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Cross-border Airport Bridge Leverages SAFR for Biometric Passenger Processing

October 14, 2020

Cross-border Airport Bridge Leverages SAFR for Biometric Passenger Processing

The first building to connect the United States to a foreign airport is going to use technology from RealNetworks‘ SAFR subsidiary in order to improve passenger throughput.

Tijuana International Airport’s Cross Border Xpress, or “CBX”, is a long bridge connecting the Mexican airport to a terminal in San Diego. Opened in late 2015, CBX is designed to help travelers avoid delays in border crossings at Otay and San Ysidro, and serves millions of passengers.

Now, thanks to a partnership with RealNetworks, Otay-Tijuana Venture LLC – the US-Mexican consortium that operates CBX, will implement video analytics technology from the SAFR platform.

In a statement announcing the collaboration, the organizations did not offer many specific details of how SAFR’s technology will be used at the border crossing. The SAFR platform prominently offers facial recognition technology, but the organizations emphasized its AI-driven “video analytics” capabilities, noting that its mask detection feature would help CBX administrators to ensure compliance with COVID-19 safety precautions.

“We are very satisfied with the performance, specific dashboards, and team support that SAFR offers, providing the necessary insights that are required to run such an important operation like CBX,” commented CBX Chief Technology Officer Julio Armentariz.

“We see optimal potential in RealNetworks’ technology and we are looking into expanding its use in other areas within CBX in order to increase operational efficiency,” he said.

News of the partnership comes after RealNetworks’ announcement this week that it will publish its third quarter results on Tuesday, November 3.

–

October 14, 2020 – by Alex Perala

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Filed Under: News Tagged With: AI, airport deployments, artificial intelligence, Biometric, biometrics, face biometrics, facial recognition, passenger processing, RealNetworks, SAFR, video analytics

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