Real-Time UAV Trash Monitoring System

Abstract

This study proposes a marine trash detection system based on unmanned aerial vehicles (UAVs) and aims to replace manpower with UAVs to detect marine trash efficiently and provide information to government agencies regarding real-time trash pollution. Internet technology and computer-machine interaction were applied in this study, which involves the deployment of a marine trash detection system on a drone's onboard computer for real-time calculations. Images of marine trash were provided to train a modified YOLO model (You Look Only Once networks). The UAV was shown to be able to fly along a predefined path and detect trash in coastal areas. The detection results were sent to a data streaming platform for data processing and analysis. The Kafka message queuing system and the Mongo database were used for data transmission and analysis. It was shown that a real-time drone map monitoring station can be built up at any place where mobile communication is accessible. While a UAV is automatically controlled by an onboard computer, it can also be controlled through a remote station. It was shown that the proposed system can perform data analysis and transmit heatmaps of coastal trash information to a remote site. From the heatmaps, government agencies can use trash categories and locations to take further action.