AUSTIN, Texas — Analysts have forecast intelligent devices in perimeter security to top $200 million in 2013 as video surveillance and analytics are becoming an integral part of electronic perimeter security solutions.
Historically, sensors have been the primary means of detection for perimeter security applications. In recent years, though, a growing trend has developed for cameras and analytics to be used in addition to sensors on a perimeter, according to a report by research firm IHS.
Since before 2010, video and especially video analytics has remained the fastest growing portion of the perimeter security industry. Prior to that, perimeter security applications mostly offered detection without verification or identification. As more perimeter security systems integrate with video, users are seeing an enhancement in terms of efficiency and the reduction of false alarms, according to the report.
One of the most talked about perimeter security trends has been intruder identification. The report notes that the trend is partly being driven by the demand to lower false alarms, lower costs and the ability to provide patrols and guards in the field with real-time information on the location and status of an intruder.
Slew-to-cue surveillance functionality remains one of the top trends and uses of video for perimeter, especially when integrated with a ground surveillance radar. In its simplest form, video is integrated with a passive infrared (PIR) for video motion detection. Lastly, video analytics has two main forms: embedded on a device (camera, NVR, DVR or encoder) or centrally located and server based. To determine which video analytics offering is more robust with the most functionally is primarily dependent on customer requirements.
Although analytics is poised to alter the perimeter detection market, the perimeter security industry will continue to use multiple layers and will not rely solely on video, according to the report. Analytics has improved since its introduction to the market but false alarms continue to plague end users and programming/adjusting the analytics remains hands-on for installers. Additionally, the environment plays a large role in the accuracy of the solution. Very crowded areas do not work well for analytics, while sterile areas with fewer crowds help improve performance.
Overall, use of video has been limited in perimeter applications compared with sensors; however, this has begun to change with the degree of integration and reliance on identification. In the medium to long-term, video analytics may begin to displace more traditional sensors as a means not only to identify, but detect as well.