Automated Field Data Collection
Description
The proliferation of screening technologies has increased the number of field data collection events necessary to characterize system performance. Currently, TSA does not have a solution to gather operational data without deploying physical teams. Addressing this gap presents an opportunity to achieve significant field efficiencies through automation and enhance wait times communication.
Detailed example
AI system outputs multiple decisions to include screening location performance, rates and standards of the end-to-end screening system, and passenger wait times.
AI / analytics pattern
Computer Vision: AI that processes and interprets visual data (e.g., images and videos).
Automation level / stage
a) Pre-deployment – The use case is in a development or acquisition status.
Expected benefit
The AI will analyze screening environments via CCTV footage and extract passenger processing times of various steps within the screening processes. Enabling AI to extract and visualize this data will enable TSA to make data informed decisions while testing or deploying new screening equipment, identify anomalies, establish real-world rates and standards, and reduce or eliminate TSA’s need to deploy data collection teams, resulting in real-time data collection and significantly reduced computational time of findings.
Controls / human review
ATO: Not reported; PIA: Not published