Marine Environment
Marine environmental research is intensely focused on addressing pollution, particularly microplastics and macro-debris, and improving the efficiency of marine operations. Current efforts leverage advanced technologies like autonomous underwater and surface vehicles equipped with sensors and AI-powered image analysis (including deep learning models such as YOLOv5 and UNet) for detection, mapping, and quantification of marine debris and other features. These advancements, coupled with the development of specialized large language models for oceanographic data analysis, are significantly improving our understanding of marine ecosystems and informing conservation strategies. The resulting data and improved analytical capabilities are transforming both scientific understanding and practical applications in areas like pollution monitoring and resource management.
Papers
FathomGPT: A Natural Language Interface for Interactively Exploring Ocean Science Data
Nabin Khanal, Chun Meng Yu, Jui-Cheng Chiu, Anav Chaudhary, Ziyue Zhang, Kakani Katija, Angus G. Forbes
Composing Open-domain Vision with RAG for Ocean Monitoring and Conservation
Sepand Dyanatkar, Angran Li, Alexander Dungate