A device for counting animal traffic in an aquatic animal passage system includes chutes positioned across the aquatic animal passage system and a sensor positioned to sense an animal moving through or in the aquatic animal passage system. The chutes and the aquatic animal passage system are formed with precast concrete segments and may include a protective liner or coating coupled to their outer surface to protect animals from contacting the outer surface of the precast concrete segments. The sensors may be integrated with the precast concrete segments forming the chutes. Smart concrete segments may be employed as transducers to create an electric field in the chutes, with impedance sensors coupled to the transducers being responsive to changes to the electric field in the chutes caused by passing animals.

A device for counting animal traffic in an aquatic animal passage system includes chutes positioned across the aquatic animal passage system and a sensor positioned to sense an animal moving through or in the aquatic animal passage system. The chutes and the aquatic animal passage system are formed with precast concrete segments and may include a protective liner or coating coupled to their outer surface to protect animals from contacting the outer surface of the precast concrete segments. The sensors may be integrated with the precast concrete segments forming the chutes. Smart concrete segments may be employed as transducers to create an electric field in the chutes, with impedance sensors coupled to the transducers being responsive to changes to the electric field in the chutes caused by passing animals.

Methods and systems, including computer implemented methods and systems, for creating groups of embryonic fish or juvenile aquatic organisms from a pool based on predicted growth potential or feed efficiency wherein whole-body metabolic rate of each individual in the pool is measured and individuals are sorted into one of two or more containers based on relative whole-body metabolic rate. The embryonic fish or juvenile aquatic organisms with the highest whole-body metabolic rate are predicted to grow significantly more than those with the lowest whole-body metabolic rate.

A fish monitoring system deployed in a particular area to obtain fish images is described. Neural networks and machine-learning techniques may be implemented to periodically train fish monitoring systems and generate monitoring modes to capture high quality images of fish based on the conditions in the determined area. The camera systems may be configured according to the settings, e.g., positions, viewing angles, specified by the monitoring modes when conditions matching the monitoring modes are detected. Each monitoring mode may be associated with one or more fish activities, such as sleeping, eating, swimming alone, and one or more parameters, such as time, location, and fish type.

A system for monitoring marine animals includes a monitoring tag attachable to a marine animal. The monitoring tag includes a processor, a memory coupled to the processor, at least one communication interface, and at least one sensor. The processor is configured to store readings from the at least one sensor in the memory. The system also includes at least one communication receiver having a processor, a memory coupled to the processor, and at least one communication interface. The at least one communication receiver is configured to float in water. The processor of the monitoring tag is configured to determine, using the at least one sensor, whether the monitoring tag is within a communication range for radio frequency communication with the at least one communication receiver, and to transmit, via the at least one communication interface of the monitoring tag, the stored readings to the at least one communication receiver responsive to the processor of the monitoring tag determining that the monitoring tag is within the communication range for radio frequency communication with the at least one communication receiver.

The present disclosure relates to a method for operating a measuring point in process engineering, wherein at least one Lidar (light detection and transmission) system is used at the measuring point, comprising: acquiring spatial information from the surroundings of the measuring point by means of the Lidar system; extracting object information from the spatial information; and reconstructing and identifying objects on the basis of the object information and associating the object information with the reconstructed and identified objects.

The present disclosure relates to a method for operating a measuring point in process engineering, wherein at least one Lidar (light detection and transmission) system is used at the measuring point, comprising: acquiring spatial information from the surroundings of the measuring point by means of the Lidar system; extracting object information from the spatial information; and reconstructing and identifying objects on the basis of the object information and associating the object information with the reconstructed and identified objects.

A precast dam structure includes at least two precast segments coupled together via linkages and a flow path structure. The flow path structure defines a flow path having an intake port and a draft port and is associated with at least one of the at least two precast segments. The flow path structure is configured to provide a change in flow direction, either internally or externally, from the at least one of the at least two precast segments.

A precast dam structure includes at least two precast segments coupled together via linkages and a flow path structure. The flow path structure defines a flow path having an intake port and a draft port and is associated with at least one of the at least two precast segments. The flow path structure is configured to provide a change in flow direction, either internally or externally, from the at least one of the at least two precast segments.

Computer-implemented techniques for forecasting growth of a set of aquatic organisms in an aquaculture environment using time-series models. The techniques can be used to predict the growth of a set of aquatic organisms in a fish farm enclosure in a period. In some variations, the techniques proceed by obtaining an evidentiary time series (e.g., daily biomass estimates produced by a biomass estimation system) and a set of one or more reference (covariant) time series (e.g., daily biomass estimates produced by a biological model of fish growth). The techniques construct a time-series model from the evidentiary time series and the set of reference time series. The techniques use the constructed time-series model to forecast the evidentiary time series. In some variations, the time-series model is a Bayesian structural time-series model or other state space model for time series data.