Airport Throughput Predictive Model
Description
This use case is a predictive model for passenger volume to help with airport staffing.
Detailed example
Once a month the data is ingested, the predictive model is trained, and predictions of airport checkpoint throughput are made for the airports.
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
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.
Controls / human review
ATO: Yes; PIA: Not published
Data needed
Secure Flight Passenger Data: passenger and airline reservation information received from airlines; PMIS Data: Secure checkpoint throughput counts by airport and checkpoint.