Transportation security apparatus, system, and method to analyze images to detect a threat condition
In a transportation security technique, images are stored that are received from image capturing equipment deployed at respective screening nodes. The images are analyzed using a machine learning model, where presence of a particular object in an image indicates that a threat condition exists at the screening node. The analyzed images are transmitted to threat assessment components in accordance with predetermined criteria. An indication that the particular object is observed in the image is received from the threat assessment components. An indication that the particular object is observed in the image is transmitted to the screening node responsive to receiving the indication that the particular object is observed in the image. An indication of whether the particular object is present at the screening node is received. The machine learning model is trained based on the received indication of whether the particular object is observed in the image.
1. A method, comprising:
receiving a first set of images from image capturing equipment deployed at respective screening nodes located at one or more airports;
receiving a second set of images from a covert node, which generates the second set of images under controlled conditions at a non-airport facility, the second set of images includes at least one of a threat-positive test image depicting objects indicative of threat conditions or a threat-negative test image void of objects indicative of threat conditions;
utilizing a threat detection model to evaluate an image from the first set or the second set to determine whether a particular object is depicted in the image, the particular object being indicative of a threat condition;
transmitting the image from the first set or the second set to one or more threat assessment components in accordance with operator selection criteria;
receiving, from a threat assessment component, an indication that the particular object is observed or not observed in the image; and
determining whether the image includes the particular object based on at least the indication from the threat assessment component or a result from the threat detection model.
2. The method of claim 1 , wherein the image originates from a screening node, and wherein the method further comprises transmitting an indication that the particular object is present or absent in the image to the screening node at which the image was captured, and
when an indication that the particular object is present in the image transmitted to the screening node, the indication further includes a command to route property associated with the image to a security officer for verification, and the method further includes:
receiving an indication of whether the particular object is verified in the property at the screening node; and at least one of:
computing a rating for a human operator at the threat assessment component to which the image was transmitted based on the indication received from the screening node; or
determining an effectiveness of the threat detection model based on the result of the threat detection model.
3. The method of claim 2 , further comprising training a model based on the indication of whether the particular object is verified in the property at the screening node, wherein the model is one of the threat detection model or another model.
4. The method of claim 1 , wherein the image is a threat-positive image or a threat-negative image from the covert node, and wherein the method further comprises at least one of:
computing a rating for a human operator at the threat assessment component to which the image was transmitted based on the indication received from the threat assessment component; or
determining an effectiveness of the threat detection model based on the result of the threat detection model.
5. The method of claim 1 , further comprises training a model based on the second set of images, wherein the model is one of the threat detection model or another model.
6. The method of claim 1 , further comprising verifying whether the particular object is present or absent in the image before utilizing the image to train a model, wherein the model is at least one of the threat detection model or another model.
7. The method of claim 1 , further comprising training a model based on the indication that the particular object is observed or not observed in the image received from the threat assessment component, wherein the model is one of the threat detection model or another model.
8. The method of claim 1 , wherein the threat detection model is deployed on one or more of a screening node, a threat assessment component, or a central node device, and
wherein the screening node or the covert node transmits the image from the first set or the second set to the one more threat assessment components.
9. A transportation security apparatus, comprising:
a memory; and
a processor coupled to the memory and configured to:
receive a result from a threat detection model that evaluates an image from a first set of images or a second set of images to determine whether a particular object is depicted in the image, the particular object being indicative of a threat condition;
receive, from a threat assessment component selected from one or more threat assessment components in accordance with operator selection criteria, an indication that the particular object is observed or not observed in the image; and
determine whether the image includes the particular object based on at least the indication from the threat assessment component or a result from the threat detection model,
wherein the first set of images includes images from image capturing equipment deployed at respective screening nodes located at one or more airports, and
wherein the second set of images include images from a covert node, which generates the second set of images under controlled conditions at a non-airport facility, the second set of images includes at least one of a threat-positive test image depicting objects indicative of threat conditions or a threat-negative test image void of objects indicative of threat conditions.
10. The transportation security apparatus of claim 9 , wherein the image originates from a screening node, and wherein the processor is further configured to transmit an indication that the particular object is present or absent in the image to the screening node at which the image was captured.
11. The transportation security apparatus of claim 9 , wherein the image is a threat-positive image or a threat-negative image from the covert node, and wherein the processor is further configured to at least one of:
compute a rating for a human operator at the threat assessment component to which the image was transmitted based on the indication received from the threat assessment component; or
determine an effectiveness of the threat detection model based on the result of the threat detection model.
12. The transportation security apparatus of claim 9 , wherein the processor is further configured to train a model based on the second set of images, wherein the model is one of the threat detection model or another model.
13. The transportation security apparatus of claim 10 , wherein an indication that the particular object is present in the image transmitted to the screening node includes a command to route property associated with the image to a security officer for verification, and wherein the processor is further configured to:
receive an indication of whether the particular object is verified in the property at the screening node; and at least one of:
compute a rating for a human operator at the threat assessment component to which the image was transmitted based on the indication received from the screening node; or
determine an effectiveness of the threat detection model based on the result of the threat detection model.
14. The transportation security apparatus of claim 13 , wherein the processor is further configured to train a model based on the indication of whether the particular object is verified in the property at the screening node, wherein the model is one of the threat detection model or another model.
15. The transportation security apparatus of claim 9 , wherein the processor is further configured to obtain verification whether the particular object is present or absent in the image before utilizing the image to train a model, wherein the model is one of the threat detection model or another model.
16. The transportation security apparatus of claim 10 , wherein an indication that the particular object is absent in the image transmitted to the screening node includes a command to route property associated with the image back to a passenger.
17. The transportation security apparatus of claim 9 , wherein the processor is further configured to train a model based on the indication that the particular object is observed or not observed in the image received from the threat assessment component, wherein the model is one of the threat detection model or another model.
18. The transportation security apparatus of claim 9 , wherein the transportation security apparatus is one or more of a screening node, a threat assessment component, or a central node device, and
wherein the threat detection model is deployed on one or more of the transportation security apparatus, a threat assessment component, a screening node, or a central node device.
19. A transportation security system, comprising:
a set of screening node devices located at one or more airports, each having image capturing equipment deployed thereat by which image data are generated, the image data comprising individual images of objects passing through the image capturing equipment, wherein presence of a particular object at any of the set of screening node devices manifests a threat condition at that screening node device;
a set of image interpretation node devices, each having a threat assessment component deployed thereat at which is determined whether the particular object is depicted in the image data generated at each of the screening node devices;
a covert node device that generates at least one of a threat-positive test image that depicts an object indicative of a threat condition or a threat-negative test image, the covert node device located at a non-airport facility under controlled conditions; and
a processor coupled to the memory and configured to:
receive a first set of images from the set of screening nodes;
receive a second set of images from the covert node device;
receive a result from a threat detection model that evaluates an image from the first set or the second set to determine whether a particular object is depicted in the image, the particular object being indicative of a threat condition;
receive, from a threat assessment component selected from one or more threat assessment components in accordance with operator selection criteria, an indication that the particular object is observed or not observed in the image;
determine whether the image includes the particular object based on at least the indication from the threat assessment component or a result from the threat detection model.
20. The transportation security system of claim 19 , wherein the processor is included in one or more of a screening node device, an image interpretation node device, or a central node device, and
wherein the set of screening node devices, the set of image interpretation node devices, and the covert node device are communicatively coupled through a telecommunications network.