Russia Develops AI System to Monitor Coastal Pollution

Russian experts have created a neural network designed to assess pollution levels along coastlines, according to the Ministry of Natural Resources and Environment, according to "TV BRICS".

The new technology has been successfully tested in the Kronotsky Nature Reserve in Kamchatka, a region where challenging terrain often hampers cleanup efforts.

Roman Korchigin, project leader and a staff member at the Kronotsky Reserve, explained that the initiative began with drone surveys capturing images of the coastline to identify areas heavily affected by waste.

To streamline the process, the team developed a neural network capable of analyzing coastal photographs and calculating the amount, volume, and weight of debris. The system also classifies waste into six categories: fishing nets, metal, rubber, large plastics, concrete, and wood.

With an accuracy rate exceeding 80 percent, the AI model promises to significantly enhance the speed and efficiency of environmental cleanup operations by enabling better resource planning and waste management. 

Previously, Sada El- Balad and TV BRICS international media network signed an agreement on joint activities to strengthen Egypt's position in the international media space and to widely inform the population of the country and the Middle East about the development of BRICS' nations.