Multi-channel VideoStreaming Technology for Processing Based on Distributed Computing Platform

Abstract

With the rapid development of the Internet, sensor network, and mobile Internet technology, a large number of data sets are continuously generated in the form of streaming in various application fields. At the same time, the processing of stream data has drawn more and more attention because of its application in different situations. To meet the urgent need for the processing of streaming data, there are many computing engines on the market, such as Spark and Flink. Traditional data-flow analysis has many problems in the process of streaming data, such as the high time delay, weak extensibility, and bad adaptability. In order to improve them, people use Kafka as the intermediate-cache and the computing engine that uses Spark Structured Streaming as the streaming data to realize the effective process of multichannel flow data. Considering the present demand for low latency and high flux that are analyzed by urban management in traffic video, processing the data of multichannel traffic video on distributed computing platform realized the tracking and search on motor vehicles, non-motor vehicles, and pedestrians of multiple roads and intersections.