SP-Loc: A crowdsourcing fingerprint based shop-level indoor localization algorithm integrating shop popularity without the indoor map

doi:10.1177/1550147718815637

	SP-Loc: A crowdsourcing fingerprint based shop-level indoor localization algorithm integrating shop popularity without the indoor map
	Wei, Jie 1; Zhao, Fang 1; Luo, Haiyong 2
	2018-11-29
发表期刊	INTERNATIONAL JOURNAL OF DISTRIBUTED SENSOR NETWORKS
ISSN	1550-1477
卷号	14 期号:11 页码:18
摘要	With the development of indoor localization technology, the location-based services such as product advertising recommendation in the shopping mall attract widespread attention, as precise user location significantly improves the efficiency of advertising push and brings broader profits. However, most of the Wi-Fi-based indoor localization approaches requiring professionals to deploy expensive beacon devices and intensively collect fingerprints in each location grid, which severely limits its extensive promotion. We introduce a zero-cost indoor localization algorithm utilizing crowdsourcing fingerprints to obtain the shop recognition where the user is located. Naturally utilizing the Wi-Fi, GPS, and time-stamp fingerprints collected from the smartphone when user paid as the crowdsourcing fingerprint, we avoid the requirement for indoor map and get rid of both devices cost and manual signal collecting process. Moreover, a shop-level hierarchical indoor localization framework is proposed, and high robustness features based on Wi-Fi sequences variation pattern in the same shop analysis are designed to avoid the received signal strength fluctuations. Besides, we also pay more attention to mine the popularity properties of shops and explore GPS features to improve localization accuracy in the Wi-Fi absence situation effectively. Massive experiments indicate that SP-Loc achieves more than 93% localization accuracy.
关键词	Indoor localization shop-level localization crowdsourcing fingerprints shop popularity property supervised learning
DOI	10.1177/1550147718815637
收录类别	SCI
语种	英语
资助项目	National Key Research and Development Program[2018YFB0505200] ; National Natural Science Foundation of China[61872046] ; Open Project of the Beijing Key Laboratory of Mobile Computing and Pervasive Device
WOS研究方向	Computer Science ; Telecommunications
WOS类目	Computer Science, Information Systems ; Telecommunications
WOS记录号	WOS:000452829800001
出版者	SAGE PUBLICATIONS INC
引用统计	被引频次：4[WOS] [WOS记录] [WOS相关记录]
文献类型	期刊论文
条目标识符	http://119.78.100.204/handle/2XEOYT63/3521
专题	中国科学院计算技术研究所期刊论文_英文
通讯作者	Luo, Haiyong
作者单位	1.Beijing Univ Post & Telecommun, Sch Software Engn, Beijing, Peoples R China 2.Chinese Acad Sci, Inst Comp Technol, Beijing, Peoples R China
推荐引用方式 GB/T 7714	Wei, Jie,Zhao, Fang,Luo, Haiyong. SP-Loc: A crowdsourcing fingerprint based shop-level indoor localization algorithm integrating shop popularity without the indoor map[J]. INTERNATIONAL JOURNAL OF DISTRIBUTED SENSOR NETWORKS,2018,14(11):18.
APA	Wei, Jie,Zhao, Fang,&Luo, Haiyong.(2018).SP-Loc: A crowdsourcing fingerprint based shop-level indoor localization algorithm integrating shop popularity without the indoor map.INTERNATIONAL JOURNAL OF DISTRIBUTED SENSOR NETWORKS,14(11),18.
MLA	Wei, Jie,et al."SP-Loc: A crowdsourcing fingerprint based shop-level indoor localization algorithm integrating shop popularity without the indoor map".INTERNATIONAL JOURNAL OF DISTRIBUTED SENSOR NETWORKS 14.11(2018):18.