DocumentCode
169094
Title
Demonstration abstract: Crowdsourced indoor localization and navigation with Anyplace
Author
Petrou, Lambros ; Larkou, George ; Laoudias, Christos ; Zeinalipour-Yazti, Demetrios ; Panayiotou, Christos G.
Author_Institution
Dept. of Comput. Sci., Univ. of Cyprus, Nicosia, Cyprus
fYear
2014
fDate
15-17 April 2014
Firstpage
331
Lastpage
332
Abstract
In this demonstration paper, we present the Anyplace system that relies on the abundance of sensory data on smartphones (e.g., WiFi signal strength and inertial measurements) to deliver reliable indoor geolocation information. Our system features two highly desirable properties, namely crowdsourcing and scalability. Anyplace implements a set of crowdsourcing-supportive mechanisms to handle the enormous amount of crowdsensed data, filter incorrect user contributions and exploit WiFi data from heterogeneous mobile devices. Moreover, Anyplace follows a big-data architecture for efficient and scalable storage and retrieval of localization and mapping data.
Keywords
Big Data; indoor radio; information filtering; radionavigation; smart phones; wireless LAN; Big Data architecture; WiFi data; anyplace system; crowdsourced indoor localization; crowdsourcing-supportive mechanisms; heterogeneous mobile devices; indoor geolocation information reliability; indoor navigation; localization data retrieval; mapping data retrieval; scalable storage; sensory data; smartphones; Buildings; Computer architecture; Crowdsourcing; IEEE 802.11 Standards; Navigation; Servers; Smart phones; Crowdsourcing; indoor localization; navigation;
fLanguage
English
Publisher
ieee
Conference_Titel
Information Processing in Sensor Networks, IPSN-14 Proceedings of the 13th International Symposium on
Conference_Location
Berlin
Print_ISBN
978-1-4799-3146-0
Type
conf
DOI
10.1109/IPSN.2014.6846788
Filename
6846788
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