Smart probabilistic fingerprinting for WiFi-based indoor positioning with mobile devices

被引：54
作者：
Bisio, Igor [1 ]
Lavagetto, Fabio [1 ]
Marchese, Mario [1 ]
Sciarrone, Andrea [1 ]
机构：
[1] Univ Genoa, Dept Elect Elect Telecommun Engn & Naval Architec, Via Opera Pia 13, I-16145 Genoa, Italy
来源：
PERVASIVE AND MOBILE COMPUTING | 2016年 / 31卷
关键词：
Indoor positioning; WiFi fingerprinting; Computational and energy efficiency; Smartphones; SYSTEMS;
D O I：
10.1016/j.pmcj.2016.02.001
中图分类号：
TP [自动化技术、计算机技术];
学科分类号：
0812 ;
摘要：
Different positioning schemes are based on the probability p(o vertical bar l) to have an observation vector o at a Reference Point (RP) l, based on Gaussian probabilities. This paper presents an approach to speed-up the p(o vertical bar l) computation without any approximation. The consequent positioning scheme is called Smart P-FP. The comparison between Traditional (without any p(o vertical bar l) acceleration) and Smart P-FP is performed over different smartphones. The saved energy is about 90% for a large number of Access Points (APs) but is significant even with few APs: more than 86% with 3 APs. The proposed p(o vertical bar l) computation is beneficial to any p(o vertical bar l)-based positioning scheme. (C) 2016 Elsevier B.V. All rights reserved.
引用
收藏
页码：107 / 123
页数：17
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