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To address the privacy protection and data invalidation issues faced by traditional Origin-Destination(OD) crowd flow monitoring methods based on real MAC addresses, this paper proposes an anonymous OD crowd flow identification method based on Wi-Fi probe request information elements. By analyzing stable features in fields such as HT Capabilities and VHT Capabilities within probe requests, we design an enhanced DBSCAN clustering algorithm to accurately distinguish randomized MAC devices. To address cross-region trajectory matching, we introduce an OD association strategy leveraging information element group filtering and distance matrix computation. Experimental results in a public facility environment demonstrate a device clustering accuracy of 97.87% and an OD matching accuracy of 81.8%, validating the method's effectiveness. Compared to existing techniques, our approach achieves high precision and low computational complexity while preserving user privacy, offering novel insights for public safety, transportation planning, and emergency management.
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Basic Information:
DOI：10.13291/j.cnki.djdxac.2026.03.004
China Classification Code:TN92;U491.12
Citation Information:
[1]ZHU Chengjuan,ZHAO Xingji,CHEN Aitong.Pedestrian Origin-Destination(OD) Identification Method Based on Wi-Fi Probe Requests Under Randomized MAC Address Mechanisms[J].Journal of Dalian Jiaotong University,2026,47(03):36-44.DOI:10.13291/j.cnki.djdxac.2026.03.004.
Fund Information:
国家自然科学基金面上项目(72171033); 辽宁省教育厅科学研究计划项目(JDL2019037)
2025-03-12
2025
2025-05-19
2025-06-02
2025
1
2026-06-09
2026-06-09
2026-06-09