With the continuous advancement of urbanization, traffic congestion has become a major problem in urban management. To solve this problem, this study designs and implements a set of intelligent traffic data analysis system. Background Based on the demand of urban traffic management, it is necessary to obtain, analyze and predict the traffic congestion situation in time in order to take corresponding measures for optimization.
The back end of the system is based on Flask framework. Requests library is used to crawl congestion information from the network in real time, and time series analysis technology is used to achieve congestion prediction function. The front-end interface adopts HTML5, CSS3, JavaScript and Bootstrap2 technologies, and realizes the visual analysis of traffic data through Echarts, so that users can intuitively understand the traffic situation. The system realizes the following functions: real-time crawling congestion information, congestion prediction, and visualization of traffic data. Through the system, the traffic management department can timely understand the urban traffic situation, predict the possibility of congestion, so as to take effective measures to alleviate traffic pressure and improve transportation efficiency.
The significance of this study lies in the design and implementation of a complete set of intelligent traffic data analysis system by combining a variety of technologies and frameworks, providing scientific and efficient decision support for urban traffic management, helping to improve urban traffic conditions and enhance residents' quality of life. Key words: Intelligent traffic data analysis system; BootStrap2; Flask
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