Autonomous Aerial Monitoring Framework for Floating Waste Detection and Geolocation

The conservation of aquatic ecosystems is essential to protect biodiversity, sustain ecological balance, and safeguard human health, particularly as pollution levels continue to rise. Floating plastic debris presents a significant threat to these environments, impacting marine life and degrading water quality. Unmanned Aerial Vehicles (UAVs) have emerged as a scalable and cost-effective alternative for detecting and tracking floating waste across large water bodies. This study presents a UAV framework that performs live detection and geolocation of floating debris in parallel with flight operations. The system integrates DJI Mobile SDK (MSDK) and Robot Operating System (ROS) to enable autonomous navigation, telemetry acquisition, and live video streaming. A YOLOv8 object detection model, trained on a combination of public and custom datasets, performs inference on the video stream to identify debris, while geolocation is calculated from synchronized GPS and IMU data published via ROS. Field trials demonstrated high detection precision at altitudes up to 7.5 meters, with latency inference times under 1.5 seconds per frame and stable performance across sunny and cloudy conditions. The geolocation pipeline achieved consistently accurate positioning, with detections closely matching their actual locations in satellite imagery. The proposed framework is modular and compatible with multiple UAV configurations, allowing integration across different platforms with available telemetry and video streams. It also supports future extensions such as adaptive path planning and coordination with collection systems, including the deployment of autonomous surface vehicles to retrieve detected waste. The results demonstrate the potential of the system as a reliable and adaptable solution for autonomous aquatic waste monitoring.