Abstract: A net monitoring system, including: a plurality of net monitoring devices, each net monitoring device including: a housing; a plurality of tensioning arms, each tensioning arm reversibly extendable through the housing and configured to reversibly secure to a net, each tensioning arm including a force sensor configured to generate a tension signal indicative of a tension applied to the corresponding tensioning arm; a tensioning mechanism configured concurrently retract the plurality of tensioning arms into the housing; an impulse generating device, configured to generate an impulse responsive to a command; and a communications device configured to receive the tension signals from the plurality of force sensors, and transmit the tension signals through water; and a controller, configured to: command at least one of the plurality of net monitoring devices to generate the impulse; receive the tension signals responsive to the command to generate the impulse; and determine, based on the received tension signals, a

Abstract: Methods, systems, and apparatus, including computer programs encoded on computer-storage media, for microplastic removal. In some implementations, a method can include controlling a camera to capture one or more images of plastic in water; providing the one or more images to a machine learning model trained to detect plastic; obtaining output from the machine learning model indicating one or more items of plastic; and controlling one or more acoustic transducers to move the one or more items of plastic.

Abstract: Methods, systems, and apparatus, including computer programs encoded on computer-storage media, for automated underwater camera system control for aquaculture systems. An underwater camera system includes (i) a line on which the underwater camera system is mounted, the line detachably affixed to a feeder that provides feed for aquatic livestock, (ii) a sensor manager, (iii) one or more sensors that are managed by the sensor manager, (iv) a line navigation controller, and (v) a first actuator for controlling a distance between the feeder and the underwater camera system. The one or more sensors obtain sensor data and the line navigation controller of the underwater camera system determines a distance to position the underwater camera system beneath the feeder to obtain additional sensor data. The line navigation controller transmits a first message to the first actuator to position the underwater camera system at the determined distance beneath the feeder.

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 obtaining drone-based water measurements. One of the methods includes receiving, by a drone management system that controls a drone that is configured to collect water samples, data from a simulator that generates simulation data associated with a body of water; receiving, by the drone management system, an indication that the drone is available to collect one or more water samples from the body of water; determining, by the drone management system and based on the data from the simulator, one or more locations associated with the body of water at which the drone is to collect one or more respective water samples; and; transmitting, by the drone management system, the one or more locations associated with the body of water to the drone.

Abstract: Methods, systems, and apparatus, including medium-encoded computer program products, for adjusting an aquaculture camera mounting system. A current combined field of view of two or more cameras that are mounted on an adjustable camera mounting structure in an environment can be determined based upon a current configuration of the adjustable camera mounting structure. A target field of view for the two or more cameras that are mounted on the adjustable camera mounting structure can be determined. Based at least on the field of view target and the current combined field of view, an adjustment parameter for the adjustable camera mounting structure can be determined. The adjustable camera mounting structure can be adjusted according to the adjustment parameter to provide a field of view in accordance with the field of view target.

Abstract: Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, that validate the synchronization of controllers in an aquaculture environment. One of the methods includes an image processor that receives images generated by a first image generating device that includes a light filter that is associated with light of a particular light frequency while an aquaculture environment was illuminated with light. Based on the image that was generated by the first image generating device, the image processor determines whether the intensity value of the light frequency in the image satisfies a threshold value. Based on determining whether the intensity value of the light frequency in the image satisfies the threshold value, the image processor determines whether the aquaculture environment was illuminated with light of the particular light frequency when the image was generated.

Abstract: In one aspect, there is provided a moisture detection system that includes: a moisture detection unit including: a moisture sensor configured to obtain a measurement that indicates an amount of moisture, and a Radio Frequency Identification (RFID) module coupled to the moisture sensor through multiple wires, where the RFID module includes an antenna and is configured to wirelessly transmit a telemetry message based on the measurement from the moisture sensor through the antenna and is further configured to wirelessly receive energy for powering the moisture detection unit through the antenna; and a control unit communicatively coupled to the moisture detection unit, where the control unit is configured to wirelessly receive the telemetry message from the RFID module and process the telemetry message to determine the amount of moisture measured by the moisture sensor.

Abstract: Methods, systems, and apparatus, including computer programs encoded on computer storage media, for estimating wave properties of a body of water. A computer-implemented system obtains measurement data for a duration of time from an inertial measurement unit (IMU) onboard an underwater device, generates model input data based on at least the measurement data obtained at the plurality of time points, and processes the model input data to generate model output data indicating one or more wave properties using a machine-learning model. The system further determines, based on at least the one or more wave properties, whether the device is safe to be deployed.

Abstract: Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, that validate the synchronization of controllers in an aquaculture environment. One of the methods includes an image processor that receives images generated by a first image generating device that includes a light filter that is associated with light of a particular light frequency while an aquaculture environment was illuminated with light. Based on the image that was generated by the first image generating device, the image processor determines whether the intensity value of the light frequency in the image satisfies a threshold value. Based on determining whether the intensity value of the light frequency in the image satisfies the threshold value, the image processor determines whether the aquaculture environment was illuminated with light of the particular light frequency when the image was generated.

Abstract: Methods, systems, and apparatus, including computer programs encoded on computer storage media, for estimating wave properties of a body of water. A computer-implemented system obtains measurement data for a duration of time from an inertial measurement unit (IMU) onboard an underwater device, generates model input data based on at least the measurement data obtained at the plurality of time points, and processes the model input data to generate model output data indicating one or more wave properties using a machine-learning model. The system further determines, based on at least the one or more wave properties, whether the device is safe to be deployed.

Abstract: Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, that validate the synchronization of controllers in an aquaculture environment. One of the methods includes an image processor that receives images generated by a first image generating device that includes a light filter that is associated with light of a particular light frequency while an aquaculture environment was illuminated with light. Based on the image, the image processor determines whether the intensity value of the light frequency in the image satisfies a threshold value. Based on determining whether the intensity value of the light frequency in the image satisfies the threshold value, the image processor determines whether the aquaculture environment was illuminated with light of the particular light frequency when the image was generated. The image processor provides an indication of whether the aquaculture was illuminated with light of the particular frequency when the image was generated.

Abstract: Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, that validate the synchronization of controllers in an aquaculture environment. One of the methods includes an image processor that receives images generated by a first image generating device that includes a light filter that is associated with light of a particular light frequency while an aquaculture environment was illuminated with light. Based on the image that was generated by the first image generating device, the image processor determines whether the intensity value of the light frequency in the image satisfies a threshold value. Based on determining whether the intensity value of the light frequency in the image satisfies the threshold value, the image processor determines whether the aquaculture environment was illuminated with light of the particular light frequency when the image was generated.