ANALYSIS AND DEEP LEARNING MODELING OF SENSOR-BASED OBJECT DETECTION DATA FOR ORGANIC MOTION DETERMINATION IN BOUNDED AQUATIC ENVIRONMENTS USING UNDERWATER POWERED SYSTEMS

摘要

Techniques for analysis and deep learning modeling of sensor-based object detection data for organic motion determination in bounded aquatic environments using underwater powered systems are described, including a light disposed substantially within a recess of a boundary wall, the light being disposed substantially underwater and configured to receive power using a conduit, and a spacer ring disposed circumferentially about an opening associated with the recess, the spacer ring being configured to secure the light within the recess and to provide a channel formed in the spacer ring, the channel being configured to receive the conduit.