AI-based video surveillance and analytics are seeing growth in adoption, owing to their ability to reduce the workload of security staff and management. Using artificial intelligence in video analytics can bring significant benefits to enterprises in terms of detecting unusual incidents and generating alerts. Object recognition, face recognition, event recognition, remote asset management, intelligent image processing, and analytics are some of the key technologies that are transforming camera-based security systems today.

Artificial intelligence can be harnessed to radically increase the efficacy of the surveillance systems by driving human attention towards things that can compromise the security by sending them real-time alerts.

AI can be trained to observe every detail and notify the operator in case of any unusual activity found on the video feed. It can be trained to learn what typical activities in a scenario look like and detect incidents, behavior, or actions that do not follow the usual pattern. And, of course, AI can continue to function at a high level of efficiency round the clock, unaffected by mental or physical fatigue.

Surveillance cameras do provide the facility of capturing high-resolution images and videos, yet most of the systems do not use it for video surveillance. Therefore, most of the images or video clips captured and analyzed by the operators are of low quality. This issue can prevent operators from delivering accurate analysis reports and increase the chances of missed incidents.

In such a case, image processing can be used to sharpen the low-quality images and video clips to make it easier to derive meaningful data from them. Operators can easily analyze the improved images, thereby reducing the scope of undesirable incidents.