基于Netty的多源交通GNSS数据获取方法

Research on Traffic GNSS Big Data Acquisition Method based on Netty

随着城市化程度的不断深化,以大数据为基础的智慧交通在解决出行、管控交通、处理突发情况方面发挥着日益重要作用。GNSS技术具备定位精度高、自动化程度高与可测量点的三维位置与速率等特点,在智能交通中已成功应用。面对海量数据,为提升数据处理效率,优化数据传输框架,急需一种能够稳定传输多源高并发GNSS数据的方法,对数据进行稳定高效接收并进行多平台处理。基于Netty框架技术,对收集的GNSS数据进行收集、解析与转发,利用了Kafka集群实现数据的持久化,并针对具体的智能交通问题进行实践验证,将传统的简单数据处理统计转向智能辅助决策,全面提升了数据的获取与挖掘效率,为智能交通的数据资源整合奠定了基础。

With the development of urbanization,smart traffic based on big data plays an increasingly important role in solving travel,managing traffic,and dealing with emergency.GNSS technology has the characteristics of high positioning accuracy,high degree of automation and three-dimensional position and velocity of measurable points.GNSS technology has been successfully applied in intelligent transportation.Facing massive data,in order to improve data processing efficiency and optimize the data transmission framework,it is meaningful to explore a method for stably transmitting multi-source high-concurrency GNSS data,which make it possible to receive data and perform multi-platform processing stably and efficiently.Based on Netty framework technology,this paper collects,parses and forwards collected GNSS data,use Kafka cluster to realize data persistence and carries out practical verification for specific intelligent traffic problems.It turns traditional data processing statistics to intelligent assistant decision-making,which can improve data acquisition and mining.It has laid a foundation for the integration of data resources for intelligent transportation.