Abstract: Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for controlling a remotely operated vehicle (ROV) for performing an underwater task. One apparatus includes a watertight housing; a mounting hardware that attaches the watertight housing to the ROV; one or more sensors in the watertight housing, the one or more sensors configured to generate sensor data that is associated with an underwater task; and one or more processors in the watertight housing, the one or more processors configured to: receive the sensor data from the one or more sensors; generate a navigation plan for the ROV using the sensor data; determine, using the navigation plan, control instructions configured to control the ROV to perform the underwater task; and provide the control instructions to an interface of the ROV configured to communicate with the apparatus.

Abstract: Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for determining turbidity of water using machine learning. One of the methods includes obtaining, by a camera, an image of water; detecting, using a blob detector, a plurality of blobs in the image that represent particles suspended in the water; determining a distribution of the plurality of blobs; determining, from the distribution of the plurality of blobs, a measurement associated with turbidity of the water; and providing a signal associated with the measurement.

Abstract: Methods, systems, and apparatus, including medium-encoded computer program products, for receiving outputs from a plurality of models that are each informed by real-time data provided by one or more sensors that are present in an aquaculture environment. An input is generated for an algorithmic music composer for algorithmically composing music that reflects multiple current conditions within the aquaculture environment, based at least on the received outputs from the plurality of models. The input is provided to the algorithmic music composer to algorithmically compose the music that reflects the multiple current conditions within the aquaculture environment.

Abstract: Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for determining turbidity of water using machine learning. One of the methods includes obtaining, by a camera, an image of water; detecting, using a blob detector, a plurality of blobs in the image that represent particles suspended in the water; determining a distribution of the plurality of blobs; determining, from the distribution of the plurality of blobs, a measurement associated with turbidity of the water; and providing a signal associated with the measurement.

Abstract: Methods, systems, and apparatus, including computer programs encoded on computer-storage media, for automatic object detection for underwater cameras. In some implementations, an underwater camera captures many images which are obtained by a control unit. The control unit can detect one or more contours within a captured image based on values representing pixels of the image, generate a representation of the image based on the detected contours, provide the representation to a model that is trained to classify an input image as including a net or as not including a net, and perform an action based on classifying the image as including a net.