Design And Implementation Of New Energy Vehicle Data Detection And Processing System Based On Big Data

With the rapid development of the Internet of Vehicles,information mining of vehicle driving data has become increasingly important.Through the massive data in the vehicle network platform,the behavior characteristics of new energy vehicles are analyzed,and the information behind the driving data of the vehicle can not only strengthen the state’s supervision of the new energy vehicle industry and protect the legitimate rights and interests of new energy vehicle users.Use these data to observe the distribution of new energy vehicles in all provinces,cities,and regions across the country,as well as the driving laws,to understand the overall situation of the national new energy vehicle industry and policy subsidy data,to collect the battery products of various models of vehicles and the distribution of new energy charging piles across the country It will have a detailed understanding of the entire new energy automobile industry,so as to provide data reference for the government to introduce various related policies.For vehicle manufacturing and sales enterprises,by analyzing the vehicle status data of each model,establishing related models,predicting battery life,and providing data support for improving product quality.Therefore,public data collection and analysis research based on new energy vehicles is of great significance.The main research and work of this article are as follows:1.Introduction and analysis of several major big data technologies used in the system,such as distributed storage technology HDFS,big data processing technology Spark,etc.2.Study two key issues in the analysis model of behavioral characteristics of new energy vehicles:vehicle mileage verification and identification of multiple data terminals loaded on the same vehicle;3.Requirement analysis of the final new energy vehicle data detection and processing system,first of all,the data source and approximate scale required for system data analysis;secondly,analyze the functional and non-functional requirements of the system from the perspective of big data underlying data processing;4.Design the overall architecture of the system,elaborate from two aspects of physical architecture and logical architecture,and focus on the complete design and implementation of the three modules in the underlying business requirements,namely the mileage verification module and the multi-terminal data screen.Search module and vehicle abnormal data statistics module.The system analyzes the uploaded vehicle data and stores it in the Hadoop distributed file system.At the same time,Spark technology is used as the big data calculation model of the system architecture.The calculation results are stored in HBase and MySQL for data according to different scenarios.Visual use.Give full play to the efficient data processing methods of Spark RDD and Spark SQL,and improve the efficiency of system processing and analysis.