Significance of Video Analytics
Like it or not, the world is becoming more and more digital. Therefore, more and more data is being captured and stored each day. Real-time video analytics solutions help us make sense of all this data.
As of 2023, over a billion surveillance cameras are estimated to be watching the world right now
Traditional video surveillance systems are not enough. Police departments are starting to use in-camera video analytics to help with crime prevention, retail businesses are using video analytics to reduce theft, and city councils are using video analytics to improve traffic flow. The possibilities are endless.
Intelligent video analysis may be helpful in unexpected sectors, such as retail, helping companies better understand consumers by analyzing their behavior in stores. Additionally, businesses can monitor consumer behavior such as gaze patterns, visit durations, and sales site locations. For example, they can show where customers cluster in the store or when they pick up a product and then put it back down again. Through this technology, retail businesses can improve their store layouts and displays to encourage customers to browse items more thoroughly.
There are three types of video algorithms in video analytics solutions:
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The first two of these strategies attempt to accomplish the same thing. They try to determine whether an undesirable or suspicious activity occurs in the video camera's field of view and notify the console operator of the occurrence. Each, however, follows a distinct path to arrive at its conclusion. For example, fixed algorithm analytics employ a pre-programmed algorithm that does not change unless a security system administrator or engineer changes the program itself.
Artificial intelligence learning algorithms, on the other hand, are adaptive, which means that they automatically learn from their environment within specific parameters set by their developers. Therefore, these solutions become more accurate at detecting suspicious activity over time for system administrators.
A facial recognition systems approach to video analytics is also adaptive. But unlike other forms of intelligent video analysis software, they utilize specific computer vision techniques to compare images within the camera's field of view with known photographs or videos that have been tagged as potential threats. And just like the first two types of video algorithms, this type of technology is also pre-programmed to look for specific individuals or objects. The facial recognition software may be helpful on dating sites where users can upload a profile picture. This way, users can find out if their prospective mate is a serial dater or if they have been married before. Some financial institutions also use the technology to allow customers to deposit checks with video security systems that analyze their behavior as they complete the transaction.
To sum it all up, video analytics, be it edge-based or server-side is a very useful technology and becoming fairly accessible these days.
Looking for a video analytics solution?
Prodcrew provides cutting-edge video analytics solutions which can be installed at your premises or backed by our high-performance servers. contact us to know more.