Real-Time Beach Monitoring: Addressing Beach Safety with UAVs and Computer Vision

This study employs computer vision techniques to address beach safety concerns, with a focus on camera-equipped UAVs. The UAVs provide five channels of information that require preprocessing and image alignment to remove noise. The main challenges addressed are the identification of dangerous areas and people detection. For segmentation tasks, several lightweight models were evaluated, with YOLOv8-seg demonstrating superior efficiency and computational lightness across diverse conditions. In people detection, YOLOv8 also shows suitable results, identifying beach users, bathers, swimmers, and surfers. These solutions enable the use of UAVs for beach monitoring, providing a foundation for applications that evaluate danger for individuals on the beach. The results demonstrate the models' effectiveness and their capability to be deployed in real-time on board the UAVs.