Updated Project: Our project develops an innovative shark tagging and satellite-based monitoring system that combines in-situ sensing with remote ocean data. The tag is designed for low-power operation and environmental adaptability, measuring mov…
Updated Project: Our project develops an innovative shark tagging and satellite-based monitoring system that combines in-situ sensing with remote ocean data. The tag is designed for low-power operation and environmental adaptability, measuring movement, depth, temperature, and water color to detect feeding and migration patterns. By integrating these data with satellite indices such as sea surface temperature, phytoplankton concentration, and ocean eddies, we can accurately map shark habitats and ecosystem interactions. This approach supports sustainable marine management, predictive modeling of shark presence, safer fishing practices, and long-term ocean conservation through the integration of space technology and ocean sensing.
AI tools were used only to enhance writing clarity, refine code, and speed up idea development—not for data generation or scientific analysis.
ChatGPT supported the improvement of technical documentation, while all scientific concepts and interpretations were developed and validated by the project team. AI suggestions were applied to optimize formatting and syntax in our Python data-fusion pipeline, with all outputs manually reviewed.
All plots and maps were generated using our own Python scripts and NASA datasets. A single AI-generated illustration was included only to represent the conceptual shark tag design and was clearly labeled. No synthetic data were used; all datasets were sourced from NASA’s open repositories via the earthaccess API.
