Systems, methods, and computer readable media for vessel rendezvous detection and prediction
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.
1. A computer implemented method for generating a future vessel rendezvous prediction output, the method comprising:
receiving, at a processor, a rendezvous prediction model;
receiving, at the processor, vessel data for a plurality of vessels from one or more sources;
receiving, at the processor, updated vessel data for the plurality of vessels from the one or more sources, the updated vessel data comprising data collected subsequent to the vessel data;
constructing, at the processor, a future vessel trajectory for each vessel of the plurality of vessels based on the vessel data and the updated vessel data, each future vessel trajectory comprising one or more trajectory segments;
identifying, at the processor, at least one unstable speed segment of the one or more trajectory segments;
providing, at the processor, the plurality of constructed future vessel trajectories and the at least one unstable speed segment to the rendezvous prediction model;
generating, at the processor, the future rendezvous prediction output from the rendezvous prediction model, the rendezvous prediction output comprising a risk score and a risk explanation; and
outputting a user interface comprising a map, at least two vessel icons positioned on the map accompanied by the risk score and the risk explanation based on the updated vessel data, and the future rendezvous prediction output associated with the at least two vessel icons.
2. The method of claim 1 further comprising:
receiving, at the processor, region boundaries data from a region boundaries data source, the region boundaries data describing a plurality of regional boundaries;
enhancing, at the processor, the vessel data with the plurality of region boundaries based on the region boundaries data; and
wherein each of the plurality of constructed future vessel trajectories are constructed based on the enhanced vessel data.
3. The method of claim 1 wherein the future rendezvous prediction output comprises an output selected from the group of: no rendezvous threat, threat of an imminent rendezvous, and involved in a rendezvous.
4. The method of claim 3 further comprising:
receiving, at the processor, a rendezvous type classification model;
converting, at the processor, the one or more trajectory segments of the plurality of constructed future vessel trajectories corresponding to the future vessel rendezvous prediction output into images;
providing, at the processor, the images to the rendezvous type classification model; and
generating, at the processor, a rendezvous type classification output from the rendezvous type classification model.
5. The method of claim 4 , wherein the rendezvous type classification output comprises at least one selected from the group of a path crossing type, a parallel course type and a loitering in the same vicinity type.
6. The method of claim 1 , wherein the vessel data comprises at least one selected from the group of AIS data source, vessel information data from a vessel information source, radio frequency vessel data from a satellite radio frequency data source, satellite image data from an optical satellite image data source, and satellite image data from a radar satellite image data source.
7. The method of claim 1 , wherein the future rendezvous prediction model comprises one or more long short term memory networks.
8. The method of claim 1 , wherein generating the future rendezvous prediction output is based on the at least one unstable speed segment of the one or more trajectory segments.
9. A computer-implemented system for generating a future vessel rendezvous prediction output, the system comprising:
a memory comprising:
a rendezvous prediction model;
a network device;
a processor in communication with the memory and the network device, the processor configured to:
receive, via the network device, vessel data for a plurality of vessels from one or more sources;
receive updated vessel data for the plurality of vessels from the one or more sources, the updated vessel data comprising data collected subsequent to the vessel data;
construct a future vessel trajectory for each vessel in the plurality of vessels based on the vessel data and the updated vessel data, each future vessel trajectory comprising one or more trajectory segments;
identify at least one unstable speed segment of the one or more trajectory segments;
provide the plurality of constructed future vessel trajectories and the at least one unstable speed segment as input to the rendezvous prediction model;
generate the future rendezvous prediction output from the rendezvous prediction model, the rendezvous prediction output comprising a risk score and a risk explanation; and
output a user interface comprising a map, at least two vessel icons positioned on the map accompanied by the risk score and the risk explanation based on the updated vessel data, and the future rendezvous prediction output associated with the at least two vessel icons.
10. The system of claim 9 , wherein the processor is further configured to:
receive, via the network device, region boundaries data from a region boundaries data source, the region boundaries data describing a plurality of regional boundaries;
enhance the vessel data with the plurality of region boundaries based on the region boundaries data; and
wherein each of the plurality of constructed future vessel trajectories are based on the enhanced vessel data.
11. The system of claim 9 , wherein the future rendezvous prediction output comprises an output selected from the group of: no rendezvous threat, threat of an imminent rendezvous, and involved in a rendezvous.
12. The system of claim 11 , wherein the memory further comprises a rendezvous type classification model; and
wherein the processor is further configured to:
convert the one or more trajectory segments of the plurality of future vessel trajectories corresponding to the future vessel rendezvous prediction output into images;
provide the images to the rendezvous type classification model as input; and
generate a rendezvous type classification output from the rendezvous type classification model.
13. The system of claim 12 , wherein the rendezvous type classification output comprises at least one selected from the group of a path crossing type, a parallel course type and a loitering in the same vicinity type.
14. The system of claim 9 , wherein the vessel data comprises at least one selected from the group of AIS data source, vessel information data from a vessel information source, radio frequency vessel data from a satellite radio frequency data source, satellite image data from an optical satellite image data source, and satellite image data from a radar satellite image data source.
15. The system of claim 9 , wherein the rendezvous prediction model comprises one or more long short term memory networks.
16. The system of claim 9 , wherein the future rendezvous prediction output is generated based on the at least one unstable speed segment of the one or more trajectory segments.