GhostNetBusters: Development of AI-based methods for detecting ghost nets on the seabed
ACRONYM
GhostNetBusters
Title
GhostNetBusters: Development of AI-based methods for detecting ghost nets on the seabed
General information
Background:
Various sources estimate that lost fishing gear is one of the major sources of plastic pollution in the world's oceans. Data from the World Wildlife Fund for Nature (WWF), for example, shows that ghost nets now account for 30% to 50% of the plastic waste in our oceans. The Food and Agriculture Organization of the United Nations (FAO) estimates that there are around 12,500 km of lost nets in the Baltic Sea alone. These so-called ghost nets are drifted by currents and continue to catch fish and other creatures until they sink to the seabed. In the Baltic Sea, ghost nets often get caught on underwater obstacles such as shipwrecks and become deadly traps for the creatures living there. They also contribute significantly to the production of microplastics.
Objective:
GhostNetBusters will use sidescan sonar data to detect objects, such as lost nets, on the seabed. The identification of objects and especially nets on sonar images requires some experience, as they are usually difficult to distinguish from the seabed and other structures on it. In areas with complex geological or biological structures, it is therefore necessary to visually verify the location of suspected targets, for example by using underwater cameras or by diving. The use of machine learning algorithms based on side-scan sonar data aims to significantly increase the efficiency of ghost net recovery by reducing the need for time-consuming manual verification.
Start
June, 2024
End
December, 2025
Funding (total)
-
Funding (GEOMAR)
156000
Funding body / Programme
-
Other
/ WT.SH
Coordination
Helmholtz-Zentrum für Ozeanforschung Kiel (GEOMAR), Germany
Contact
Partners
One Earth - One Ocean e.V. (OEOO), Germany
