Method and device for information processing of campus shared bicycles based on wi-fi logs

Abstract

The present invention relates to a method and device for processing information about sharing bicycles on campus based on Wi-Fi logs, wherein the method includes campus map segmentation; Wi-Fi log collection: collecting a certain amount of user equipment Wi-Fi connection logs, screening mobile equipment for Data builds historical datasets; spatiotemporal trajectory extraction: extracts the spatiotemporal information of users in Wi‑Fi logs to form historical trajectories; time series forecasting: generates statistical data sets of regional people flow, builds prediction models, and realizes regional population, inflow, and outflow traffic Long-term and accurate forecasting; research on delivery strategy: According to the forecast results of people flow, design resource demand metrics, and select the bicycle delivery area and delivery ratio based on this. Compared with the prior art, the present invention takes the campus Wi-Fi log as the starting point, quantitatively analyzes the actual change of the flow of people in each area, and uses the deep learning model for long-term accurate prediction, which can improve the utilization rate of shared bicycles on campus.

Description

technical field [0001] The invention relates to the field of campus shared bicycle delivery, in particular to a method and device for processing information of campus shared bicycle delivery based on Wi-Fi logs. Background technique [0002] With the promotion of the concept of sharing economy and the development of Internet of Things technology, its representative product, shared bicycles, is rapidly popular in major cities in China. Over the years, the shared bicycle business has been continuously optimized and developed, and the bicycle quality, app experience, and vehicle coverage have been substantially improved. On college campuses, shared bicycles are also a convenient, low-carbon and affordable way to travel, which is favored by teachers and students. [0003] In colleges and universities, during weekdays from Monday to Friday, teachers and students go out less often, and bicycles often flow in closed campuses; while on weekends from Saturday to Sunday, some bicycle...

AI Technical Summary

Problems solved by technology

However, due to the lack of influence of the campus environment, neither the space nor the time of delivery is detailed enough, which still results in a certain degree of low utilization rate of bicycles.

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