Autonomous Surveillance Tower

Overview

Development stage

DeployedSource: c) Deployed – The use case is being actively authorized or utilized to support the functions or mission of an agency.

High-impact designation

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

Impact justification

The AI outputs do not serve as a principal basis for a decision or action concerning a specific individual or entity that has a legal, material, binding, or similarly significant effect on that individual’s or entity’s civil rights, civil liberties or privacy, equal opportunities, or access to or the ability to apply for critical government resources or services. The AI provides alerts when it detects the presence of an IoI (i.e., persons, vehicles, animals) in the image frame. With regard to persons, this computer vision application is trained to determine if the object in the image frame is a person with a certain of level of confidence and not another object that may be shaped similarly to a person. After the alert of a detection, a trained agent or user, reviews the image to identify and classify the activity taking place. The AI merely alerts to the presence of an item it was trained to detect. This is not a biometric system and does not identify or track specific individuals.

Start date

2020-01-01 (day precision)Source: 2020-01-01T00:00:00

Withheld from public reporting

Not reported

Mission

Topic area

Law Enforcement

Operational functions

Biometrics and identity Derived by keyword rules; see methodology

Problem the AI is intended to solve

CBP's limited manpower constrains its ability to manually monitor all areas of the border at all times. To account for this limitation, surveillance and sensor systems assist in monitoring the border.

Expected benefits

AST machine learning assisted system is augmenting the U.S. Border Patrol by enhancing the capabiltiies of individual users when carrying out the domain awareness mission. The expected benefit is to have ability of single person to monitor magnitude greater area than could be done with conventional CCTV or human surveillance. The ultimate outcome for the agency and the public is greater availability of the agents to solve and address more complex tasks and allow for better strategic/tactical deployment of existing resources and personnel.

System outputs

The AI provides alerts when it detects the presence of an IoI (i.e., persons, vehicles, animals) in the image frame. With regard to persons, this computer vision application is trained to determine if the object in the image frame is a person with a certain of level of confidence and not another object that may be shaped similarly to a person. After the alert of a detection, a trained agent or user, reviews the image to identify and classify the activity taking place. The AI merely alerts to the presence of an item it was trained to detect. This is not a biometric system and does not identify or track specific individuals.

Technology

AI classification

Classical / predictive MLSource: Classical/Predictive Machine Learning: Models trained on data to make predictions or classifications based on identified patterns or relatio…

System name(s)

Autonomous Surveillance Towers

Custom-developed code

Yes

Public source code

Not reported

Sourcing

How it was built

Purchased from vendorSource: a) Purchased from a vendor

Vendor (as reported)

Anduril

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

No

Privacy Impact Assessment

cbpgov.sharepoint.com ↗

Authorization to Operate

Yes

Demographic features

Not reported

Training and evaluation data

Meta-data and data created by CBP. Generally comprised of agent adjudications of autonomous sensory inputs of items of interests by the system.

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