Improving Security : Artificial Intelligence for Video Surveillance - Part 1
As one of the most widely used and efficient methods for improving security systems, artificial intelligence (A.I.) is rapidly changing the nature of video surveillance. With computer software programs utilizing machine vision and a series of algorithms to compare objects seen with stored reference images of humans, A.I. technology can analyze videos taken from surveillance cameras and detect potential threats, including humans, vehicles, objects, attributes, and events.
One of the most significant advantages of A.I. in video surveillance is that it can operate continuously, maintaining surveillance of hundreds of cameras simultaneously. By using A.I. technology in security systems, users can set rules for all possible alerts, and A.I. can detect and alert users instantly when there is a breach.
A.I. technology in video surveillance has evolved from earlier attempts to resolve problems like limitations in humans' ability to monitor live video surveillance footage. Motion detection cameras and advanced video motion detection were some of the initial solutions, but were not very effective for distinguishing the human form, vehicles, and selected objects from the general movement of all other objects and visual static or changes in pixels on the monitor.
Using A.I. technology in video surveillance has provided cost-effective and reliable solutions for detecting potential security breaches. For instance, rules could be set for using a "virtual fence" or intrusion into a pre-defined area. A.I. technology is also capable of overcoming the limitations of traditional vigilance-based solutions by monitoring all cameras' images simultaneously.
Behavioural analytics is a type of A.I. that continuously classifies objects and events seen by video cameras. The system recognizes patterns in human behavior and detects things that are out of the ordinary in active environments. However, behavioral analytics has its limitations, as it samples down to a low resolution of only 1 CIF to conserve computational demand, meaning that objects more than sixty to eighty feet distant may not be detected.
Despite its limitations, A.I. technology has better visual acuity than humans or the machine approximation to it and can handle very large datasets requiring simultaneous calculations in multiple remote viewed locations. Humans remain far superior at judging subtleties of behaviors or intentions of subjects or degrees of threat and take over the function of assessment and response.
The potential of A.I. in the form of behavioral analytics to proactively intercept and prevent incidents is significant. This technology can identify unsafe employee behavior that may result in incidents, thereby preventing consequential damages that are about six times the direct insured cost. Consequential losses are often under-assessed since direct costs of potential losses are often the only ones considered.
Atlast, I can say A.I. technology in video surveillance has revolutionized security systems by providing cost-effective and efficient solutions. With continued development, A.I. technology will become even more critical in detecting potential security breaches and preventing consequential losses.
