How to Process the “Mountain” of Video Data?
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עברית (Hebrew)
How can security forces deal with the astronomic amounts of video data collected by all sorts of different sensors? Over the past decade, technological improvements have made the dream of the unblinking eye a near reality. Cameras are cheaper to make and install, while providing higher quality images. The advent of streaming video, much of it relayed via satellite, has given US Defense Department analysts a wealth of information previously unimaginable.
According to Defense News, the unintended consequence of those increased capabilities is that the Pentagon is drowning in data, unable to keep up with the gigabytes of information collected every day — and it is only going to get worse as more capabilities come online.
It is a large enough problem that the National Security Agency included a special subject line for research on “coping with information overload” in the National Intelligence Program Summary, also known as the “Black Budget.” The agency requested $39 million in fiscal year 2011 and $64.3 million in 2012 for that research. That request dropped to $48.6 million for its proposed 2013 funding, according to documents disclosed in August by the Washington Post.
The US Air Force, which runs a significant portion of the Pentagon’s space and airborne ISR assets, also is aware that its operators and analysts are in danger of being swamped by a wave of information. Experts say that automating ISR functions is going to be key.
iHLS – Israel Homeland Security
“We need to start processing [the data] without an overabundance of human intervention,” said Rob Mitrevski, Vice President for Environmental Intelligence/Integrated Sensing and Information Solutions at Exelis. “What we really want as humans is the answer. And the closer we can get to the answer without having to tell each and every piece uniquely what to do, the better off we’re going to be.”
Ideally, a system could be set up that looks something like this: An ISR asset is tasked to track a house and is told to note whenever someone enters the front door. If that criterion is met, it sets off another chained automated task — for instance, telling the asset to request another platform with a hyperspectral camera to come and check for a specific substance whenever someone enters the house.
In theory, it would operate like a classic “if-then” statement, used by computer programmers for years. Meanwhile, operators on the ground are no longer receiving gigabytes of data indicating that nothing is happening. Instead, they are being sent only relevant data to work with, leaving them less mentally taxed and potentially trimming the number of operators and analysts needed for each mission.
