Video stream analysis system and method based on end-edge-cloud computing architecture

Abstract

The invention discloses a video stream analysis system and method based on an end-edge-cloud computing architecture. The system comprises a cluster control module, a front-end display module, a rear-end service module, a front-end display module, a rear-end display module, a front-end display module, a rear-end service module, a request analysis module, an intelligent analysis module, a distributed storage module, a database module and a message queue module. The cluster control module is connected with all other modules; the front-end display module is connected with the back-end service module and the request analysis module; the intelligent analysis module is connected with the request analysis module, the message queue module and the back-end service module; and the back-end service module is connected with the front-end display module, the intelligent analysis module, the distributed storage module, the database module and the message queue module. According to the end-edge-cloud video streaming system, the rapid deployment and starting characteristics of the Docker container technology are combined, and the reliability, usability and expandability of the system are improved in multiple aspects through the designed end-edge-cloud video streaming system.

Description

technical field [0001] The present invention relates to the technical field of video stream analysis, in particular to a video stream analysis system and method based on an end-edge-cloud computing architecture. Background technique [0002] In recent years, the rise of convolutional neural networks has promoted the rapid development of video stream analysis applications, and created high-efficiency, high-accuracy intelligent analysis levels. Surveillance cameras mainly produced by companies such as Hikvision and Dahua Technology are widely deployed in China. Some surveillance cameras themselves have the ability to analyze video streams. This type of intelligent surveillance camera can "self-produce and consume" surveillance video streams with high efficiency. However, intelligent surveillance cameras are limited to one or several specific intelligent analysis algorithms, such as only face intelligent analysis or vehicle intelligent analysis, and it is not easy to carry out...

AI Technical Summary

Problems solved by technology

However, intelligent surveillance cameras are limited to one or several specific intelligent analysis algorithms, such as only face intelligent analysis or vehicle intelligent analysis, and it is not easy to carry out secondary development on it, so its It is not suitable for complex application scenarios where intelligent analysis algorithms need frequent iterative updates and multiple intelligent analysis algorithms need to be used at the same time

Images