Drones - Various Applications

Dragan Cvetković

• Publisher: IntechOpen
• Year: 2024
• Print ISBN:
  9780854661640
• eBook ISBN:
  9780854661633
• Topic: Technology & Engineering
• Index: Technology & Engineering

Although many believe that unmanned aerial vehicles or drones are a recent invention, unmanned flight has a rich history that goes all the way back to ancient times. The first systems that can be specified under the modern definition of unmanned aerial vehicles or drones include reconnaissance drones developed and deployed during the Cold War period. Today, such systems have evolved and can have different designs. In the last twenty years, many drones with different aerodynamic characteristics, flight endurance, methods and places of launch and acceptance, and even more diverse purposes have been developed. The achievements of modern science, technique, and technology, especially in the field of microelectronics and control systems, have made it possible to design and manufacture drones that are capable of performing controllable flight in a wide range of altitudes, speeds, and distances while performing complex and diverse tasks with almost the same efficiency as well as manned aircraft. This book provides a comprehensive overview of drone technology and applications with chapters on the detection and classification of drones, issues related to electric unmanned aerial vehicles, integrating drones into educational curricula, and the uses of different types of drones in various situations, among other topics.

Table of contents

• Drones-Various Applications
• Contents
• Preface
• Chapter1 DroneTechnologies and Applications
• Chapter2 Detection and Classification of Drones Using Radars, AI, and Full-Wave Electromagnetic CAD Tool
• Chapter3 Defining and Implementing Autonomy in Multi-Drone Systems
• Chapter4 Deformable Correlation Networks for Aerial ObjectTracking and Segmentation
• Chapter5 Modeling and Simulation of a Solar-Powered Quadcopter Using MATLAB
• Chapter6 Implementation of a Hybrid PowerTestbed Model of a Hybrid Electric Unmanned Aerial Vehicle
• Chapter7 Integrating Drones across the Curriculum at Stephen F. Austin State University
• Chapter8 Leveraging Programmable Educational Drones, Robots and AI for Learning STEM, Computational Thinking and Higher OrderThinking in Schools in Rural Villages
• Chapter9 Aerial Drones for Fire Disaster Response
• Chapter10 Depth Learning Methods for Bridges Inspection Using UAV
• Chapter11 Immune Neural Network Machine Learning of Autonomous Drones for Energy Efficiency and Collision Prevention
• Chapter12 Comparison and Transferability of Nitrogen Content Prediction Model Based inWinterWheat from UAV Multispectral Image Data
• Chapter13 Using Unmanned Aerial Systems and Deep Learning for Agriculture Mapping in Dubai Emirate