DHS S&T Awards Funding to Design Video Analytics for TSA Checkpoints
In the face of the COVID-19 pandemic, the Transportation Security Administration (TSA) is putting social distancing and other safety measures into place at airport TSA checkpoints. On March 2, the Department of Homeland Security (DHS) Science and Technology Directorate (S&T) Silicon Valley Innovation Program (SVIP) announced $196,880 in Phase 1 funding to Deep North, a start-up based in Foster City, California, to apply video analytics to airport screening processes to help minimize exposure and contact between Transportation Security Officers (TSOs) and passengers. The Phase 1 award was made under SVIP’s Emerging Needs: COVID-19 Response & Future Mitigation solicitation.
The solicitation accelerates efforts to explore the use of self-screening portals at airport security checkpoints by TSA’s Innovation Task Force and DHS S&T’s Screening at Speed Program, which aims to increase security effectiveness while dramatically reducing wait times and improving passenger experience. In Phase I of this project, Deep North proposes to augment its existing technology and deliver a video analytics platform for integration into self-screening portals that will provide a next generation screening experience, improve security, alleviate burden on TSOs, and reduce contact between travelers.
“Future passenger self-screening portals are expected to not only keep travelers and TSOs safer in pandemic situations like the one we face today,” said John Fortune, DHS S&T screening at speed program manager, “but also will improve the quality of screening from a security perspective and provide an innovative and convenient experience for airline passengers.”
The Deep North project proposes to meet this need by leveraging their capabilities to detect patterns and anomalies in full-motion video (FMV) footage using artificial intelligence (AI)-based video analytics that provide real-time feedback. These video solutions will validate that passengers are properly progressing through the screening process, passengers needing assistance navigating the self-screening portal are quickly identified, and social distancing measures are maintained. The system will not use biometric data, such as facial recognition. Instead, the system will place a unique identifier on passengers as they move through the airport security screening that expires immediately after they leave the checkpoint. The project proposes to also integrate 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,” said Melissa Oh, SVIP managing director. “There’s a lot of potential impact to be made on TSA’s future screening processes with this project.”
