TSA explores video analytics for better security screening
The Transportation Security Administration is experimenting with video analytics to improve the passenger experience at TSA airport checkpoints.
Under a Silicon Valley Innovation Program (SVIP) Phase 1 award to Deep North, TSA will explore how video analytics can help monitor that passengers are socially distanced and properly moving through the screening process. It will also flag anomalous behavior and measure the contact time between passengers and transportation security officers (TSOs).
The award accelerates efforts by TSA’s Innovation Task Force and the Department of Homeland Security Science & Technology Directorate’s Screening at Speed Program to develop self-screening portals at airport security checkpoints.
Deep North’s technology analyzes video captured from surveillance cameras in retail settings and transportation hubs. It applies artificial intelligence and machine learning to extract insights on how passengers react to and move through a facility’s physical retail, food and travel environments.
The company plans to augment its existing systems and design a video analytics platform that can be integrated into self-screening portals. The system would use AI to detect patterns and anomalies in full-motion video and provide real-time feedback to improve security, alleviate burden on TSOs and reduce contact between travelers.
The system will not use biometric or facial recognition data, DHS said in its announcement. Instead, the system will place a temporary, unique identifier on passengers as they move through the security screening process that expires immediately after they leave the checkpoint. Eventually, the technology would be integrated with automated baggage- and body-scanning software to create a robust self-service screening solution.
“Deep North has already demonstrated commercial success in the travel and telecommunication industries – at both the global and national level,” SVIP Managing Director Melissa Oh said. “There’s a lot of potential impact to be made on TSA’s future screening processes with this project.”
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