Abstract: An AI-based system and method for feed monitoring in a land-based fish farm, where the fish farm has a tank containing fish and an effluent pipe that is coupled to the tank where uneaten feed pellets and non-pellet objects flow through the effluent pipe to an exit port. A feed camera is mounted to an effluent pipe for capturing a video feed having images of objects that traverse a field of view of the feed camera when each image is acquired. A special-purpose computer executes a pellet-tracking algorithm that employs a region of interest (ROI) proposal module, an ROI classification module, an ROI tracking module, and a trajectory classification module for at least counting uneaten feed pellets. The computer generates in real time a pellet count based on the pellet trajectories.

Abstract: Embodiments for an AI-based system and method for feed monitoring in a land-based fish farm are described where the system may include: a feed camera mounted to an effluent pipe for capturing a video feed having images of objects that traverse a field of view of the feed camera when each image is acquired; and a special-purpose computer that executes a pellet-tracking algorithm that employs a region of interest (ROI) proposal module, an ROI classification module, an ROI tracking module, and a trajectory classification module for at least counting uneaten feed pellets. In at least one embodiment, an object enhancer may be mounted to the effluent pipe opposite to and in the field of view of the feed camera to provide a background so that the objects in the acquired images have a definable perimeter.