Campus shared bicycle delivery information processing method and device based on Wi-Fi log

Abstract

The invention relates to a campus shared bicycle delivery information processing method and device based on a W-iFi log. The method comprises the following steps: segmenting a campus map; Wi-Fi log collection: collecting a certain amount of user equipment Wi-Fi connection logs, and screening data of mobile equipment to construct a historical data set; space-time trajectory extraction: extracting space-time information of a user in the Wi-Fi log to form a historical trajectory; time sequence prediction: performing statistics to generate a regional pedestrian flow data set, constructing a prediction model, and realizing long-term accurate prediction of the number of people, the inflow and the outflow of the region; and release strategy research: designing resource demand measurement according to a pedestrian volume prediction result, and selecting a bicycle release area and a release proportion based on the resource demand measurement. Compared with the prior art, the method takes the campus WiFi log as a starting point, quantitatively analyzes the actual change condition of the pedestrian volume of each region, and adopts the deep learning model to carry out long-term accurate prediction, so that the utilization rate of the campus shared bicycle can be improved.

Description

technical field [0001] The present invention relates to the field of campus shared bicycle delivery, in particular to a method and device for processing campus shared bicycle delivery information 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 becoming popular in major cities in China. Over the years, the bike-sharing business has continued to optimize and develop, and has substantially improved bike quality, app experience, and vehicle coverage. On college campuses, shared bicycles are also a convenient, low-carbon, and affordable way of travel, and are favored by teachers and students. [0003] In colleges and universities, during weekdays from Monday to Friday, teachers and students are less likely to go out, and bicycles tend to flow in closed campuses; while weekends from Saturday to Sunday, as students go...

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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