Enhancing WiFi-based localization with visual clues

Indoor localization is of great importance to a wide range of applications in the era of mobile computing. Current mainstream solutions rely on Received Signal Strength (RSS) of wireless signals as fingerprints to distinguish and infer locations. However, those methods suffer from fingerprint ambigu...

Full description

Saved in:
Bibliographic Details
Main Authors: XU, Han, YANG, Zheng, ZHOU, Zimu, SHANGGUAN, Longfei, LIU, Yunhao, YI, Ke
Format: text
Language:English
Published: Institutional Knowledge at Singapore Management University 2015
Subjects:
Online Access:https://ink.library.smu.edu.sg/sis_research/4750
https://ink.library.smu.edu.sg/context/sis_research/article/5753/viewcontent/ubicomp15.pdf
Tags: Add Tag
No Tags, Be the first to tag this record!
Institution: Singapore Management University
Language: English
id sg-smu-ink.sis_research-5753
record_format dspace
spelling sg-smu-ink.sis_research-57532020-01-16T10:36:00Z Enhancing WiFi-based localization with visual clues XU, Han YANG, Zheng ZHOU, Zimu SHANGGUAN, Longfei LIU, Yunhao YI, Ke Indoor localization is of great importance to a wide range of applications in the era of mobile computing. Current mainstream solutions rely on Received Signal Strength (RSS) of wireless signals as fingerprints to distinguish and infer locations. However, those methods suffer from fingerprint ambiguity that roots in multipath fading and temporal dynamics of wireless signals. Though pioneer efforts have resorted to motion-assisted or peer-assisted localization, they neither work in real time nor work without the help of peer users, which introduces extra costs and constraints, and thus degrades their practicality. To get over these limitations, we propose Argus, an image-assisted localization system for mobile devices. The basic idea of Argus is to extract geometric constraints from crowdsourced photos, and to reduce fingerprint ambiguity by mapping the constraints jointly against the fingerprint space. We devise techniques for photo selection, geometric constraint extraction, joint location estimation, and build a prototype that runs on commodity phones. Extensive experiments show that Argus triples the localization accuracy of classic RSS-based method, in time no longer than normal WiFi scanning, with negligible energy consumption. 2015-09-11T07:00:00Z text application/pdf https://ink.library.smu.edu.sg/sis_research/4750 info:doi/10.1145/2750858.2807516 https://ink.library.smu.edu.sg/context/sis_research/article/5753/viewcontent/ubicomp15.pdf http://creativecommons.org/licenses/by-nc-nd/4.0/ Research Collection School Of Computing and Information Systems eng Institutional Knowledge at Singapore Management University Indoor Localization; Smart Phone Photogrammetry Digital Communications and Networking Information Security
institution Singapore Management University
building SMU Libraries
continent Asia
country Singapore
Singapore
content_provider SMU Libraries
collection InK@SMU
language English
topic Indoor Localization; Smart Phone
Photogrammetry
Digital Communications and Networking
Information Security
spellingShingle Indoor Localization; Smart Phone
Photogrammetry
Digital Communications and Networking
Information Security
XU, Han
YANG, Zheng
ZHOU, Zimu
SHANGGUAN, Longfei
LIU, Yunhao
YI, Ke
Enhancing WiFi-based localization with visual clues
description Indoor localization is of great importance to a wide range of applications in the era of mobile computing. Current mainstream solutions rely on Received Signal Strength (RSS) of wireless signals as fingerprints to distinguish and infer locations. However, those methods suffer from fingerprint ambiguity that roots in multipath fading and temporal dynamics of wireless signals. Though pioneer efforts have resorted to motion-assisted or peer-assisted localization, they neither work in real time nor work without the help of peer users, which introduces extra costs and constraints, and thus degrades their practicality. To get over these limitations, we propose Argus, an image-assisted localization system for mobile devices. The basic idea of Argus is to extract geometric constraints from crowdsourced photos, and to reduce fingerprint ambiguity by mapping the constraints jointly against the fingerprint space. We devise techniques for photo selection, geometric constraint extraction, joint location estimation, and build a prototype that runs on commodity phones. Extensive experiments show that Argus triples the localization accuracy of classic RSS-based method, in time no longer than normal WiFi scanning, with negligible energy consumption.
format text
author XU, Han
YANG, Zheng
ZHOU, Zimu
SHANGGUAN, Longfei
LIU, Yunhao
YI, Ke
author_facet XU, Han
YANG, Zheng
ZHOU, Zimu
SHANGGUAN, Longfei
LIU, Yunhao
YI, Ke
author_sort XU, Han
title Enhancing WiFi-based localization with visual clues
title_short Enhancing WiFi-based localization with visual clues
title_full Enhancing WiFi-based localization with visual clues
title_fullStr Enhancing WiFi-based localization with visual clues
title_full_unstemmed Enhancing WiFi-based localization with visual clues
title_sort enhancing wifi-based localization with visual clues
publisher Institutional Knowledge at Singapore Management University
publishDate 2015
url https://ink.library.smu.edu.sg/sis_research/4750
https://ink.library.smu.edu.sg/context/sis_research/article/5753/viewcontent/ubicomp15.pdf
_version_ 1770575020021514240