The article considers the results of research received by the authors in the process of developing and implementing the components of an intelligent monitoring system. The system is designed to collect and process big data on road incidents from photo-radar complexes. Monitoring system is the main part of the Smart Road Environment. The authors propose a convergent model for processing big sensor data, which includes three layers using fog, cloud and mobile computing technologies. Within the framework of the convergent model, the multi-agent approach for data processing is implemented. In the process of working on the project, software agents that perform data collecting, cleaning, clustering, comparing time series, retrieving data for visualization, preparing charts and reports, performing spatial analysis, etc. Big sensor data and other heterogeneous information from other sources (weather stations, video surveillance systems, mobile communication equipment, built-in car navigation equipment etc.) are collected. The results of data processing mining are presented. The comparison of time series of traffic accidents and time series of meteorological factors is established, that the presence of factors to become determinants for an abnormal change in the traffic situation in controlled areas.

本文考虑了作者在开发和实施智能监控系统的组件过程中获得的研究结果。该系统旨在收集和处理来自光电雷达综合体的道路事故大数据。监控系统是智能道路环境的主要部分。作者提出了一种用于处理大传感器数据的收敛模型，该模型包括使用雾，云和移动计算技术的三层。在收敛模型的框架内，实现了用于数据处理的多主体方法。在项目工作过程中，软件代理执行数据收集，清理，聚类，比较时间序列，检索数据以进行可视化，准备图表和报告，执行空间分析等。从其他来源（气象站，视频监视系统，移动通信设备，内置汽车导航设备等）收集大传感器数据和其他异构信息。给出了数据处理挖掘的结果。建立了交通事故的时间序列与气象因素的时间序列的比较，即存在因素成为控制区域交通状况异常变化的决定因素。