Video Intelligent Analysis Framework for Edge Computing

The vigorous development of the security monitoring and the use of a large number of high-definition cameras have brought difficulties in the storage and calculation of video data. The cloud framework represented by Hadoop has the disadvantages of strong dependence on bandwidth resources and low real-time performance. This paper makes use of the advantages of edge computing in the areas of marginalization and distribution, and proposes an intelligent analysis framework based on edge computing, which transfers the analysis and computing tasks from the cloud to the edge. Using index files to upload the result data of edge nodes reduces the dependence on network resources. The primary key structure with data item semantics is designed to optimize the query speed and reduce the data response delay, thereby improving the real-time performance. Finally, the experiment proves the superiority of the framework in terms of bandwidth and delay.