Interesting Courses - Unmanned Aircraft System and Technology Engineering

UE477

UAV Applications in Disaster Response

Unmanned aerial vehicle applications for disaster response and emergency management, flight planning under safety and operational constraints, real-time situational mapping, use of thermal imaging sensors for search and localization, support of search and rescue operations, coordination with emergency management systems and agencies, utilization of unmanned aerial vehicle data for decision support in critical missions.

UE476

LiDAR and Advanced Aerial Surveying

Applications of unmanned aerial vehicles integrated with LiDAR technology for advanced surveying, operating principles of laser ranging sensors, integration of inertial measurement units and global navigation satellite systems, flight planning for controlled point density, LiDAR data calibration and quality assessment, point cloud processing and management, generation of high-quality spatial datasets for surveying, land management, and environmental applications.

UE475

UAV Applications in Construction

Unmanned aerial vehicle applications in construction and structural inspection, inspection of buildings, bridges, and transportation infrastructure, construction progress monitoring and structural defect detection, safe inspection flight techniques, construction site mapping, image processing and three-dimensional model generation, analysis of structural anomalies, preparation of inspection reports aligned with construction industry standards.

UE466

Internet of Things

The meaning of the internet of things, opportunities, challenges, and obstacles, application of related technology, design tools in logical and physical, creating and deploying includes considerations regarding security and privacy.

UE464

Edge Artificial Intelligence and Real-Time Processing for UAV

Principles and development of artificial intelligence systems for edge deployment under constraints of computation, memory, and power, streaming data processing, latency and throughput budgeting, real-time system concepts including deadlines, jitter, and worst-case execution time, model optimization and deployment techniques including quantization, pruning, and distillation, runtime mechanisms for system robustness including monitoring and fallback strategies.

UE463

Autonomous UAV and Artificial Intelligence

Autonomy systems of small unmanned aerial vehicles, mission and flight planning, navigation modes, state estimation, and control loops, safety and failsafe mechanisms, telemetry communication and ground control interfaces, parameter configuration, system state monitoring, and performance evaluation using system data and logs, simulation of autonomous system behavior, artificial intelligence concepts for enhanced autonomy including perception-based decision support, obstacle avoidance, landing and target localization assistance, system health monitoring, and anomaly detection.

UE382

Drone Startup

Creation and early-stage development of unmanned aerial vehicle startup ventures, identification of business opportunities and problem validation, development of unmanned aerial vehicle–based products and services under technical, regulatory, and operational constraints, customer analysis and value proposition design, business models and revenue structures, cost estimation and feasibility assessment, regulatory frameworks and legal considerations, risk management specific to unmanned aerial vehicle businesses, value creation and viability within the unmanned aerial vehicle startup ecosystem.

UE374

UAV Applications in Monitoring System

Unmanned aerial vehicle applications for monitoring and surveillance systems across multiple domains, environmental monitoring, infrastructure and asset monitoring, safety and security applications, risk-prone areas, industrial operations, agricultural systems, and smart city environments, end-to-end design of unmanned aerial vehicle–based monitoring systems, platform and sensor selection, mission planning, continuous and temporal data acquisition, data processing and analysis, presentation of monitoring results for decision support.

UE373

UAV Applications in Architecture

Unmanned aerial vehicle applications for architecture and the built environment, data acquisition techniques for spatial documentation, generation of three-dimensional mesh and textured models, integration of spatial data with architectural software platforms, workflows for accurate spatial data production, applications for architectural design, building condition assessment, and architectural conservation.

UE372

UAV Applications in Agriculture

Unmanned aerial vehicle applications for precision agriculture, crop health assessment and field analysis, detection of plant diseases and anomalies, sensor selection for agricultural applications, multispectral data acquisition, vegetation index computation, agricultural data interpretation for farm management planning and sustainable crop productivity.

UE371

UAV Imaging for Media, Entertainment and Filmmaking

Applications of unmanned aerial vehicles in creative media and filmmaking, principles of aerial cinematography using unmanned aerial vehicles, cinematic camera movement techniques, shot design and visual composition, camera configuration for cinematic image quality, post-production and image processing workflows, visual storytelling through aerial perspectives.

UE362

Computer Vision and Deep Learning for UAV Perception

Fundamentals of computer vision and deep learning for perception tasks, principles of image formation and camera models, classical computer vision concepts including feature representation, image matching, and basic object tracking, modern deep learning approaches for visual perception including convolutional neural networks, transfer learning, and data augmentation, evaluation metrics for spatial perception performance, model robustness considerations, and deployment of perception models on edge and embedded systems in unmanned aerial vehicle contexts.

UE361

Introduction to Artificial Intelligence and Machine Learning for UAV

Machine learning workflows, problem formulation and data preparation, dataset partitioning for training, validation, and testing, fundamental machine learning models including linear regression, logistic regression, k-nearest neighbors, and decision trees, model evaluation metrics including accuracy, precision, recall, and receiver operating characteristic analysis, overfitting phenomena and regularization techniques, cross-validation methods, basic feature engineering and pipeline construction, principles of unsupervised learning including clustering and principal component analysis, foundational concepts of deep learning.

UE325

Embedded Systems and ROS for Autonomous UAV

System and data integration for unmanned aerial vehicles using MAVLink, MAVROS, and ROS2, integration of external sensors including ultrasonic sensors, inertial measurement units, and cameras, ROS software development for data acquisition, processing, and offboard control in simulation environments, fundamental electronic circuit and printed circuit board design, firmware development on STM32 microcontrollers, integration of embedded systems, ROS-based systems, and PX4 autopilot platforms in operational contexts.

UE256

Drone Pilot

Preparation of knowledge and competencies for unmanned aerial vehicle pilot certification, aviation laws and regulations for unmanned aircraft operations, operational procedures for unmanned aerial vehicles, flight safety and risk assessment, documentation and regulatory compliance requirements, scope and requirements of unmanned aerial vehicle pilot examinations and certification under official regulatory standards.