Autonomous and Adaptive Subsea Sensor for Optical Measurement of Very-Near Seafloor Fluid Flows

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9360530 Owen This research program involves an autonomous and adaptive subsea sensor that measures very-near seafloor fluid flows, suspended particulates, and momentum exchanges in the coastal environment. We use computer-aided speckle interferometry to deduce a two- dimensional flow field from particulate speckle patterns. Particulates are sampled through long-distance microscopy. The sensor has a temporal resolution greater than 33 ms over sub- millimeter to meter scales. The system includes a laser, microprocessor, video cameras, optics, and a recorder. Power requirements are low--the sensor operates autonomously for months. We conserve power with neural networks--the sensor monitors environmental changes and samples accordingly.