Empty Container Detection Model (Cargo Insights Team)
Description
This enhances border security and optimizes resource allocation for inspections. The model is designed to accurately identify and track empty containers in cargo shipments, preventing errors and fraud in cargo declarations.
Detailed example
The system applies a prediction label alongside a bounding box on record. Officers use this information along with all information provided to determine what, if any, further steps are required.
AI / analytics pattern
Classical/Predictive Machine Learning: Models trained on data to make predictions or classifications based on identified patterns or relationships.
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
The AI improves accuracy, enhances efficiency by prioritizing legitimate containers for inspection, and strengthens security by detecting potential smuggling risks.
Controls / human review
ATO: Yes; PIA: Not published
Data needed
X-ray images and associated metadata.