Features Of Artificial Intelligence In Video Surveillance

Growth is now being seen in artificial intelligence for video surveillance and analytics which is helping to reduce the workload of security management staff.

By the use of ai in the manufacturing industry, significant benefits can be seen in enterprises in terms of generating alert notifications and detecting unusual incidents. Recognition of objects, face, events, intelligent image processing, remote asset management, and analytics are some of the main technologies that are helping to transform the camera-based security systems today.

Attention span better than humans

Most of the times, the security operators who are there to analyze the videos might miss some of the problematic activities because no one can be attentive 24/7.

As a remedy to this issue, AI can be trained to record and observe each and every detail and alert the operator in case of any unusual activity. AI can be trained in order to differentiate between normal and unusual activities, behavior, detect incidents or actions that are not normal. Also, AI can continue to function 24/7 at a high level of efficiency.

Object, face and event recognition

Artificial Intelligence provides real-time and proactive security. For some businesses, AI can also be used for the identification of physical, facial characteristics of the customers, which is called ‘faceless recognition’. In this type of recognition, a person’s build, height, clothes, gender, and posture are used to identify them in a crowd. Also, the activities of a person can also make him distinguishable.

 Remote asset management

Video analytics can identify whether the assets are being optimally used or they need to be maintained.

The main target of remote asset monitoring is to gain as many as possible return on assets (ROA), which can only be made possible using artificial intelligence for video analytics. Ideal machine conditions and performance metrics can be fed into the AI system to analyze the machine behavior patterns. This can be used to predict machine performance, and alert operators when to expect machine failures.  Predictive analytics can save big bucks by reducing machine downtime, which is the key to have an uninterrupted production process.

 Image processing for better analytics

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

In these cases, processing of the image can be used to improve the low-quality images and video clips to make it easier to extract meaningful data from them. Operators are able to easily analyze the improved images, and therefore they reduce the scope of unwanted incidents.

 Use of data deluge

A huge amount of data is collected during the video footage collections of the urban areas and public spaces. But this data is many times not utilized properly due to the legacy systems.

For deriving important insights from the video surveillance data, special software that works can be used to analyze huge data and create security alert notifications. The insights that are derived can be very useful for security operators, who can then take required actions to protect important assets and people.

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