Low-Altitude Drone Detection System Based on YOLOv8

To meet the rising demand for real-time detection and monitoring of low-altitude drones in industrial security, border surveillance, agriculture, and aerial photography, this study proposes a YOLOv8-based detection system. The optimized model, enhanced with data augmentation, achieves 80% [email protected], improving accuracy and generalization. A PyQt5-OpenCV visualization interface was developed to streamline YOLOv8’s complex configuration and reduce manual annotation efforts for large datasets. It simplifies training workflows and supports efficient data management. Experiments show the system boosts development efficiency and enhances YOLOv8’s Practicality in drone detection, promising wide applicability.