Traffic Flow Monitoring Platform On Web Based On J2EE

The development of ITS(Transportation System Intelligent, ITS) is of great significance to improve the efficiency of social production and reduce environmental pollution. And ITS greatly save the travel time of people. On the other hand, traffic flow monitoring in the framework of intelligent transportation system is an indispensable function of ITS. In order to provide users with real-time and intuitive traffic information, this paper focuses on the realization of ITS traffic flow monitoring platform. And this paper designed and developed a Web traffic flow monitoring service platform based on J2 EE standard, which is suitable for browser access.According to the demand analysis, five functional modules had been designed, including authority management, traffic data in real time, dynamic map, traffic data statistics and historical data, equipment condition monitoring and sensor network state control. Taking into account the scalability of the system in the future, this paper also makes a preliminary study on the technology of big data. A large data traffic data processing algorithm is designed to provide people with more comprehensive traffic information.In the system implementation, the platform uses HTML5 to realize the response page and uses Hibernate, Struts2 and Spring framework to achieve the system background. Therefore the system can handle HTTP requests as needed and complete the storage, analysis and visualization of the traffic data. At the same time, the data communication protocol is designed with the Mina framework, which realizes the data transmission between the traffic flow monitoring platform and the sensor network. So users can get real-time traffic information and send device control commands. Finally, a large data processing platform is built in the virtual machine. And the peak traffic data search algorithm is realized by using the Hadoop framework.The test results of the traffic flow monitoring platform show that the function of each module of the system is normal, and the expected design goal is achieved. Test results in the Ubuntu virtual machine environment also show that the big data processing platform works well. Peak traffic data search algorithm is correct.