Digital solutions, according to experts working on the new Nile initiative, can assist alter sustainability and promoting the UNSDGs. AI holds out hope for resolving issues such as food security in the region and the depletion of resources in the world's oceans.
Dubai: Dutch academics and the UN's Food and Agriculture Organization have begun a critical new project to improve the identification and assessment of fish species and populations in the Nile Basin using cutting-edge artificial intelligence technologies.
Increasing the collection of crucial data from fishing communities across the region might become a key instrument in the battle for sustainability and food security.
The initiative, which is supported by Wageningen University and Research in the Netherlands, is the latest development in a decades-long effort by FAO to assist countries in better identifying species for fisheries purposes, so that data on fish catches can be improved and the fishing industry can be improved, which began in the 1970s.
The technologies have arisen due to significant new research, aided by artificial intelligence, that could improve ocean conservation efforts, which are vital given the plight of many of the world's fish species. Species tracking using advanced technology can now be so detailed that the data can even detect the freshness of fish, which was once a costly and time-consuming operation carried out by observers aboard vessels. According to Edwin van Helmond, a fisheries expert at WUR's Wageningen Marine Research, the potential for using AI and other technologies to support fisheries management is enormous.
"The fact that detailed catch information can be collected through algorithms, without experts, makes data collection available in remote areas," he told Arab News. "Data can be sent or collected at a later stage or directly stored in a data cloud and made remotely available for experts."
He believes that, in the long run, such technology will tremendously assist food security, which is a critical concern in the Gulf region and sustainable natural resource management, which begins with the collection of appropriate data. The FAO puts algorithms to the test to see if they can compute sustainable harvest numbers without risking overexploitation.
"To perform a good assessment of the available resources, in this case, local fish stocks, you need good data," he said. "This includes detailed catch information by species, catch weight, and length frequencies.
"These variables form the input for any stock-assessment model. With these models, you can calculate sustainable harvest quantities without the danger of overexploitation, which equates to sustainable management of local fish stocks and long-term food security." FAO is now working to make the technology more accessible to the industry so that more people can profit from it, which will help the agency extend its data sets. Algorithms that can identify species, their locations, and detect changes would be built using detailed information on each species.