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Surveillance technology provides a vital shield

against terrorism, and cheap modern electronics make it easy to fill the city streets with closed-circuit television (CCTV) cameras. New York City mayor Michael Bloomberg recently toured London's ring of cameras, seeking information on how to bring it to the Big Apple to thwart terrorist attacks. But unless the feeds from those cameras are constantly monitored, they only provide an illusion of security. Finding enough eyeballs to watch thousands of screens simply isn't practical, yet modern automated systems can fill the gap with a surprising degree of intelligence.

The Automated Warning and Response Engine (AWARE) from Abeo Technical Services is one such system. It replaces the traditional banks of screens with a single view, combining the images from many cameras to give a picture across the entire area under surveillance. It makes it possible to zoom in to a single room, or zoom out to a bird's-eye view. And instead of relying on humans to scan for potential threats, the software will actually analyze the video itself.

The Times Square Example

Let's look at how this type of system would deal with an event like the failed car-bomb attack in Times Square: The vehicle involved was parked in a No Parking area, the emergency warning flashers were going, and smoke was pouring out of it. All of these were potential warning signs. If the system issued an alert every time a car was parked illegally, there would be a lot of false alarms. But AWARE can cross-check all illegally parked cars without human intervention.

"Should a vehicle be detected parked illegally, AWARE would aim a local camera at the license plate, and License Plate Recognition software would interpret the number," says Robert Allen of AbeoTS. "AWARE would submit the data to the appropriate DMV and the result would be analyzed for threat potential. In the Times Square incident, this would have triggered a threat as the license plate did not match the vehicle."

AWARE can detect other anomalies such as flashing lights and smoke. Any event or combination of events can be set to trigger an alert. The system is not limited to video cameras but can be networked to other sensors. These can be anything from radar motion sensors to explosives sniffers or radiation detectors. And just as it can link to license plate recognition, the system can plug into facial-recognition systems or even iris recognition if suitable image databases are available.

Having detected an anomaly, AWARE uses all available resources. This would typically involve recruiting other sensors, such as PTZ (pan, tilt, zoom) cameras which can get a more detailed look and confirm what was happening. The software is trained to recognise common events which might be mistaken for threats to cut down on false alarms.

If the threat is determined to be real, the system moves on to the next stage, sending out alerts to responders' cellphones, radio, pagers and other receivers. It can follow this with further updates if the event escalates. With this sort of setup, the responder's role is shifted from being just a screen-watcher to being a decision maker, whether this is a false alarm or time to start calling out the emergency services.

Camera imagery can then be sent to smartphones, PCs or tablets. Any HTML-capable device can view everything that could be seen in the control center. It also means that a responder can be moving around with an iPhone rather than stuck in the control center.

But Is AWARE Better Than Human?

How good is AWARE at spotting threats? The company says that when it is set up correctly, the software "has a higher probability of detection than a human observer." Allen accepts that it's a bold claim, but says that it's largely a matter of arithmetic. At a big site, even in a control room "wallpapered with monitors," there are only enough screens for a tiny fraction of the hundreds of cameras in place. And those dozens of monitors will only be assigned three or four human watchers, whose rate of spotting threats will be correspondingly low.

Much of AWARE's current workload involves areas with a high volume of pedestrian traffic such as airports. The automated overwatch comes into its own when it has to keep an eye out across multiple cameras for possible threats, such as unattended objects. "The application's rules processor is looking for articles which are stationary in locations where there should be no unattended articles which are stationary for certain periods, typically minutes," Allen says. "The technology also monitors camera systems for persons suddenly in the prone position which might indicate an accident or an assault."

Two other popular features are being able to watch for unusual crowding in an area, and a "follow me" capability which allows individuals to be tracked as they move from the field of view of one camera to another. This would be used to follow anyone who, for example, came the wrong way through an exit-only door, though Allen says in practice offenders tend to be apprehended before they get very far.

These features amount to a substantial automated surveillance capability, making it possible to protect much larger areas than human observers can manage.

And as processors get more powerful, cameras gain in resolution and algorithms get smarter, this type of system will continue to get even better. When you next look up at a security camera, there could be only a machine staring back.

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