Entity tracking
Systems and methods for tracking at least one entity. Systems according to various embodiments may include an interface for at least receiving training data representing movements of a plurality of training entities and a query regarding a test entity's movement, a memory, and at least one processor executing instructions stored on the memory to create a plurality of tracks, generate an index of the plurality of tracks, execute the received query, and output a feature value with respect to the test entity.
1. A system for tracking at least one entity, the system comprising:
an interface for at least receiving:
training data representing movements of a plurality of training entities, and
a query regarding a test entity's movement;
a memory; and
at least one processor executing instructions stored on the memory to:
create a plurality of tracks based on the received training data, wherein each track represents the movement of a training entity and is associated with at least one attribute,
generate an index of the plurality of tracks by defining at least one of the tracks using a plurality of points from the received training data, wherein each point of the plurality represents a location of a training entity at a point in time,
execute a function to develop a trend line associated with the plurality of points,
represent the track by the developed trend line and add a buffer to the developed trend line,
execute the received query regarding the test entity's movement on the generated index, and
output a feature value with respect to the test entity based on the generated index.
2. The system of claim 1 wherein the test entity is selected from the group consisting of a person, a ship, an aircraft, and a vehicle.
3. The system of claim 1 wherein the feature value is an anomaly score representing whether the test entity's movement is anomalous with respect to the at least one attribute.
4. The system of claim 1 wherein the feature value is a prediction of the test entity's movement.
5. The system of claim 1 wherein the at least one attribute includes one or more of a city associated with the entity, a country associated with the entity, and an entity type.
6. A method for tracking at least one entity, the method comprising:
receiving training data representing movements of a plurality of training entities using an interface;
creating, using at least one processor executing instructions stored on a memory, a plurality of tracks based on the received training data, wherein each track represents the movement of a training entity and is associated with at least one attribute;
generating, using the at least one processor, an index of the plurality of tracks by defining at least one of the tracks using a plurality of points from the received training data, wherein each point of the plurality represents a location of a training entity at a point in time;
executing a function to develop a trend line associated with the plurality of points;
representing the track by the developed trend line and adding a buffer to the developed trend line;
receiving a query regarding a test entity's movement using the interface;
executing, using the at least one processor, the received query regarding the test entity's movement on the generated index; and
outputting, using the at least one processor, a feature value with respect to the test entity based on the generated index.
7. The method of claim 6 wherein the test entity is selected from the group consisting of a person, a ship, an aircraft, and a vehicle.
8. The method of claim 6 wherein the feature value is an anomaly score representing whether the test entity's movement is anomalous with respect to the at least one attribute.
9. The method of claim 6 wherein the feature value is a prediction of the test entity's movement.
10. The method of claim 6 wherein the at least one attribute includes one or more of a city associated with the entity, a country associated with the entity, and an entity type.
11. A system for tracking at least one entity, the system comprising:
an interface for at least receiving:
training data representing movements of a plurality of training entities, and
a query regarding a test entity's movement;
a memory; and
at least one processor executing instructions stored on the memory to:
create a plurality of tracks based on the received training data, wherein each track represents the movement of a training entity and is associated with at least one attribute,
generate an index of the plurality of tracks by defining at least one of the tracks using a plurality of points from the received training data, wherein each point of the plurality represents a location of a training entity at a point in time
execute a function to develop a trend line associated with the plurality of points,
represent the track by the developed trend line and adding a buffer to the developed trend line,
execute the received query regarding the test entity's movement on the generated index, and
output at least one of:
an anomaly score representing whether the test entity's movement is anomalous with respect to the at least one attribute, and
a prediction of the test entity's movement.
12. The system of claim 11 wherein the test entity is selected from the group consisting of a person, a ship, an aircraft, and a vehicle.
13. The system of claim 11 wherein the at least one attribute includes one or more of a city associated with the entity, a country associated with the entity, and entity type.
14. The system of claim 11 wherein an attribute is a ship type associated with the entity.