earticle

한국어

Integrating unmanned aerial vehicles (UAVs) and computer vision techniques has contributed to enhancing the accuracy and speed of monitoring for surveillance and warning systems. This paper presents an application of human detection in a beach-warning-system using drone-captured images and YOLO. Our research focuses on detecting critical objects and anomalies on the beach, such as people or buoys. By leveraging the real-time capabilities of YOLO, our system processes highresolution drone images to swiftly identify and classify objects, enabling rapid responses in emergencies. We conducted evaluations using several methods to validate the model's effectiveness. The results showcase its potential to enhance beach warning systems and quick warning of dangerous situations.