Autonomous Uncrewed Systems (UxS) for Identifying Microplastic & Marine Debris

Intelligence Aqua Bot: An Autonomous Solution for Real-Time Marine Plastic Debris Including Microplastics Detection and Cleanup Using Deep Learning

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Researchers developed the Intelligence Aqua Bot, an autonomous AI-driven underwater system capable of real-time identification and cleanup of marine plastic debris including microplastics, using deep learning to address the growing threat of plastic pollution to marine biodiversity and human health.

Advancing Environmental Surveillance: The Role of Microplastic Robotics in Modern Ecosystem Monitoring

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Researchers explored how robotic systems equipped with sensors and autonomous capabilities could advance environmental surveillance of micro and nanoplastic pollution, enabling real-time, large-scale ecosystem monitoring that outperforms traditional manual sampling in coverage and precision.

Exploring the Potential of Autonomous Underwater Vehicles for Microplastic Detection in Marine Environments: A Review

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This review explores how autonomous underwater vehicles equipped with sensors could detect microplastics directly in the ocean, rather than relying on labor-intensive water sampling. Current detection methods are slow and expensive, making real-time monitoring difficult. Advances in onboard sensing technology could dramatically improve our understanding of where microplastics concentrate in marine environments.

Optical RGB-IR Classification Method for a Drone-Mounted Microplastics Detector: Plastic vs. Metal Discrimination

Remote Sensing Application for Monitoring Microplastic in Aquatic Environments

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Researchers reviewed how satellite imagery, UAVs, radar, and machine learning can detect and track micro- and macroplastics in rivers, lakes, and oceans far more efficiently than traditional nets and trawls. Better remote monitoring tools are essential for understanding where plastic pollution concentrates and how to prioritize cleanup efforts before it reaches the food chain.