Pubbl/distr/stampa |
Cham, Switzerland : , : Springer International Publishing, , [2022]
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Descrizione fisica |
1 online resource (294 pages)
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Disciplina |
629.1326
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Collana |
Studies in Computational Intelligence
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Soggetto topico |
Drone aircraft - Control systems
Drone aircraft - Design and construction
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ISBN |
3-030-97113-9
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Formato |
Materiale a stampa |
Livello bibliografico |
Monografia |
Lingua di pubblicazione |
eng
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Nota di contenuto |
Intro -- 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.
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Record Nr. | UNINA-9910558490603321 |