Watercraft automation and aquatic data utilization for aquatic efforts are utilized for updating map data with current position and current sonar information of a sonar device.

Techniques are disclosed for systems and methods for video based sensor fusion with respect to mobile structures. A mobile structure may include at least one imaging module and multiple navigational sensors and/or receive navigational data from various sources. A navigational database may be generated that includes data from the imaging module, navigational sensors, and/or other sources. Aspects of the navigational database may then be used to generate an integrated model, forecast weather conditions, warn of dangers, identify hard to spot items, and generally aid in the navigation of the mobile structure.

Techniques are disclosed for systems and methods for video based sensor fusion with respect to mobile structures. A mobile structure may include at least one imaging module and multiple navigational sensors and/or receive navigational data from various sources. A navigational database may be generated that includes data from the imaging module, navigational sensors, and/or other sources. Aspects of the navigational database may then be used to generate an integrated model, forecast weather conditions, warn of dangers, identify hard to spot items, and generally aid in the navigation of the mobile structure.

Watercraft automation and aquatic data utilization for aquatic efforts are disclosed. In one aspect, an anchor point is obtained and a watercraft position maintenance routine is actuated to control the watercraft to maintain association with the anchor point. In another aspect, prior aquatic effort data is obtained in association with an anchor point. In yet another aspect, current aquatic effort data is generated in association with an anchor point, in still another aspect, current aquatic effort data and prior aquatic effort data are utilized for prediction generation. In yet another aspect, current aquatic effort data and prior aquatic effort data are utilized to obtain another anchor point for a watercraft.

Watercraft automation and aquatic data utilization for aquatic efforts are disclosed. In one aspect, an anchor point is obtained and a watercraft position maintenance routine is actuated to control the watercraft to maintain association with the anchor point. In another aspect, prior aquatic effort data is obtained in association with an anchor point. In yet another aspect, current aquatic effort data is generated in association with an anchor point, in still another aspect, current aquatic effort data and prior aquatic effort data are utilized for prediction generation. In yet another aspect, current aquatic effort data and prior aquatic effort data are utilized to obtain another anchor point for a watercraft.

Watercraft automation and aquatic data utilization for aquatic efforts are disclosed. In one aspect, an anchor point is obtained and a watercraft position maintenance routine is actuated to control the watercraft to maintain association with the anchor point. In another aspect, prior aquatic effort data is obtained in association with an anchor point. In yet another aspect, current aquatic effort data is generated in association with an anchor point. In still another aspect, current aquatic effort data and prior aquatic effort data are utilized for prediction generation. In yet another aspect, current aquatic effort data and prior aquatic effort data are utilized to obtain another anchor point for a watercraft.

Watercraft automation and aquatic data utilization for aquatic efforts are disclosed. In one aspect, an anchor point is obtained and a watercraft position maintenance routine is actuated to control the watercraft to maintain association with the anchor point. In another aspect, prior aquatic effort data is obtained in association with an anchor point. In yet another aspect, current aquatic effort data is generated in association with an anchor point. In still another aspect, current aquatic effort data and prior aquatic effort data are utilized for prediction generation. In yet another aspect, current aquatic effort data and prior aquatic effort data are utilized to obtain another anchor point for a watercraft.

A method for automated navigational marker detection and association in maritime applications includes providing a camera system equipped with one or more red-green-blue (RGB) cameras for capturing visual data of a surrounding maritime environment in real-time, and then providing a computing unit comprising a neural network-based object detector, a projection mechanism module, and a GPS mapping and chart data integration module. Next, providing a database comprising pre-existing chart data of navigational markers. Next, capturing visual data of the surrounding maritime environment using the camera system. Next, processing the visual data by the computing unit using the neural network-based object detector to identify navigational markers. Next, projecting pixel positions of detected navigational markers into a three-dimensional (3D) coordinate system. Next, integrating the projected positions of the detected navigational markers into a navigational map, and then cross-referencing the projected positions of the detected navigational markers with pre-existing chart data of navigational markers for the same location to enhance navigational accuracy and reliability.

A method for automated navigational marker detection and association in maritime applications includes providing a camera system equipped with one or more red-green-blue (RGB) cameras for capturing visual data of a surrounding maritime environment in real-time, and then providing a computing unit comprising a neural network-based object detector, a projection mechanism module, and a GPS mapping and chart data integration module. Next, providing a database comprising pre-existing chart data of navigational markers. Next, capturing visual data of the surrounding maritime environment using the camera system. Next, processing the visual data by the computing unit using the neural network-based object detector to identify navigational markers. Next, projecting pixel positions of detected navigational markers into a three-dimensional (3D) coordinate system. Next, integrating the projected positions of the detected navigational markers into a navigational map, and then cross-referencing the projected positions of the detected navigational markers with pre-existing chart data of navigational markers for the same location to enhance navigational accuracy and reliability.

A marine vessel smart pole includes a wireless transmitter configured or programmed to perform a communication function to communicate with a marine vessel and a communication object other than the marine vessel, and a position information function to provide a position of the marine vessel smart pole to the marine vessel or a server of a port facility.