Design and Implementation of Intelligent Traffic Monitoring System Based on IOT and Big Data Analysis

智能交通系统 大数据 先进的交通管理系统 计算机科学 物联网 平面图(考古学) 浮动车数据 数据收集 集合(抽象数据类型) 工程类 运输工程 计算机安全 交通拥挤 数据挖掘 历史 统计 数学 考古 程序设计语言
作者
Yongling Chu,Yanyan Sai,Shaochun Li
出处
期刊:Lecture notes on data engineering and communications technologies 卷期号:: 400-410
标识
DOI:10.1007/978-3-031-31775-0_41
摘要

With the increasing rapidly of urban road traffic, traffic jam,causing traffic trouble, pollution of the environment and other problems are becoming increasingly serious. Therefore, intelligent transportation, which can understand the traffic conditions in real time and reasonably plan the traffic routes, is particularly critical to solve the above problems. At the same time, the economic loss of storage equipment and the technical constraints of data analysis and processing caused by massive traffic data collection to the background system also need new technical ideas and means to solve. At present, IOT technology, big data technology and machine learning technology are increasingly mature, and the combination of the three has natural application advantages in the monitoring and management of intelligent transportation. This paper proposes a solution to intelligent traffic condition detection and prediction by combining IOT, big data technology and machine learning technology. The Internet of things technology is used to solve intelligent transportation’s data collection, the big data technology is used to solve the storage question of massive data, and the machine learning technology is used to judge and predict the operation state of intelligent transportation. A set of monitoring systems that can be used for intelligent transportation are designed and implemented. The availability and effectiveness of the system are verified through experiments and tests.

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