Computational Intelligence for Unmanned Aerial Vehicles Communication Networks (Studies in Computational Intelligence, 1033)

✍ Scribed by Mariya Ouaissa (editor), Inam Ullah Khan (editor), Mariyam Ouaissa (editor), Zakaria Boulouard (editor), Syed Bilal Hussain Shah (editor)

• Publisher: Springer
• Year: 2022
• Tongue: English
• Leaves: 294
• Category: Library

✦ Synopsis

This book aims to provide a vision that can combine the best of both Artificial Intelligence (AI) and communication networks for designing the deployment trajectory to establish flexible Unmanned Aerial Vehicles (UAV) communication networks.This book will discuss the major challenges that can face deploying unmanned aerial vehicles in emergent networks. It will focus on possible applications of UAV in a Smart City environment where they can be supported by Internet of Things (IoT), wireless sensor networks, as well as 5G, and beyond. This book presents the possible problems and solutions, the network integration of the UAV and compare the communication technologies to be used.This book will be a collection of original contributions regarding state of the art AI/ML based solutions in UAV communication networks which can be used for routing protocol design, transport layer optimization, user/application behaviour prediction, communication network optimization, security, and anomaly detection.

✦ Table of Contents

Preface
Contents
About the Editors
Machine Learning and AI Approach to Improve UAV Communication and Networking
1 Introduction
2 Literature Discussions
3 UAVs Characteristics
4 Artificial Intelligence and Machine Learning
4.1 Machine Learning Approaches
5 Unsupervised and Supervised ML for UAVs
5.1 Supervised-Based Learning
5.2 Unsupervised Learning Overview
6 Solution for UAVs-Based Issues
6.1 UAVs Coordination and Placement
6.2 Path Calculation
6.3 Virtual Reality in Drones
6.4 Abnormalities in Drone Monitoring
6.5 UAVs Detection
7 Interpretation and Future Practice
8 Conclusion
References
Implementation of Machine Learning Techniques in Unmanned Aerial Vehicle Control and Its Various Applications
1 Introduction
2 Classification of UAV
3 Unmanned Aerial Vehicle (UAV) Market Trends and Values
4 Machine Learning Techniques for UAV Applications
4.1 Linear Regression
4.2 Logistic Regression
4.3 Decision Tree (DT)
4.4 Random Forest (RF)
4.5 Support Vector Machine (SVM)
5 Applications of Machine Learning Techniques in UAV
6 Summary and Discussion
7 Conclusion
References
Machine Learning Techniques for UAV Trajectory Optimization—A Survey
1 Introduction
1.1 What is UAV?
1.2 Machine Learning with Artificial Intelligence
2 Survey Works
2.1 Issues on Physical Layer
2.2 Channel—Modeling
2.3 Interference Management
2.4 Configuration of Transmission Parameters
3 Resource Management and Network Planning
4 Open Issues
4.1 Implementation
4.2 Issues in Physical Layer
4.3 Issues in Security and Privacy
5 Conclusion
References
Metaheuristic Algorithms for Integrated Navigation Systems
1 Introduction
2 Expressing the Navigation Problem
2.1 Inertial Navigation
2.2 Integrated Navigation
3 Optimization by Using Metaheuristic Algorithms
3.1 Genetic Algorithm
3.2 Particle Swarm Optimization
3.3 Inclined Planes System Optimization
3.4 Modified Inclined Planes System Optimization
4 Metaheuristic Algorithms for Designing Integrated Navigation Systems
5 Results
6 Conclusions
References
Security Threats in Flying Ad Hoc Network (FANET)
1 Introduction
2 Overview of FANET
2.1 Network Topology
2.2 Mobility Models
2.3 Node Mobility
2.4 Node Density
2.5 Localization
2.6 Power Consumption
2.7 Radio Propagation Model
3 Literature Review
4 Security in FANET
5 Security Challenges
5.1 Dynamic Network Topology
5.2 High Mobility
5.3 Error Tolerance
5.4 Latency Control
5.5 Key Distribution
5.6 Data Consistency
5.7 Location Awareness
5.8 Need of High Computational Ability
5.9 Privacy
5.10 Routing Protocol
5.11 Network Scalability
6 Security Services
6.1 Availability
6.2 Confidentiality
6.3 Data Integrity
6.4 Authentication
6.5 Non-repudiation
7 Types of Attackers
7.1 Basis of Membership
7.2 Basis of Intention
7.3 Basis of Activity
7.4 Basis of Scope
8 Security Threats
8.1 Attack on Availability
8.2 Attack on Confidentiality
8.3 Attack on Data Integrity
8.4 Attack on Authentication
8.5 Attack on Non-repudiation
9 Solution for Security Threats
9.1 SEAD
9.2 Ariadne
9.3 RobSAD
9.4 ARAN
9.5 SAODV
9.6 A-SAODV
9.7 One Time Cookie
10 Conclusion
References
Secure Communication Routing in FANETs: A Survey
1 Introduction
2 Literature Review
3 Wireless Communication
