Anomaly Detection POV Structure

Overview

Development stage

In development or acquisitionSource: a) Pre-deployment – The use case is in a development or acquisition status.

High-impact designation

Presumed high-impact, determined notSource: b) Presumed high-impact, but determined not high impact

Impact justification

Computer Vision is intended to detect anomalies in non-intrusive inspection images. The images are then shared with officers who review the detections within the images (represented as a polygon). If the officer feels physical review is required, the vehicle is moved to secondary inspection for more thorough review by an officer. The output of the AI does not serve as a principal basis for a decision or action.

Start date

Not reported

Withheld from public reporting

Not reported

Mission

Topic area

Law Enforcement

Operational functions

No function tag matched Derived by keyword rules; see methodology

Problem the AI is intended to solve

The Anomaly Detection Algorithm (ADA) models are intended to solve several key problems for U.S. Customs and Border Protection (CBP) related to the screening of privately owned vehicles (PoVs). Improving the detection of anomalies and contraband, enhancing efficiency in image review, enhance human capability to consistently detect items of interest or concern, addressing high traffic volumes and resource constraints, and supporting the analysis of complex inspections.

Expected benefits

CBP is seeking Anomaly Detection Algorithm (ADA) models capable of operating on CBP systems to enable rapid screening of passenger and cargo vehicles. The objective is to develop a suite of algorithms that enhance CBP's Non-Intrusive Inspection (NII) image analysis, improving the detection of anomalies and contraband. These algorithms are intended to assist CBP officers in efficiently reviewing images, with a particular focus on identifying concealed contraband and anomalies in passenger vehicles and cargo conveyances. The implementation of ADA models will enhance human capability to consistently detect items of interest or concern, including concealed objects, in vehicles entering the United States. Additionally, these algorithms will enhance throughput efficiency at ports of entry, enabling the expedited processing of compliant vehicles while maintaining robust security standards.

System outputs

Bounding boxes around an anomaly or unidentifiable object(s) within an image or any portion of the image that cannot be identified or explained.

Technology

AI classification

Computer visionSource: Computer Vision: AI that processes and interprets visual data (e.g., images and videos).

System name(s)

Not reported

Custom-developed code

Not reported

Public source code

Not reported

Sourcing

How it was built

Not reported

Vendor (as reported)

Not reported

Vendors (standardized)

None on the standard list

A vendor is the supplier named by the agency. It does not identify the underlying model or AI technology.

Data and privacy

Involves PII

Not reported

Privacy Impact Assessment

Not reported

Authorization to Operate

Not reported

Demographic features

Not reported

Training and evaluation data

Not reported

Federal Data Catalog

Not reported

Governance

0 of 8 minimum-practice questions answered. A blank answer means the agency reported nothing; it does not mean the practice is absent.

Potential impacts and how they were identified

Not reported