Personal trajectory detection method and device, electronic equipment and storage medium
By combining the weighting coefficients of multiple data sources, the reliability of a person's location is determined, thus solving the trajectory detection error caused by a single data source and achieving higher-precision personal trajectory analysis.
CN115563449BActive Publication Date: 2026-07-21BEIJING WANGRUIDA TECH CO LTD
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Patent Information
- Authority / Receiving Office
- CN · China
- Patent Type
- Patents(China)
- Current Assignee / Owner
- BEIJING WANGRUIDA TECH CO LTD
- Filing Date
- 2022-09-02
- Publication Date
- 2026-07-21
AI Technical Summary
Technical Problem
In existing technologies, when detecting personal trajectories using a single data source, there are missing location data and errors, resulting in low detection accuracy.
Method used
Using various data sources, such as access control card swipe data, facial recognition data, and wireless network data, the weighted credibility of a person's location is determined by calculating the weight coefficients of preset indicators, and the individual's trajectory is obtained based on the relationship between the weighted credibility and preset thresholds.
Benefits of technology
It improves the accuracy of personal trajectory detection, reduces errors caused by a single data source, and enhances the precision of trajectory analysis.
✦ Generated by Eureka AI based on patent content.
Smart Images
Figure CN115563449B_ABST
Abstract
The application provides a personal trajectory detection method and device, electronic equipment and a storage medium, and relates to the technical field of data processing. The method comprises the following steps: acquiring at least two different types of data sources associated with personnel position information; obtaining a weight coefficient of a preset index according to the data sources, wherein the preset index comprises at least one of a data source type, a number of continuous appearances of the data source representing that the personnel is at the same position within a continuous time period, and a time difference between a current position and a previous position of the personnel; determining a weighted credibility that the personnel is at a target position according to the weight coefficient; and obtaining a personal trajectory of the personnel according to a relationship between the weighted credibility and a preset threshold. The detection error when detecting the personnel trajectory through a single data source is reduced, the trajectory of the measured personnel can be analyzed in combination with multiple different types of data sources, and the personal trajectory data accuracy is improved.
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