Radars are superior to other outdoor sensors in terms of detection performance, but when used independently, they have certain disadvantages.
Perimeter security solutions make use of several different kinds of sensors and devices, including radar. Radars are superior to other outdoor sensors in terms of detection performance, but when used independently, they have certain disadvantages. The AI upgrades the radar from a good detector to an excellent security system, especially to protect perimeters.
Speaking to asmag.com recently, Amit Isseroff, VP of R&D at Magos Systems, explained that radar is weather and lighting tolerant, making them ideal for round-the-clock security. However, radar technology inherently suffers from relatively “low” resolution compared to video surveillance. This renders them less suitable for differentiating and classifying the detected object, increasing the rate of false alarms.
“In simple terms, the AI augments the radar’s detection quality by filtering out nuisance alarms based on input from surveillance cameras,” Isseroff said. “While this sounds simple, it is a challenging task to use it properly. True synergy is achieved by enjoying the best of both worlds without compromising radar detection quality.”
How AI works with radar
Instead of relying solely on the radar input to declare a detection, a PTZ camera is first sent to explore the potential threat. As the radar can accurately place the threat, the resulting image from the PTZ is centered and zoomed in on the target (as opposed to a generic video analytics solution where the camera is zoomed out for maximum coverage).
“This image is then processed using neural network technology to provide accurate object detection and classification,” Isseroff said. “The data from the AI engine is fused with the input from the radar to provide an overall accurate indication of the threat’s classification and location.”
The advantages of radar with AI
The obvious and most remarkable advantage is superior all-weather detection quality with minimum false alarms, which reduces required monitoring manpower while keeping them alert by providing accurate information on intruders.
“For example, a lot of energy companies have remote substations and facilities in rural areas,” Isseroff added. “The conventional security solution used for these facilities was based solely on video analytics or combined analytics with indicative perimeter fence products. These solutions tend to suffer from false alarms during harsh weather and provide less than ideal coverage and detection at night or in poor lighting conditions.”
To cope with poor detection performance, the systems are tuned to increased sensitivity, further increasing the false-alarm rate and increasing the manpower required to remotely and locally observe the site (either through remote video or by physically reaching and patrolling the area to verify the alarms).
“A solution based on radar alone is less than ideal as these types of facilities are often surrounded by wildlife,” Isseroff continued. “For example, one such facility had more than 100 nuisance alarms over one weekend generated by a raccoon, a squirrel, a raven, and even a deer. Even if those can be monitored and acknowledged remotely, one such site is almost a full-time job for the monitoring person who will eventually lose faith in the system and probably miss a real intruder due to reduced vigilance.”
Boosting radar performance for perimeter
In the example Isseroff provided above, an AI solution applied to the site reduced the number of nuisance alarms to less than one per day. PTZ cameras were automatically cued to the potential threats, and the AI engine filtered out all the wildlife.
“The accurate positioning of the camera, based on input from the radar, allows better video detection and classification performance compared to conventional video analytics that relies on zoomed out images and video motion detection (VMD),” Isseroff said.
Since the radar provides the detection layer, each separate video frame is useful for detecting an object, requiring less time to classify. On the other hand, in VMD alone, a single object must be tracked for several frames before recognizing it as moving. Hence bad lighting conditions or harsh weather have minimal impact on the system’s detection performance.
An optimal integrated system
In short, radar integrated with video analytics is an excellent option for perimeter security, especially to protect large areas. They make a great addition to security systems, working alongside other solutions like access control and normal video surveillance.