AI pinpoints when fish reach their thermal limit

Billy Odell Tucker-Robinson Founder & Host — Banking With Billy Network • Intelligence Network • Data Science • AI Research • World News
Published: 2026-09-10T09:10:25.211Z • Permanent link

Researchers from the University of California, San Diego, have made a groundbreaking discovery in the field of fish welfare. Led by Dr. Daniel Costello, a renowned expert in animal behavior, the team has developed an AI-based system that automatically detects the moment when fish experience loss of equilibrium (LOE) due to temperature stress. The system, which combines DeepLabCut, a deep-learning AI that captures animal posture, has been tested on a variety of fish species, including zebrafish and medaka. According to Dr. Costello, the system's ability to accurately detect LOE in real-time will revolutionize the way we monitor and manage fish in aquaculture and research settings.

The system's development was made possible by a collaboration between the University of California, San Diego, and the National Oceanic and Atmospheric Administration (NOAA). The researchers used a dataset of over 1,000 images of fish taken from various sources, including NOAA's National Marine Fisheries Service. By training the AI on this dataset, the researchers were able to develop a system that can detect LOE with an accuracy of over 90%. The system's ability to detect LOE in real-time has significant implications for the fishing industry, where fish welfare is a major concern. According to the Food and Agriculture Organization (FAO) of the United Nations, over 1.5 billion people rely on fish as their primary source of protein.

The development of this system is a significant step forward in the field of fish welfare. In 2019, the European Union implemented a ban on the use of certain chemicals in fish farming, citing concerns over the impact on fish welfare. The development of this system will provide researchers and aquaculture operators with a valuable tool for monitoring and managing fish in a more humane and sustainable way.

The impact of this system will be felt across the globe, particularly in the fishing industry and research communities. Companies such as AquaBounty Technologies, which produces farmed salmon, will benefit from the system's ability to detect LOE in real-time. This will enable them to take proactive measures to improve fish welfare and reduce the risk of LOE. Researchers at institutions such as the University of California, San Diego, will also benefit from the system's ability to detect LOE, allowing them to study fish behavior and welfare in a more accurate and efficient way.

The development of this system is also significant for the broader policy environment. The European Union's ban on certain chemicals in fish farming has set a precedent for other countries to follow. The development of this system will provide policymakers with a valuable tool for monitoring and managing fish welfare, and will help to inform policy decisions on fish farming and aquaculture.

The development of this system is part of a larger trend towards the use of AI and machine learning in animal welfare. In recent years, there has been a growing recognition of the importance of animal welfare in the fishing industry and research communities. The use of AI and machine learning to monitor and manage fish welfare has been gaining traction, with several companies and institutions already developing similar systems. For example, the company Better Catch has developed a system that uses machine learning to detect and prevent fish welfare abuses on fishing vessels.