DHS · DHS-2432 · record R1983
Airport Throughput Predictive Model
Department of Homeland Security · TSA
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
- Not high-impactSource: c) Not high-impact
- Impact justification
- Not reported
- Start date
- 2024-04-01 (day precision)Source: 2024-04-01T00:00:00
- Withheld from public reporting
- Not reported
Mission
- Topic area
- Administrative Functions
- Operational functions
- Forecasting and prediction Derived by keyword rules; see methodology
Problem the AI is intended to solve
This use case is a predictive model for passenger volume to help with airport staffing.
Expected benefits
This project was to create a predictive model for the passenger volume using the Security Operations throughput count from checkpoints to help with airport staffing.
System outputs
Once a month the data is ingested, the predictive model is trained, and predictions of airport checkpoint throughput are made for the airports.
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)
- Secure Flight
- 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
- Secure Flight Passenger Data: passenger and airline reservation information received from airlines; PMIS Data: Secure checkpoint throughput counts by airport and checkpoint.
- 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