An End-Edge-Cloud Based Method of Business Data Sign and Collaborative Processing for the EMU Bogie

Abstract

Traditional EMU bogie business data production and processing are concentrated at the edge. Today, under the background of big data, cloud computing, and artificial intelligence technologies, it is not only required to process a large amount of data but also the core task is to quickly complete data mining processing and to explore tacit knowledge. The end-cloud synergy architecture combines the end and the cloud to achieve complementary advantages. With an acceptable delay, the computing power shortage of the end can be solved, and the cloud's elastic distributed processing capabilities and rich data model-building capabilities can be used to improve the overall computing power and application ability. Aiming at the business data processing of EMU bogies, this paper proposes a data tag collaborative processing method architecture based on end-edge-cloud. The data is mainly marked at the edge layer. After sending to the cloud, the cloud can quickly scan, clean, classify, store, and process based on the data marking rules. Meanwhile, the labeled data can be used for model training to strengthen the model. This paper also builds a simulation system to conduct experiments to verify the effectiveness and advancement of the method.