Computer Vision and Edge Computing Technologies for the Drone IndustryКНИГИ » АППАРАТУРА
Название: Computer Vision and Edge Computing Technologies for the Drone Industry Автор: Imdad Ali Shah, Noor Zaman Jhanjhi Издательство: IGI Global Год: 2025 Страниц: 386 Язык: английский Формат: pdf (true), epub Размер: 23.1 MB
Computer vision powers critical functions like object detection, classification, and tracking while the drone is airborne. Without computer vision, drones would be unable to autonomously recognize and respond to features like buildings, trees, and diverse terrains. Advances in computer vision enable drones to effectively perform surveillance and security tasks. They analyze visual data to identify suspicious activities, unauthorized access, and enhance threat detection, thus improving decision-making and mission success rates. Computer vision technology is pivotal in developing autonomous navigation and obstacle avoidance in drones.
Computer Vision and Edge Computing Technologies for the Drone Industry explores the enhancement of the autonomous capability of drones for operations in dense forests, mountainous regions, or urban settings. It highlights the abilities of computer vision algorithms to enable drones to navigate hazardous environments without human intervention, enabling autonomous flight and collision avoidance. Covering topics such as drone surveillance, traffic management, and industrial applications, this book is an excellent resource for computer scientists, aviation scientists, industrial professionals, professionals, researchers, scholars, academicians, and more.
CV and ML-enabled drones with capabilities such as autonomous navigation, object recognition in real time, weather monitoring etc. are transforming industries today. This chapter discusses the incorporation of edge computing for real-time processing, scalable and powerful AI models, and learning-based optimization. This showcases promising developments in autonomous and swarm technologies while addressing challenges like energy limitations and ethical issues. The chapter demonstrates the ability of AI-powered drones to innovate fields such as agriculture, logistics and disaster management by linking scientific progress with real-world applications.
Swarm intelligence in drone systems means that swarms of drones coordinate with local interactions and simple rules to effectively achieve tasks. This, following the example of ants, bees, and birds, enables drones to fly without a central controller and can therefore respond better to complex environments. In a search and rescue mission following an earthquake, instead of employing a single drone to sweep a vast region, a swarm of drones can fan out, communicate in real time, and cover a wider region in a shorter period. It has been proved in research that swarm-intelligent drones can navigate around obstacles and locate survivors in a shorter time compared to conventional means. This ability to organize in a decentralized manner makes them very applicable in agriculture, with drones flying in fields and dropping fertilizers directly to where they are needed.
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Computer Vision and Edge Computing Technologies for the Drone Industry 
