Industrial CCTV Surveillance System using smart video analytics to safeguard against fire-theft-intrusion and sabotage.
Protection of Factories and Industrial Assets
Advances in video analytics technology are made possible by advances in the underlying information technologies, such as computer processing power, memory speed, parallel processing, solid state and hard drive data storage, high-speed databases, high-capacity networking, and artificial intelligence (AI). Video analytics is actually a subfield of AI. Video analytics capabilities fit both of the definitions of AI below.
he capacity of a computer to perform operations analogous to learning and decision making in humans, as by … a program for the perception and recognition of shapes in computer vision systems.2
The ability of a computer or other machine to perform actions thought to require intelligence.3
The ever-accelerating pace of advancement for the underlying technologies provides the research and development (R&D) efforts in video analytics with ever more powerful tools with which to develop and refine video analytics applications.
Two important video analytics improvement trends include higher detection rates and lower false alarm rates. In the U.S. National Institute of Standards and Technology’s (NIST) assessment of biometric face recognition in still images, the error rate halves every two years. In 2010, the best face recognition method matched 92 percent of mug shots to one out of 1.6 million images.4 Since then, the video analytics technologies have continued to advance in quality and effectiveness.
One of the largest guarding companies in the world is already using video analytics to support its operators and as a backup for patrolling guards. Some smaller, specialized companies are even using the technology as the foundation for their entire business of providing security and remote guarding as a service.
With the help of strategically placed network video cameras and advanced video analytics, fewer operators can monitor more and larger installations 24/7, and they can react more quickly and adequately to incidents. Automatic alerts flag suspicious events in real time, including a person moving in or near restricted areas, loitering, or someone trying to tamper with property, including the video cameras themselves.
Once the video analytics application has alerted an operator about an incident, the operator can verify the alarm before sending a security guard. This way the number of false alarms and unnecessary emergency responses is kept down, and the guards can focus on the areas where they are needed most.
Sometimes, the only response to an incident that is required is to deter the intruder by letting him know he is being watched and recorded on camera. Connected horn speakers allow the operator to address the intruder, while the cameras transmit the intruder’s reaction. Not having to send out a guard in these instances can saves hundreds of dollars – a saving that is ultimately passed on to the end customer.
Video analytics applications are developing fast, and they are changing the way the security industry works. They are not going to replace security guards entirely, though – ultimately, it is always up to the operator to validate any alarms raised, and make the right decision on how to react.
In 2013, the world’s largest supplier of automotive components (which also provides 90 percent of Google’s autonomous driving software) announced that it had begun sharing video analytics technology with one of its sister companies, a security systems manufacturing company. This is a noteworthy example of how the security industry will continue to benefit from analytics advances in other industries, some of which — like the automotive industry — have R&D initiatives that are significantly better-funded and better-staffed than R&D initiatives within the security industry.
Overall, four key factors are driving the ever-accelerating advancement of security video analytics:
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