Indoor Mapping and Localization for Pedestrians using Opportunistic Sensing with Smartphones

	Indoor Mapping and Localization for Pedestrians using Opportunistic Sensing with Smartphones
	Qing Liang; Lujia Wang; Youfu Li; Ming Liu
	2018
会议日期	2018
会议地点	马德里
英文摘要	Indoor localization based on Visible Light Com- munication (VLC) has been in favor with both the academia and industry for years. In this paper, we present a prototyping photodiode-based VLC system towards large-scale localization. Specially, we give in-depth analysis of the design constraints and considerations for large-scale indoor localization research. After that we identify the key enablers for such systems: 1) distributed architecture, 2) one-way communication, and 3) random multiple access. Accordingly, we propose Plugo — a photodiode-based VLC system conforming to the aforementioned criteria. We present a compact design of the VLC-compatible LED bulbs featuring plug-and-go use-cases. The basic framed slotted Additive Links On-line Hawaii Area (ALOHA) is ex- ploited to achieve random multiple access over the shared optical medium. We show its effectiveness in beacon broadcasting by experiments, and further demonstrate its scalability to large-scale scenarios through simulations. Finally, preliminary localization experiments are conducted using fingerprinting-based methods in a customized testbed, achieving an average accuracy of 0.14m along with a 90-percentile accuracy of 0.33m.
语种	英语
URL标识	查看原文
内容类型	会议论文
源URL	[http://ir.siat.ac.cn:8080/handle/172644/14126]
专题	深圳先进技术研究院_数字所
推荐引用方式 GB/T 7714	Qing Liang,Lujia Wang,Youfu Li,et al. Indoor Mapping and Localization for Pedestrians using Opportunistic Sensing with Smartphones[C]. 见:. 马德里. 2018.