With the continuous improvement of user security monitoring requirements, high-definition has become a new trend in the development of network video, and high-definition video has also been more widely used in the fields of transportation, medical care, retail, and finance. However, due to the large amount of data transmitted and stored, high-definition video places higher requirements on network bandwidth and back-end storage, which has become the biggest obstacle to the large-scale application of high-definition video. As a leader in the global network video field, Axis uses the open network platform to achieve intelligent front-end applications, which fundamentally solve the obstacles of high-definition video applications.
It is understood that the intelligent video function of the current network video system is mainly realized by the center analysis method. Through the video management software of the back-end server, the video stream transmitted by the front-end camera is intelligently analyzed, thereby realizing the intelligent processing of the front-end video information. . With the growth of the system scale, this method puts tremendous pressure on back-end storage management and transmission bandwidth. It needs to be solved by improving the performance of back-end equipment, such as increasing the server configuration, increasing the number of servers and switches, and finally This has led to an increase in the cost of video systems. Taking the Ping An City project as an example, in the entire security monitoring system, the investment budget for storage servers is up to 30%, the network and cameras are 20% each, and the software accounts for 10%. Therefore, it can be seen that the back-end storage costs are reduced. It is the key to reducing the total cost of network video systems.
In order to solve such problems encountered in the development of high-definition video, Axis put forward the concept of "smart front-end" to realize the full intelligence of the monitoring system. Axis has an independent processor, mainly through the front-end embedded video analysis services for intelligent analysis of video information, the pressure of the back-end storage server is dispersed to all front-end video equipment, thereby further reducing the transmission bandwidth and the central server The pressure meets the storage space requirements for high-definition surveillance video. More importantly, the intelligent identification capability of the front end can determine whether the data information is useful, avoid redundant information occupying a large amount of storage space, and effectively reduce the pressure on the back-end storage costs.
In addition, Axis' “smart front-end†is based on its open platform and cooperates with third-party partners to develop more intelligent analysis applications and deploy it to front-end network cameras to meet the user's personalized video surveillance requirements. This also means that The same Axis network camera can implement differentiated functions by deploying different intelligent front-end applications.
In today's widespread use of high-definition network video, AXIS's intelligent front-end application not only realizes the intelligentization of front-end monitoring devices, but also greatly reduces back-end storage pressure, reduces storage costs, and achieves targeted signal transmission. While improving transmission efficiency and reducing total costs, it will also accelerate the application of high-definition video and promote the mature development of domestic online video market.
It is understood that the intelligent video function of the current network video system is mainly realized by the center analysis method. Through the video management software of the back-end server, the video stream transmitted by the front-end camera is intelligently analyzed, thereby realizing the intelligent processing of the front-end video information. . With the growth of the system scale, this method puts tremendous pressure on back-end storage management and transmission bandwidth. It needs to be solved by improving the performance of back-end equipment, such as increasing the server configuration, increasing the number of servers and switches, and finally This has led to an increase in the cost of video systems. Taking the Ping An City project as an example, in the entire security monitoring system, the investment budget for storage servers is up to 30%, the network and cameras are 20% each, and the software accounts for 10%. Therefore, it can be seen that the back-end storage costs are reduced. It is the key to reducing the total cost of network video systems.
In order to solve such problems encountered in the development of high-definition video, Axis put forward the concept of "smart front-end" to realize the full intelligence of the monitoring system. Axis has an independent processor, mainly through the front-end embedded video analysis services for intelligent analysis of video information, the pressure of the back-end storage server is dispersed to all front-end video equipment, thereby further reducing the transmission bandwidth and the central server The pressure meets the storage space requirements for high-definition surveillance video. More importantly, the intelligent identification capability of the front end can determine whether the data information is useful, avoid redundant information occupying a large amount of storage space, and effectively reduce the pressure on the back-end storage costs.
In addition, Axis' “smart front-end†is based on its open platform and cooperates with third-party partners to develop more intelligent analysis applications and deploy it to front-end network cameras to meet the user's personalized video surveillance requirements. This also means that The same Axis network camera can implement differentiated functions by deploying different intelligent front-end applications.
In today's widespread use of high-definition network video, AXIS's intelligent front-end application not only realizes the intelligentization of front-end monitoring devices, but also greatly reduces back-end storage pressure, reduces storage costs, and achieves targeted signal transmission. While improving transmission efficiency and reducing total costs, it will also accelerate the application of high-definition video and promote the mature development of domestic online video market.