Buoy Detection

Buoy detection research focuses on improving the accuracy and reliability of detecting and utilizing data from buoys across various applications, from oceanographic monitoring to aquaculture management. Current research employs machine learning algorithms, including deep learning models like convolutional neural networks and YOLO variants, and Gaussian processes, to enhance buoy data acquisition and interpretation, often addressing challenges like data gaps and harsh environmental conditions. These advancements are significant for improving the accuracy of ocean models, enabling more efficient aquaculture practices, and enhancing early warning systems for natural hazards like tsunamis by leveraging alternative data sources to supplement or replace traditional buoy networks.