Artificial intelligence has begun to have a significant impact on the industry, but the scope of its impact is not as far-reaching as the security field. New innovative solutions are not only released by established security vendors, such as Huawei, etc., but also released by smaller technology start-ups. Together, these solutions add value to the organization's security operations. Let us discuss how AI will affect the video surveillance industry in the near future.
1. Real-time monitoring
Initially, in the era of closed-circuit television cameras, video used to be streamed in real time on TV screens, but no meaningful analysis was made to analyze possible security incidents. The video surveillance solution at the time was always passive, and it is still in this state in most parts of the world.
Most organizations only use CCTV video recording when an incident occurs or when a large-scale security incident is perceived. Through real-time monitoring of video recordings, and intelligent analysis of how security incidents occur through AI, and what measures need to be taken to prevent security incidents, the use of AI has completely changed the scene.
Various large IT vendors have proposed AI solutions that can detect unattended objects such as luggage in airports and public places, so that security agencies can take timely action. Similarly, AI-enabled surveillance solutions can monitor people walking around in retail stores and identify those who may be theft.
2. More accurate than manual
The accuracy and reliability of CCTV surveillance are only the same as those of the people who monitor it on the screen.
However, as a human, the operator sometimes misses important safety clues, which may bring catastrophic consequences. Fatigue is another problem that people cannot watch videos often.
The advantage of an AI-based solution is that the machine can always remain accurate and can compensate for human defects. This can ensure that no detailed information is missed, and it can also improve the security of supervision.
3. Flawless technology deployment, such as object, event detection and facial recognition
AI technology brings excellent facial recognition, object recognition and event recognition functions, thereby providing active and real-time security. This has a wide range of applications for public safety, such as identifying criminals in crowds in large-space scenes.
Another interesting application is the marketing department of large companies. They need to identify high net worth customers from shop visitors in order to provide them with high value services.
Another key way to recognize people is faceless recognition, where the physical characteristics of the person (such as height, posture, and figure) can be used to identify them in a crowd. In addition, the mode of activity can be used in different environments to detect and find criminal acts, thereby improving the safety of the surrounding environment.
4. Image processing can be used for better analysis
Although ultra-high-definition cameras can be used to capture high-resolution images, they are still rarely used in video surveillance solutions. Because most images captured with this solution are of poor quality, especially in low light conditions. These will become an obstacle when performing meaningful data analysis on such videos.
Artificial intelligence can be used to sharpen low-quality images so that security personnel can extract meaningful and valuable information from them. It also helps to make full use of otherwise blurred images and videos for useful analysis by the naked eye.
Based on AI+ big data, through data processing, data sharing, data mining, data analysis, data application and other big data technologies, the AI video intelligent analysis platform EasyCVR developed by TSINGSEE Qingxi Video, internally integrated AI+ video intelligent analysis technology, can be used on the scene Automatic analysis of video surveillance images, such as target detection, target recognition, target tracking, face recognition, scene segmentation, character and vehicle attribute analysis, etc., through the understanding and description of target behavior in the surveillance scene to achieve higher accuracy Video surveillance recognition.
5. Make full use of data analysis
There is a network of cameras that can capture valuable security videos in important geographic locations. However, for meaningful analysis of such big data, traditional solutions cannot achieve more scenario expansion. Special software based on the latest technology is needed to process these massive amounts of data and create security alerts based on comprehensive data analysis. This will also enable security managers to interpret big data in a qualitative way and enable them to take critical steps to ensure safety.