In 2011, the simple exploitation of an existing data set could have prevented a near disaster in northern Afghanistan.
Then, an entire operations center watched as the feed from an MQ-1 drone, newly reassigned from its original mission, displayed a growing group of protesters at the perimeter of a small U.S. forward operating base. Although conventional signals intelligence indicated a possible disturbance, full-motion video confirmed the severity of the threat only well after it had matured. Intelligence analysts didn’t understand what the protestors were doing — and why they were doing it — until they had already massed at the entry point. If used properly, automated social media monitoring and geofencing, which calls for creating virtual geographic boundaries, could have filled this critical gap in situational awareness.
Read the full article at C4ISRNET