Marine litter is harmful to coastal and ocean environments for many reasons. Many devices have been developed in the last few years to recover as much litter as possible in ports and coastal areas. However, they usually employ a brute-force approach, leading to high energy and resource consumption. This is not negligible, considering their ecological goal. In this scenario, the deployment of Unmanned Surface Vehicles (USVs) to inspect the area of interest could complement the use of cleaning devices, adding relevant knowledge and intelligence to the context. Cleaning devices could be deployed or activated only where and when needed, leading to a more resource-aware approach. The contribution of this work is the development and deployment of an object detection neural network onto the H20mni-X USV, aiming to real-time detection of floating marine litter through an optical camera.
Real-Time Floating Marine Litter Detection on USV
Guido Lazzerini,Alberto Topini,Gherardo Liverani,Lorenzo Cecchi,Alessandro Ridolfi,Fausto Ferreira
Published 2024 in 2024 IEEE International Workshop on Metrology for the Sea; Learning to Measure Sea Health Parameters (MetroSea)
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- Publication year
2024
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2024 IEEE International Workshop on Metrology for the Sea; Learning to Measure Sea Health Parameters (MetroSea)
- Publication date
2024-10-14
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