Computer implemented methods, systems, and computer-readable media for predicting a vessel identifier are provided. These include providing, at a memory, a vessel identification model, receiving, at a processor in communication with the memory, vessel data from one or more sources, determining, at the processor, a plurality of periodograms from the vessel data, the plurality of periodograms determined for a candidate vessel corresponding to candidate vessel data in the vessel data, determining, at the processor, a spectrogram based on the plurality of periodograms; and predicting, at the processor, a vessel identifier output of the candidate vessel based on the spectrogram and the vessel identification model.
Computer implemented methods, systems, and computer-readable media for predicting a vessel identifier are provided. These include providing, at a memory, a multivariate model and a vessel identification model, receiving, at a processor in communication with the memory, vessel data from one or more sources, determining, at a processor, a dynamic candidate vessel corresponding to the vessel data from the one or more sources, and a candidate vessel corresponding to candidate vessel data in the vessel data and predicting, at the processor, a vessel identifier output of the candidate vessel based on the dynamic candidate vessel, the multivariate model, and the vessel identification model.
Provided are systems and methods for vessel risk assessment. This includes determining a risk assessment associated with a vessel, including receiving vessel data from at least one source, generating at least one vessel profile based on the vessel data, wherein each vessel profile provides indication of expected behavior events for one vessel and abnormal behavior events for one vessel, determining at least one abnormal behavior event of the vessel based on the at least one vessel profile, each event in the at least one abnormal behavior event having a time of occurrence, determining at least one frequency of occurrence of abnormal behavior events of the vessel based on the time of occurrence of each event, using at least one model to determine a risk assessment associated with the vessel based on the at least one frequency of occurrence of abnormal behavior events of the vessel.
Provided are systems and methods for determining an estimated time of arrival for one or more vessels based on vessel tracking data, and systems and methods for generating an estimated time of arrival model. This includes providing, at a memory, an estimated time of arrival model and a plurality of port boundaries; receiving, at a processor in communication with the memory, vessel data corresponding to at least one vessel, the vessel data comprising vessel location data and secondary data; receiving, at a network device in communication with the processor, an estimated time of arrival request; in response to the estimated time of arrival request, determining an estimated time of arrival corresponding to at least one vessel based on the vessel data and the estimated time of arrival model; and outputting, at an output device in communication with the processor, the estimated time of arrival for the at least one vessel.
Provided are systems, methods, and computer readable media for predicting a vessel rendezvous, and systems, methods, and computer readable media for generating a vessel rendezvous prediction model. The method can include generating or receiving a rendezvous a rendezvous prediction model; receiving vessel data for a plurality of vessels from one or more sources; constructing a vessel trajectory for each vessel of the plurality of vessels based on the vessel data, each vessel trajectory comprising one or more trajectory segments; providing the plurality of constructed vessel trajectories to the rendezvous prediction model; and generating, at the processor, a rendezvous prediction output from the rendezvous prediction model.
Provided are systems, methods, and computer readable media for predicting a vessel rendezvous, and systems, methods, and computer readable media for generating a vessel rendezvous prediction model. The method can include generating or receiving a rendezvous a rendezvous prediction model; receiving vessel data for a plurality of vessels from one or more sources; constructing a vessel trajectory for each vessel of the plurality of vessels based on the vessel data, each vessel trajectory comprising one or more trajectory segments; providing the plurality of constructed vessel trajectories to the rendezvous prediction model; and generating, at the processor, a rendezvous prediction output from the rendezvous prediction model.
Provided are systems, methods, and computer readable media for predicting a vessel rendezvous, and systems, methods, and computer readable media for generating a vessel rendezvous prediction model. The method can include generating or receiving a rendezvous a rendezvous prediction model; receiving vessel data for a plurality of vessels from one or more sources; constructing a vessel trajectory for each vessel of the plurality of vessels based on the vessel data, each vessel trajectory comprising one or more trajectory segments; providing the plurality of constructed vessel trajectories to the rendezvous prediction model; and generating, at the processor, a rendezvous prediction output from the rendezvous prediction model.
G06N 3/04 - Architecture, e.g. interconnection topology
B63B 79/40 - Monitoring properties or operating parameters of vessels in operation for controlling the operation of vessels, e.g. monitoring their speed, routing or maintenance schedules
G01C 21/20 - Instruments for performing navigational calculations
9.
System and method for vessel infectious disease importation risk assessment
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.
G16H 50/30 - ICT specially adapted for medical diagnosis, medical simulation or medical data miningICT specially adapted for detecting, monitoring or modelling epidemics or pandemics for calculating health indicesICT specially adapted for medical diagnosis, medical simulation or medical data miningICT specially adapted for detecting, monitoring or modelling epidemics or pandemics for individual health risk assessment
G08G 3/00 - Traffic control systems for marine craft
G16H 10/60 - ICT specially adapted for the handling or processing of patient-related medical or healthcare data for patient-specific data, e.g. for electronic patient records
G16H 50/20 - ICT specially adapted for medical diagnosis, medical simulation or medical data miningICT specially adapted for detecting, monitoring or modelling epidemics or pandemics for computer-aided diagnosis, e.g. based on medical expert systems
Provided are systems and methods for vessel risk assessment. This includes determining a risk assessment associated with a vessel, including receiving vessel data from at least one source, generating at least one vessel profile based on the vessel data, wherein each vessel profile provides indication of expected behavior events for one vessel and abnormal behavior events for one vessel, determining at least one abnormal behavior event of the vessel based on the at least one vessel profile, each event in the at least one abnormal behavior event having a time of occurrence, determining at least one frequency of occurrence of abnormal behavior events of the vessel based on the time of occurrence of each event, using at least one model to determine a risk assessment associated with the vessel based on the at least one frequency of occurrence of abnormal behavior events of the vessel.
G06Q 10/04 - Forecasting or optimisation specially adapted for administrative or management purposes, e.g. linear programming or "cutting stock problem"
G06Q 10/08 - Logistics, e.g. warehousing, loading or distributionInventory or stock management
Provided are systems and methods for vessel risk assessment. This includes determining a risk assessment associated with a vessel, including receiving vessel data from at least one source, generating at least one vessel profile based on the vessel data, wherein each vessel profile provides indication of expected behavior events for one vessel and abnormal behavior events for one vessel, determining at least one abnormal behavior event of the vessel based on the at least one vessel profile, each event in the at least one abnormal behavior event having a time of occurrence, determining at least one frequency of occurrence of abnormal behavior events of the vessel based on the time of occurrence of each event, using at least one model to determine a risk assessment associated with the vessel based on the at least one frequency of occurrence of abnormal behavior events of the vessel.
G06Q 10/04 - Forecasting or optimisation specially adapted for administrative or management purposes, e.g. linear programming or "cutting stock problem"
G06Q 10/08 - Logistics, e.g. warehousing, loading or distributionInventory or stock management
Provided are systems and methods for vessel risk assessment. This includes determining a risk assessment associated with a vessel, including receiving vessel data from at least one source, generating at least one vessel profile based on the vessel data, wherein each vessel profile provides indication of expected behavior events for one vessel and abnormal behavior events for one vessel, determining at least one abnormal behavior event of the vessel based on the at least one vessel profile, each event in the at least one abnormal behavior event having a time of occurrence, determining at least one frequency of occurrence of abnormal behavior events of the vessel based on the time of occurrence of each event, using at least one model to determine a risk assessment associated with the vessel based on the at least one frequency of occurrence of abnormal behavior events of the vessel.
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