Provided are systems and methods for vessel infectious disease importation risk assessment. This includes receiving vessel data from one or more sources, wherein the vessel data includes infectious disease data, determining a rendezvous history of the vessel based on the vessel data, determining a port visits history of the vessel based on the vessel data, determining the vessel disease burden based on the port visits history, the rendezvous history, the infectious disease data and a period of crew social exchange outside the vessel, determining the vessel disease progression dynamics based on the vessel disease burden and the vessel time of arrival at destination, and determining, at the processor, the infectious disease importation risk assessment associated with the vessel disease progression dynamics.

Provided are systems and methods for vessel infectious disease importation risk assessment. This includes receiving vessel data from one or more sources, wherein the vessel data includes infectious disease data, determining a rendezvous history of the vessel based on the vessel data, determining a port visits history of the vessel based on the vessel data, determining the vessel disease burden based on the port visits history, the rendezvous history, the infectious disease data and a period of crew social exchange outside the vessel, determining the vessel disease progression dynamics based on the vessel disease burden and the vessel time of arrival at destination, and determining, at the processor, the infectious disease importation risk assessment associated with the vessel disease progression dynamics.

Predictive analytics techniques are used to produce leading indicators of economic activity based on factors determined from a range of available data sources, such as public and/or private transportation data. A fee-based subscription system may be provided for the sharing of leading indicators to users. A consistent, semantic metadata structure is described as well as a hypothesis generating and testing system capable of generating predictive analytics models in a non-supervised or partially supervised mode.

Predictive analytics techniques are used to produce leading indicators of economic activity based on factors determined from a range of available data sources, such as public and/or private transportation data. A fee-based subscription system may be provided for the sharing of leading indicators to users. A consistent, semantic metadata structure is described as well as a hypothesis generating and testing system capable of generating predictive analytics models in a non-supervised or partially supervised mode.

Disclosed is a ship identity recognition method based on the fusion of AIS data and video data, comprising: collecting a ship sample to train a ship target classifier; performing, using the ship target classifier, ship target detection on a video frame collected by a gimbal camera; performing a comparison with a recognized ship library to filter a recognized ship; acquiring AIS data and filtering same across time and spatial scales; predicting the current position of an AIS target using a linear extrapolation method and converting the current position to an image coordinate system; performing position matching between a target to be matched and the converted AIS target; and performing feature extraction on the successfully matched target and storing the extracted feature, together with ship identity information, into the recognized ship library. Experimental results show that the present invention can quickly and accurately extract a surveillance video and perform identity recognition on the ship target, effectively reduces labor costs, and has a broad application prospect in the fields such as ship transportation and port management.

Disclosed is a ship identity recognition method based on the fusion of AIS data and video data, comprising: collecting a ship sample to train a ship target classifier; performing, using the ship target classifier, ship target detection on a video frame collected by a gimbal camera; performing a comparison with a recognized ship library to filter a recognized ship; acquiring AIS data and filtering same across time and spatial scales; predicting the current position of an AIS target using a linear extrapolation method and converting the current position to an image coordinate system; performing position matching between a target to be matched and the converted AIS target; and performing feature extraction on the successfully matched target and storing the extracted feature, together with ship identity information, into the recognized ship library. Experimental results show that the present invention can quickly and accurately extract a surveillance video and perform identity recognition on the ship target, effectively reduces labor costs, and has a broad application prospect in the fields such as ship transportation and port management.

Disclosed herein is a method of determining an optimal route for a vessel based on vessel traffic data. The method comprises receiving vessel traffic data relating to the movement of each of a plurality of vessels in a geographical region and defining sub-regions within the geographical region in which the vessel traffic data has similar characteristics. The method also comprises determining an optimal route for a vessel between two geographical points using a representation of the geographical region. The representation comprises nodes, and each node is associated with a respective defined sub-region.

Disclosed herein is a method of determining an optimal route for a vessel based on vessel traffic data. The method comprises receiving vessel traffic data relating to the movement of each of a plurality of vessels in a geographical region and defining sub-regions within the geographical region in which the vessel traffic data has similar characteristics. The method also comprises determining an optimal route for a vessel between two geographical points using a representation of the geographical region. The representation comprises nodes, and each node is associated with a respective defined sub-region.

A hierarchical data acquisition system and method applied to a marine information network are provided. Multiple sensor nodes are arranged in clusters, each of the clusters includes a cluster head node and multiple ordinary nodes. The multiple ordinary nodes acquire data information of a seafloor and transmit the acquired data information to the cluster head node, and the cluster head node aggregate the data and transmits the aggregated data to an autonomous underwater vehicle, reducing energy consumption of each of the sensor nodes, prolonging service lives of sensors of a data acquisition layer, and improving data acquisition efficiency of a data acquisition layer. In addition, after each of data acquisition periods, a sensor node in each of the clusters is selected as a cluster head node in a next data acquisition cycle. Cluster head nodes are continuously updated in cycles.

A hierarchical data acquisition system and method applied to a marine information network are provided. Multiple sensor nodes are arranged in clusters, each of the clusters includes a cluster head node and multiple ordinary nodes. The multiple ordinary nodes acquire data information of a seafloor and transmit the acquired data information to the cluster head node, and the cluster head node aggregate the data and transmits the aggregated data to an autonomous underwater vehicle, reducing energy consumption of each of the sensor nodes, prolonging service lives of sensors of a data acquisition layer, and improving data acquisition efficiency of a data acquisition layer. In addition, after each of data acquisition periods, a sensor node in each of the clusters is selected as a cluster head node in a next data acquisition cycle. Cluster head nodes are continuously updated in cycles.