Subway crowd behavior label identification method based on base station position

Abstract

The invention discloses a subway crowd behavior label identification method based on a base station position, and the method comprises the following steps: S1, obtaining the user data of a subway operator base station, processing the user data, and obtaining the position of a cellphone user time dimension; S2, building a subway crowd recognition model: enabling the operator base stations to correspond to subway stations, building a subway region configuration table, and recognizing subway crowds; and S3, establishing a crowd label model, and performing statistics to obtain the number of inbound people, the number of outbound people and the number of exchanged people of the subway station in a fixed time interval. According to the method, the metro crowd behavior label is obtained by combining operator user signaling data, base station positions and a modeling algorithm. In combination with a previous subway crowd monitoring means, subway crowd monitoring is completed through another scene, and automation and precision are achieved.

Description

technical field [0001] The invention relates to the field of rail transit monitoring, and more specifically, to a method for identifying subway crowd behavior tags based on base station locations. Background technique [0002] In recent years, my country's urbanization process has entered the stage of accelerated urban development. The urban population has increased sharply. The over-development of the central urban area has led to a high concentration of population, which has led to a sharp increase in the total amount of traffic and increased pressure on urban rail transit. For this reason, many cities build subways to alleviate the pressure of urban road traffic. The subway has the following characteristics: strong passenger capacity, not affected by the environment, independent operation and no pollution to the environment, so it is very popular among travellers. Statistics show that in first-tier cities, the proportion of people using the subway to travel has reached mo...

AI Technical Summary

Problems solved by technology

[0003] At present, the transportation management department monitors the subway crowd mainly through manual methods such as the naked eye observation of the on-site security personnel and the observation of the crowd density by the monitoring camera. However, the card swiping data can only monitor the number of people entering the station, and cannot count the number of actual subway stations. number of people

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