NASA · NASA-398 · record R0226

Autonomous WAiting Room Evaluation (AWARE)

National Aeronautics and Space Administration · LaRC: Langley Research Center

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: This AI processes images of people waiting in the Langley Badge & Pass office. The people are counted and their images immediately deleted to avoid privacy issues.
Start date: 2023-01-01 (day precision)Source: 01/01/2023 00:00:00
Withheld from public reporting: NoSource: a) No

Mission

Topic area: Administrative FunctionsSource: Administrative functions
Operational functions: No function tag matched Derived by keyword rules; see methodology

Problem the AI is intended to solve

Using an existing security camera and YOLO Machine Learning model to detect and count number of people waiting for service at Langley's Badge & Pass Office. When a predetermined threshold of people is exceeded, automated texts and emails are sent to request additional help at the service counters.

Expected benefits

Spreads load on LaRC Badge & Pass Office (via website telling employees how busy) and adds BPO support by texting staff when waiting room conut threshold exceeded.

System outputs

Detection, classification and enumaration of people in BPO waiting area

Technology

AI classification: Computer visionSource: Computer Vision: AI that processes and interprets visual data (e.g., images and videos).
System name(s): LaRC BPO Private Server
Custom-developed code: Yes
Public source code: Not reported

Sourcing

How it was built: Developed in-houseSource: b) Developed in-house
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: No
Privacy Impact Assessment: Not reported
Authorization to Operate: Yes
Demographic features: Not reported
Training and evaluation data: Open-source Common Objects in Context (COCO) dataset
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.

Pre-deployment testingNo answer reported

AI impact assessmentNo answer reported

Independent reviewNo answer reported

Ongoing monitoringNo answer reported

Operator trainingNo answer reported

Fail-safeNo answer reported

Appeal processNo answer reported

User and public consultationNo answer reported

Potential impacts and how they were identified

Not reported