一种基于WiFi相异度的群组感知分析方法

doi:10.11896/jsjkx.200600014

计算机科学 ›› 2020, Vol. 47 ›› Issue (10): 63-68.doi: 10.11896/jsjkx.200600014

所属专题：群智感知计算

一种基于WiFi相异度的群组感知分析方法

贾玉福¹, 李明磊¹, 刘文平¹, 胡胜红², 蒋洪波³

1 湖北经济学院信息管理与统计学院武汉430205
2 湖北经济学院信息通信工程学院武汉430205
3 湖南大学信息科学与工程学院长沙410082

收稿日期:2020-05-31 修回日期:2020-09-02 出版日期:2020-10-15 发布日期:2020-10-16
通讯作者: 李明磊(liminglei@hbue.edu.cn)
作者简介:55245058@qq.com
基金资助:
国家自然科学基金(61672213);湖北省自然科学基金(2018CFB721);湖北省教育厅科技处研究计划资助项目(D20182202)

Group Perception Analysis Method Based on WiFi Dissimilarity

JIA Yu-fu¹, LI Ming-lei¹, LIU Wen-ping¹, HU Sheng-hong², JIANG Hong-bo³

1 School of Information Management and Statistics,Hubei University of Economics,Wuhan 430205,China
2 School of Information Engineering,Hubei University of Economics,Wuhan 430205,China
3 College of Computer Science and Electronic Engineering,Hunan University,Changsha 410082,China

Received:2020-05-31 Revised:2020-09-02 Online:2020-10-15 Published:2020-10-16
About author:JIA Yu-fu,born in 1974,Ph.D,lecturer,is a member of China Computer Federation.His main research interests include intelligent perception and mobile computing.
LI Ming-lei,born in 1982,Ph.D,lectu-rer.His main research interests include data analysis and data mining.
Supported by:
National Natural Science Foundation of China (61672213),Natural Science Foundation of Hubei Province(2018CFB721) andResearch program of Science and Technology Department of Education Department of Hubei Province (D20182202)

摘要/Abstract

摘要： 利用智能手机跟踪分析WiFi环境中群体结构的动态变化是一种非侵扰感知技术的新思路。基于WiFi信号差异与节点距离间的关系,设计了一种WiFi相异度的计算方法,根据节点之间的WiFi相异度统计出相异度距离,再利用提出的GSGA-RSS算法迭代计算得到节点坐标,最后利用DBSCAN进行分层次群组结构分析。文中提出了一种基于质心的节点序列位均差表示方法,基于该方法对不同节点间距条件下的队列和环状结构群组进行了实验分析。实验结果表明:在组间最小间距5 m、组内最大间距3 m的条件下,所提方法能够以94%的精度识别出85%的群体;节点间距为0.5 m的队列的位均差约为0.5,节点间距为1 m的环状结构的位均差约为1。

关键词: WiFi相异度, 弹性网络, 群组结构, 位均差, 移动感知

Abstract: It is a new idea of non-intrusive perception technology to track and analyze the dynamic change of group structure in WiFi environment by using smart phone.Based on the relationship between WiFi information difference and between-user distance,a method of WiFi dissimilarity computation is designed.According to the WiFi dissimilarity between users,the dissimilarity distance is statistically calculated,and then the GSGA-RSS algorithm is used to iteratively calculate the node coordinates.Finally,the hierarchical group structure is analyzed by DBSCAN.A method of LMD (location mean deviation) computation based on mass center is proposed,and experiments on groups structures of queues and ring topology under different between-user distances are conducted.The results show that the proposed approach can identify 85% of the groups with 94% precision for the cases with the minimum intergroup distance of 5 m and the maximum intragroup distance of 3 m.The LMD is about 0.5 for the queues with between-user distance of 0.5 m,and about 1 for the ring structure with between-user distance of 1 m.

Key words: Elastic network, Group structure, Location mean deviation, Mobile sensing, WiFi dissimilarity

中图分类号:

TP391.4

贾玉福, 李明磊, 刘文平, 胡胜红, 蒋洪波. 一种基于WiFi相异度的群组感知分析方法[J]. 计算机科学, 2020, 47(10): 63-68. https://doi.org/10.11896/jsjkx.200600014

JIA Yu-fu, LI Ming-lei, LIU Wen-ping, HU Sheng-hong, JIANG Hong-bo. Group Perception Analysis Method Based on WiFi Dissimilarity[J]. Computer Science, 2020, 47(10): 63-68. https://doi.org/10.11896/jsjkx.200600014

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一种基于WiFi相异度的群组感知分析方法

Group Perception Analysis Method Based on WiFi Dissimilarity

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