Have you ever caught yourself nodding off at work? Now imagine staring at a monitor for long hours without a break. You look at grainy images of parking lots, storage containers or perhaps construction equipment, night after night, and nothing exciting ever happens. Well, almost never. Welcome to the life of a security guard doing video surveillance.
One study has found that after 20 minutes, security guards watching a video scene will miss up to 95 percent of all activity. Other studies echo this 20-minute rule. The poorer the image quality on the video, the faster security operator performance worsens.
Viewing multiple monitors also rapidly accelerates this worsening behaviour. Studies have shown that doubling the number of monitors doubles the rate at which security operator performance degrades. In 2008, a study showed that operators miss 60 percent of targets when they are watching nine monitors—versus only 20 percent when they watch only four.
Understandably, then, a high-tech security system providing more information to the guard will not solve this problem. In fact, too much information only confuses the security guard and makes the job even more exhausting. The solution, then, lies in filtering out unnecessary information, alerting the professional to items of interest and improving image quality.
In short, high-definition video analytics can significantly reduce human fatigue—but not all video analytics systems are created equal.
The most basic video analytics software detects motion by flagging any change from one frame to another. A parked car or fluttering leaf moving across the screen may trigger an alert.
More advanced motion detection is based on an established background model. Changes that don’t fit that background model indicate movement. For example, the system may be set up to recognize what a construction pit is supposed to look like. If a person climbs on a crane, the event-triggered security system sets off an alarm. However, if a cat climbs aboard or heavy rain or snow hits the site, the system may trigger a false alarm. The background model must be continually adjusted to adapt to changing conditions.
Advanced video pattern detection (AVPD), meanwhile, is based on algorithms that track the movement patterns of known objects, such as people and cars. This technology focuses on how an object moves to determine what it is. This type of video analytics technology is the most effective at reducing false alarms.
By mimicking how people zero in on moving objects to determine whether they are a threat, AVPD highlights the most relevant information and helps reduce a security guard’s fatigue.
The second piece of the puzzle is high-resolution images. Security operators can pay sustained attention to a high-quality video much easier than a blurred or grainy one. High-definition video has another benefit: the ability to cover a wide area and zoom in on areas of interest. This, in turn, means fewer cameras, thus addressing the third problem: too many monitors.
When choosing a security provider for remote video monitoring, ensure the company uses high-definition video analytics with AVPD to reduce false alarms and the risks of human fatigue.
Source: Enhancing human attention span with HD Analytics. Avigilon, 2014