Airship Outpost for Conveyance Identification
Description
CBP must efficiently and accurately identify and document cross-border conveyances (aircraft, vessels, automobiles).
Detailed example
Identification and classification of the type of conveyance (e.g., automobile, aircraft, watercraft) including license plates, hull numbers, or tail numbers for monitoring purposes.
AI / analytics pattern
Computer Vision: AI that processes and interprets visual data (e.g., images and videos).
Automation level / stage
c) Deployed – The use case is being actively authorized or utilized to support the functions or mission of an agency.
Expected benefit
Outpost uses machine learning to identify the type of conveyance in front of the sensor camera and uses this information to determine where to capture the conveyance's identification (License plate, hull number, tail number, etc). Conveyance identifiers exist in different locations on different conveyance types. By identifying the type of conveyance, the system knows where to focus the capture mission relevant information.
Audit / financial statement impact
The AI is not being used for tracking or analysis. It is simply identifying the alpha-numeric values of the conveyances in front of it.
Controls / human review
ATO: Yes; PIA: https://www.dhs.gov/sites/default/files/2022-05/privacy-pia-cbp-tecs%20platform-april2022.pdf
Data needed
The datasets that the system uses are GOTS and LES. Purchased commercial data sources also used to enhance the value of the system. The AI only identifies the type of conveyance captured by the camera and determines the location of the alphanumeric identifiers used to identify it, such as license plates, hull numbers, or tail numbers. This information, along with an image of the conveyance and the date/time, is sent back.