The shrimp farming industry faces significant challenges in monitoring and ensuring the welfare of farmed animals. Operators must regularly handle the shrimp to weigh them and check their condition, causing stress and reducing animal welfare. Additionally, water turbidity in traditional pond systems makes it difficult to detect symptoms of stress or disease in farmed shrimp. In response to these challenges, the ShrimpWiz project, led by the Alfred Wegener Institute (AWI) in collaboration with Oceanloop, aims to revolutionize shrimp farming through the use of AI-based computer vision technology.
The ShrimpWiz project has developed a system that can count shrimp in images and accurately determine their length in real time, under realistic farming conditions. The first prototype of the system has been successfully tested at Oceanloop’s research and development farm in Kiel, Germany. An advanced smartphone installed above the water surface takes photos of the shrimp every minute and transmits the data to a local server. Computer vision algorithms then analyze the images to count individual shrimp and measure their length with 95 percent accuracy. The system has also been able to detect visual signs of stress in the animals, a breakthrough in improving animal welfare in shrimp farming.
Unlike traditional pond systems with high water turbidity, Oceanloop’s clear water systems are ideal for computer vision technology. The use of clear water technology is seen as crucial by Dr. Stephan Ende, the project coordinator at AWI, in ensuring animal welfare in intensive aquaculture. By combining computer vision software with clear water technology, the ShrimpWiz project aims to provide accurate and non-invasive monitoring of animal welfare and productivity in shrimp farming, 24 hours a day, 7 days a week. This technology, along with the Early Welfare Alert software developed by the consortium, could pave the way for more objective welfare labeling in the shrimp industry of the future.
The development of AI-based software not only improves animal welfare but also increases farming efficiency in the shrimp industry. The technology offers opportunities for the digitalization of indoor shrimp farming, which is essential for meeting today’s retail price levels. Dr. Ende emphasizes the importance of proving the technical feasibility of alternative solutions to meet the growing demand for sustainable and welfare-compliant shrimp farming among customers and stakeholders.
In conclusion, the ShrimpWiz project represents a significant step forward in revolutionizing shrimp farming through the use of AI-based computer vision technology. By providing accurate and non-invasive monitoring of animal welfare and productivity, the project aims to improve animal welfare, increase farming efficiency, and meet the demands for sustainable and welfare-compliant shrimp farming. With the success of the prototype at Oceanloop’s research and development farm, the consortium is optimistic about the future of shrimp farming with the implementation of AI-based software.
