Analysis and deep learning modeling of sensor-based object detection data in bounded aquatic environments

A system, comprising:

• a database configured to store data associated with an image captured by a sensor housed with another sensor in a structure fixed to a side of a bounded aquatic environment and electrically coupled to a light unit disposed below a waterline of a body of water and being configured to provide power to the sensor and the another sensor, the sensor being disposed above the waterline of the body of water and configured to capture the image as a side view to identify organic motion or inorganic motion above the waterline of a body of water and the another sensor being disposed below the waterline of the body of water and being configured to capture another image as a side view to identify organic motion or inorganic motion below the waterline of the body of water, being disposed proximate to the waterline of the body of water, the sensor and the another sensor being configured to capture the image above the waterline and below the waterline;
• and
• a processor configured to process data generated from the image captured by the sensor and other data generated from the another image captured by the another sensor, the sensor and the another sensor being housed in a structure electrically coupled to the light unit disposed below the waterline of the body of water, to convert the image into data, the data being digitally encoded by a processor in electronic communication with the sensor, to evaluate the data to separate background data from foreground data to identify foreground features using one or more deep learning algorithms trained against model data to further identify a person from a non-person object, to generate tracking data from the data after the background data is removed, the tracking data being evaluated to determine whether a head or a body are detected by comparing the tracking data to classifier data, to track the head or the body relative to the waterline if the head or the body are detected in the tracking data, and to determine a state associated with the head or the body, if the head or the body 1s detected, the state being associated with state data, the state data being used to determine a drowning state and generate an alert external to the bounded aquatic environment if the drowning state is determined.

A non-transitory computer readable medium having one or more computer program instructions configured to perform a method, the method comprising:

• capturing an image from a sensor disposed proximate to a waterline, the sensor being housed with another sensor in a structure fixed to a side of a bounded aquatic environment and electrically coupled to a light unit disposed below the waterline and being configured to provide power to the sensor and the another sensor, the sensor being disposed above the waterline and configured to capture the image as a side view of the bounded aquatic environment to identify organic motion or inorganic motion above the waterline and the another sensor being disposed below the waterline and being configured to capture another image as another side view of the bounded aquatic environment to identify organic motion or inorganic motion below the waterline;
• converting the image and the another image into data, the data being digitally encoded by a processor in electronic communication with the sensor;
• evaluating the data to separate background data from foreground data to identify foreground features using one or more deep learning algorithms trained against model data to further identify a person from a non-person object;
• generating tracking data from the data after the background data is removed, the tracking data being evaluated to determine whether a head or a body are detected by comparing the tracking data to classifier data;
• tracking the head or the body relative to the waterline if the head or the body are detected in the tracking data;
• and
• determining a state associated with the head or the body, if the head or the body is detected, the state being associated with state data, the state data being used to determine a drowning state and generate an alert external to the bounded aquatic environment if the drowning state is determined.