The problem with video surveillance cameras is that, usually, there are too many of them for one security staffer to monitor. In a typical large enterprise setup, a single officer might be monitoring dozens -- even hundreds -- of cameras simultaneously, making it impossible to immediately recognize suspicious activity.
"To be honest, it's sheer luck if a security officer spots something in an environment like that," says John Frazzini, a former U.S. Secret Service agent and IT security consultant. "If you get a security manager alone behind closed doors, a lot of them laugh about what a waste of money it is."
Frazzini recently signed on to serve as president of a new company -- Behavioral Recognition Systems, or BRS Labs for short -- that aims to stop that waste. BRS Labs, which is launching both its business and its technology today, has received 16 patents on a new video surveillance application that can convert video images into machine-readable language, and then analyze them for anomalies that suggest suspicious behavior in the camera's field of view.
Unlike current video surveillance gear -- which requires a human to monitor it or complex programming that can't adapt to new images -- BRS Labs's software can "learn" the behavior of objects and images in a camera's field of view, Frazzini says. It can establish "norms" of activity for each camera, then alert security officers when the camera registers something abnormal in its field of view.
"It works a lot like the behavioral software that many IT people use on their networks," Frazzini says. "It establishes a baseline of activity, and then sends alerts when there are anomalies. The big difference is that, until now, there was no way to do this kind of analysis on video images, because the data collected by the cameras wasn't machine readable. We had to invent a way to do that."
The BRS Labs software can establish a baseline in anywhere from 30 minutes to several hours, depending on how much activity the camera recognizes and how regular the patterns of behavior are. "If you're monitoring a busy highway, where traffic comes and goes frequently on a regular basis, [the software] learns very quickly," Frazzini says. "If you're monitoring an outdoor fence line when the camera sees only three or four actions all day, it will take longer."
Once the software is operational, it can "recognize" up to 300 objects and establish a baseline of activity. If the camera is in a wooded area where few humans ever go, it will alert officers when it registers a human on the screen. If it is monitoring a high fence line, it will send an alert when someone jumps the fence.
"The great thing about it is that you don't need a human to monitor the camera at all," Frazzini says. "The system can recognize the behavior on its own."
Because there are so many possible images that might cross in front of the camera, the BRS Labs technology will likely create a fair number of false positives, Frazzini concedes. "We think a three-to-one ratio of alerts to actual events is what the market will accept," he says. "We could be wrong."
Overall, however, the new technology should save enterprises money, because security officers can spend their time diagnosing alerts and less time watching their screens for anomalies. And the system is more accurate than human monitoring, he says.
"What we've seen so far is enterprises spending billions on video surveillance equipment, but having a lot of trouble proving a [return on investment]," Frazzini says. "What we're doing is helping them to get more out of that equipment."
The BRS Labs technology will be generally available in September. Pricing hasn't been finalized -- early implementations have ranged anywhere from $1,500 to $4,500 per camera.
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