Paper Info
Title
Molé: A scalable, user-generated WiFi positioning engine.
Abstract
We describe the design, implementation, and evaluation of Molé, a mobile organic localisation engine. Unlike previous work on crowd-sourced WiFi positioning, Molé uses a hierarchical name space. By not relying on a map and by being more strict than uninterpreted names for places, Molé aims for a more flexible and scalable point in the design space of localisation systems. Molé employs several new techniques, including a new statistical positioning algorithm to differentiate between neighbouring places, a motion detector to reduce update lag, and a scalable ‘cloud’-based fingerprint distribution system. Molé's localisation algorithm, called Maximum Overlap MAO, accounts for temporal variations in a place's fingerprint in a principled manner. It also allows for aggregation of fingerprints from many users and is compact enough for on-device storage. We show through end-to-end experiments in two deployments that MAO is significantly more accurate than state-of-the-art Bayesian-based localisers. We also show that non-experts can use Molé to quickly survey a building, enabling room-grained location-based services for themselves and others.
Year
DOI
Venue
2012
10.1080/17489725.2012.692617
Journal of Location Based Services
Keywords
DocType
Volume
localisation algorithm,mobile organic localisation engine,design space,user-generated wifi positioning engine,new statistical positioning algorithm,crowd-sourced wifi positioning,hierarchical name space,fingerprint distribution system,new technique,localisation system,maximum overlap mao,cloud computing,mobile computing
Journal
6
Issue
ISSN
Citations 
2
1748-9725
21
PageRank 
References 
Authors
0.95
21
7
Name
Order
Citations
PageRank
Jonathan Ledlie185845.78
Jun-geun Park21607.94
Dorothy Curtis3210.95
André Cavalcante418217.47
Leonardo Camara5210.95
Afonso Costa6210.95
Robson D. Vieira721322.42