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­a Pioneers More Effective Control For Border Patrol

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A U.S. Air Force unmanned aerial vehicle, similar to those used by U.S. Customs and Border Protection.

Researchers at the University of Arizona are developing a framework for border surveillance that uses artificial intelligence to integrate data from a variety of sources and respond in real time.

Credit: U.S. Air Force

University of Arizona (UA) researchers are developing a framework for border surveillance that uses artificial intelligence, based on realistic computer simulations, to integrate data from different sources and respond in real time.

The team plans to develop a system to most effectively, efficiently, and safely deploy border patrol resources, according to UA professor Young-Jun Son.

As part of the project, the researchers developed motion-detection and geolocation algorithms to enable aerial and ground vehicles to work in teams to precisely locate targets and decide how to respond.

In addition, the researchers analyzed and tested different wireless network technologies for drones to communicate and cooperate over varied distances.

During testing, the researchers used an aerial drone to track 10 student volunteers. The researchers also deployed an unmanned ground vehicle to identify individual people and serve as a moving landmark to prevent the drone from losing sight of its subjects.

From UA News (AZ)
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