3.1 Mobility Models
3.2 Time-Dependent Mobility Models
3.3 Routing Protocols in FANETs
4 Conclusion
References
Impact of Routing Techniques and Mobility Models on Flying Ad Hoc Networks
1 Introduction
1.1 Types of Networks
1.2 Traditional Network
2 Background Study
2.1 Mobile Ad Hoc Network (MANET)
2.2 Vehicular Ad Hoc Network (VANET)
2.3 Flying Ad Hoc Network (FANET)
2.4 Single, Multiple and Multiple-group UAVs Application Network
2.5 Classification of UAVs
2.6 Mobility Models
2.7 Routing Techniques
3 Conclusion and Future Direction
References
Analysis of Vulnerabilities in Cybersecurity in Unmanned Air Vehicles
1 Introduction
2 Motivation
3 Cybersecurity Threats
3.1 Spoofing
3.2 Tampering
3.3 Repudiation
3.4 Information Disclosure
3.5 Dos
3.6 Elevation of Privilege
4 Attacks
4.1 Spoofing Attack
4.2 Man in the Middle Attack
4.3 DoS Attack
4.4 Buffer Overflow Attack
4.5 Eaves Dropping Attack
5 Conclusion
References
Silent Listening to Detect False Data Injection Attack and Recognize the Attacker in Smart Car Platooning
1 Introduction
2 Related Works
2.1 Summary of Contributions
2.2 Chapter Organization
3 Research Method
3.1 FDI Attack Detection
3.2 FDI Attacker Recognition
3.3 Smart-Car Based Test Bed Creation for Sample Collection
3.4 Procedure
3.5 Instruments
3.6 Data Analysis Technique
4 Results and Discussion
4.1 Examining Correctness of Algorithms1 and 2
4.2 Brief Answers for RQs
5 Conclusion
References
Taxonomy of UAVs GPS Spoofing and Jamming Attack Detection Methods
1 Introduction
1.1 Motivation Based on the Statical Reports
1.2 Classification of UAVs
1.3 Design Considerations of UAV
2 Taxonomy of UAV Routing Protocols
2.1 Topology Based Routing
2.2 Position-Based Routing
2.3 Hierarchical Routing
2.4 Probabilistic Routing Protocols
2.5 AI-Enabled Routing Protocols
2.6 Deterministic Routing Protocol
2.7 Stochastic Routing Protocols
2.8 Social Network-Based Approach
3 Vulnerabilities in UAV
3.1 System-Related Vulnerabilities
3.2 Propagation Channel Vulnerabilities
3.3 Interference’s Vulnerabilities
4 GPS Spoofing and Jamming Attacks
4.1 GPS Spoofing Attack
4.2 Jamming Attack
5 Literature Survey
6 Conclusion
References
Investigation on Challenges of Big Data Analytics in UAV Surveillance
1 Introduction
1.1 UAV Surveillance
1.2 Application of UAV Surveillance
1.3 Importance of UAV Surveillance
2 Big Data Analytics
2.1 Importance of Big Data Analytics
2.2 Significance of Big Data Analytics in UAV Surveillance
3 Background Study
4 Challenges of Big Data Analytics in UAV Surveillance
4.1 Safety
4.2 Privacy
4.3 Security
5 Conclusion
References
UAV-Based Photogrammetry and Seismic Zonation Approach for Earthquakes Hazard Analysis of Pakistan
1 Introduction
2 UAVs Impacts in Hazard Analysis and Rescue-Based Mission
3 Seismicity of the Area
4 Regional Tectonic Setup
4.1 Main Karakoram Thrust
4.2 Main Mantle Thrust
4.3 Main Boundary Thrust
5 Neighbor Embedding for Seismic Zonation
5.1 Manifold Learning
5.2 Seismicity of Pakistan
6 Bilinear Interpolation for Seismic Zonation
6.1 Directional Bilinear Interpolation Approach
6.2 Results and Interpration from Pakistan Bilinear-Based Interpolation
7 Conclusion
References
Optimizing UAV Path for Disaster Management in Smart Cities Using Metaheuristic Algorithms
1 Introduction
2 Related Study
2.1 Abbreviations
3 Mathematical Modeling and Metaheuristic Algorithm
3.1 Problem Statement
3.2 Path Optimization Using SFOA
4 Case Studies with Discussion
4.1 Scenario 1: General Environment
4.2 Scenario 2: Condense Obstacle Environment
4.3 Scenario 3: Maze Environment
4.4 Scenario 4: Dynamic Environment
4.5 Performance Evaluation
5 Conclusion
References
UAV-Based Rescue System and Seismic Zonation for Hazard Analysis and Disaster Management
1 Introduction
2 Tectonic Setting of Kalabagh Area
2.1 Salt Range and Trans Indus Range Thrust
2.2 Surghar Fault
3 Approaches for Seismic Zonation of Kalabagh
3.1 Kriging Methodology
3.2 Cubic Convolution
4 Conclusion
References
Multi-sensor Fusion Methods for Unmanned Aerial Vehicles to Detect Environment Using Deep Learning Techniques
1 Introduction
1.1 Deep Learning in Object Detection
2 Multiple Sensors Fusion with CNN
2.1 ADAS (Advanced Driver Assistance System)
3 Multi-sensor Fusion Algorithm
3.1 Sensor Fusion Using FusionNet
3.2 Sensor Information Fusion Technology
3.3 CNN and Regression
4 Conclusion
References
General Parametric of Two Micro-Concentrator Photovoltaic Systems for Drone Application
1 Introduction
2 File Basic Concepts for Solar 4 Concentrators
3 Simulation Results
4 Conclusion
References