基于边缘计算的超限检测系统数据融合应用研究

Research on data fusion application of overload detection system based on edge computing

超限检测系统是实现交通运输数字执法的重要手段之一,其检测数据的有效采集与融合应用对提升执法效能具有重要意义。文章通过梳理江苏省超限检测站点及终端设备的运行情况与数据采集情况,分析其在终端设备接入、数据质量、数据传输与存储等方面存在的问题,进而提出引用边缘计算单元、“微治超”系统和超载案件证据自学习与违法对象画像分析功能,实现多源异构检测数据的自动汇聚和预处理分析,进一步扩充超载检测站点的监测治理能力,实现交通资源利用率最大化。

Overload detection system is one of the important means to realize the digital law enforcement of transportation, and the effective collection and fusion application of its detection data is of great significance to improve the efficiency of law enforcement. By sorting out the operation and data collection of the overload detection stations and terminal equipment in Jiangsu Province, this paper analyzes the problems existing in terminal equipment access, data quality, data transmission and storage, and then proposes the use of edge computing unit, “micro-overload-control”system, self-learning of overload case evidence and analysis of illegal object portrait,automatic aggregation and preprocessing analysis of multi-source heterogeneous detection data are realized to further expand the monitoring and governance capacity of overload detection stations and maximize the utilization rate of traffic resources.