SBIR Phase I: Scaling Ocean Observation with Millions of In Situ Sensors

The broader impact/commercial potential of this SBIR Phase I project is to benefit from a global network of proposed sensors continuously monitoring the world’s oceans at unprecedented scale. The need for better ocean sensing will benefit weather forecasting and fisheries management. Predicting hurricane strength is difficult when the heat content of the ocean is not measured at high resolution. In addition, many fisheries are showing signs of change as fish migrate towards the poles. This project will provide ocean temperature data to weather forecasters, as well as information about commercially important fish species. Applications include academia, government, fisheries, maritime shipping, energy, and the military. This SBIR Phase I project will scale ocean observation by developing the technology required to enable deployment millions of inexpensive smart platforms (surface drifters and profiling buoys) using acoustics, motion sensors and AI to detect marine animals, track vessels, and measure oceanographic conditions. This project will develop and test low power, efficient artificial intelligence (AI) algorithms to detect boats on a bottom-stationing profiler. This bottom-stationing profiler is designed to rest on the bottom to hold station, and then rise to the surface to transmit boat detection information over a satellite to a cloud computing system. This project includes a demonstration of monitoring boat visitation rates at artificial reefs in Florida. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.