on Students' Engagement and Learning Outcomes -- 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.
• Sommario/riassunto: 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.Drones are quickly becoming an essential technology for navigating inaccessible areas, especially during emergency situations.
• Titolo autorizzato: Drones for Transportation Logistics and Disaster Management
• ISBN: 1-394-38645-1; 1-394-38644-3
• Formato: Materiale a stampa
• Livello bibliografico: Monografia
• Lingua di pubblicazione: Inglese
• Record Nr.: 9911038525403321
• Lo trovi qui: Univ. Federico II