The CT2WS camera system being tested at the Yuma Proving Grounds in Arizona.
DARPA
As good as surveillance technology has gotten at some tasks, computers still frequently fail when it comes to figuring out the difference between a threat and a tumbleweed. As the Department of Homeland Security found out with its failed efforts to build a "virtual fence" along stretches of the US border, automated sensors can generate a very high level of false alarms, unable to distinguish cars and people from animals. In Israel, animals interfering with sensors have forced the military to string electrified barbed wire to keep wild boars from triggering alarms.
But depending on people alone to do the watching isn't the answer either. Even with the help of cameras and portable radar systems such as the Cerberus sensor towers deployed by the US military in Afghanistan, nearly half of the potential threats slip by—mostly because of the limits of human vision and fatigue associated with constant scanning of the screen or the horizon.
The Defense Advanced Research Projects Agency (DARPA) set out to find an answer to this problem in 2008 when it launched the Cognitive Technology Threat Warning System (CT2WS) program, an effort to magnify the abilities of a human lookout to achieve the perfect early warning system for soldiers in the field. Now, that program has completed testing of the product of its research: a sensor system that uses the operator's brain activity as a filter.
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