Unmanned Aerial Vehicles in Smart Cities (eBook)

Preface 7
Contents 8
About the Editor 10
A Comprehensive Review on the Use of AI in UAV Communications: Enabling Technologies, Applications, and Challenges 11
1 Introduction 11
2 Applications 12
2.1 Intelligent Transportation Systems (ITSs) 12
2.2 Agriculture 13
2.3 Disaster Management 13
2.4 Security and Surveillance 13
2.5 Remote Sensing and Geology 14
2.6 Healthcare 14
2.7 Military 14
2.8 Smart Cities 15
3 Applied Communication Protocols and Technologies 15
4 Communication Architectures 17
4.1 UAV Components 20
4.1.1 Primary Components 20
4.1.2 Secondary Components 21
5 Applied AI 21
5.1 Design Factors and Requirements 22
5.1.1 Hard Design Factors 22
5.1.2 Soft Design Factors 23
5.2 Features 27
5.3 Online Vs. Offline Classifications 29
6 Open Issues 29
6.1 Wireless Challenges 30
6.2 Security 30
6.3 UAV Autonomy 30
6.4 Deep Learning Challenges 31
7 Conclusions 31
References 31
UAVs Healthcare Applications, Communication Protocols, Deployment Strategies, and Security Challenges 37
1 Introduction 37
2 UAVs Application in Healthcare: A Brief Overview 38
3 UAVs Communication Protocols and Technologies 39
4 UAVs Deployment Techniques 41
4.1 UAVs Random Deployment 41
4.2 UAVs Controlled Deployment 41
5 UAVs Security Aspects and Issues 42
6 Challenges and Future Research Directions 43
6.1 Challenges 44
6.2 Future Research Trends 45
7 Conclusion 45
References 45
Machine Learning Applications for Internet of Flying Vehicles in Case of Critical and Environmental Cases 48
1 Introduction 48
2 Related Works 51
3 Suggested Framework 53
3.1 Severe Environmental Cases 54
3.2 Accidents and Emergency Cases 54
3.3 Real-Time Traffic Management 54
3.4 Crowded Events Surveillance 55
3.5 Deployment Aspects 55
4 Conclusions and Future Works 55
References 56
Trends, Issues, and Challenges in the Domain of IoT-Based Vehicular Cloud Network 58
1 Introduction 58
2 Vehicular Cloud 60
3 IoT-Based Vehicular Cloud Computing and Application Scenarios 61
4 Challenges and Currents Issues in IoT-Based Vehicular Cloud Network 64
4.1 Application Programming Interfaces (APIs) 64
4.2 Security and Privacy 65
4.3 Performance and Reliability 65
4.4 Big Data 66
4.5 Heterogeneity and Interoperability 66
4.6 Cloud-Layered Architecture and Service Models Issues and Challenges 66
5 Machine Learning for IoT-Based Vehicular Cloud Network 68
6 Blockchain for IoT-Based Vehicular Cloud Network 70
7 Conclusion 71
References 72
Detection and Identification of Vehicles from High-Resolution Aerial Images Using Deep Learning Approaches with the Tuned Parameters 74
1 Introduction 74
2 Literature Survey 76
3 Methodology 79
3.1 Proposed System 79
3.2 Pre-Processing 79
3.3 Region Proposal Network 79
4 Vehicle Classification 82
5 Dataset 83
6 Training Parameters and Implementation Details 84
7 Experiments and Results 85
8 Conclusion 90
References 90
An Efficient Palm-Dorsa-Based Approach for Vein ImageEnhancement and Feature Extraction in Cloud ComputingEnvironment 93
1 Introduction 93
2 Literature Review 97
3 Hardware Design Performance Evaluation 100
3.1 The Algorithm 100
3.2 The Input Vein Images 104
3.2.1 The Resample 104
3.2.2 Vein Image Segmentation 105
3.3 The Median Filter Implementation on Vein Images 107
3.4 Thinning of Vein Images 107
3.5 Output Vein Images 108
3.6 Hardware Design of Vein Image Enhancement and Feature Extraction Algorithm 108
4 Conclusions and Future Work 110
References 112
Leveraging Unmanned Aerial Vehicles in Mining Industry: Research Opportunities and Challenges 115
1 Introduction 115
2 Background 117
2.1 Potential Application of UAV in Mines 118
2.1.1 Mine Surveying 118
2.1.2 Drilling and Blasting 119
2.1.3 Mine Management 120
2.1.4 Mine Safety 121
2.1.5 Mine Construction 122
2.2 Basic Networking Architecture and Channel Characteristics 123
2.2.1 Control and Non-payload Communications 124
2.2.2 Data Link 125
2.2.3 UAV-Ground Communication Channel 126
2.2.4 UAV–UAV Communication Channel 127
3 Design Considerations 127
3.1 Optimized Path Planning 127
3.2 Energy Efficient Communication 128
4 UAV Aided Emergency Wireless Communication 129
4.1 Proposed Framework 129
4.1.1 The Design of SkyHelp 129
4.1.2 Wireless Channel Characteristics of Opencast Mines 130
4.2 SkyHelp Framework 131
5 Performance Evaluation and Preliminary Analysis 131
6 Conclusion 135
References 137
UAV and Fog Computing for IoE-Based Systems: A Case Study on Environment Disasters Prediction and Recovery Plans 141
1 Introduction 141
2 Background 143
2.1 Internet of Everything 143
2.2 Unmanned Aerial Vehicle (UAV) 144
2.3 Fog Computing 145
3 UAV-Fog Collaboration and Coordination 146
3.1 Collaborative UAVs 147
3.2 Collaborative Fogs Computing 149
3.3 Coordination of UAV and fog 149
4 UAV-Fog for Environment Disasters Management 151
4.1 Disaster Management Stages 151
4.2 Disasters Monitoring, Preparedness and Early Warning 153
4.2.1 Disasters Monitoring 153
4.2.2 Preparedness and Early Warning 154
4.3 Situational Awareness, Logistics and Evacuation 155
4.3.1 Situational Awareness 155
4.3.2 Logistics and Evacuation 155
4.4 Search and Rescue Missions 156
5 Conclusions 156
References 157
Drone of IoT in 6G Wireless Communications: Technology, Challenges, and Future Aspects 161
1 Introduction 161
1.1 IoT Wireless Technologies 162
1.2 UAVs with IoT Integration 164
1.3 UAV and IoT: A State of the Art 165
1.4 Satellite and IoT Network 165
2 UAVs, IoT, and Emerging 6G Technologies 166
2.1 Emerging Trends in Mobile Networks 167
2.2 Integrated Wireless Technologies 168
3 Technical Requirement and Specification 169
3.1 Network Characteristics 169
3.2 General Requirements in Networks 169
4 Key Responsibilities in 6G 170
5 Challenges and Future Aspects 170
6 Conclusion 171
References 172
Image Processing in Unmanned Aerial Vehicles 174
1 Introduction 174
2 Classification of UAV Types 175
3 Application Areas of UAVs 176
4 Image Processing in UAV Images 177
4.1 Analysis and Segmentation 178
4.2 Identification and Prediction 179
4.3 3D Reconstruction 182
5 Discussions and Conclusions 183
References 184
Index 187