Paper Info
Title
Combining similarity functions and majority rules for multi-building, multi-floor, WiFi positioning
Abstract
Fingerprint is one of the most widely used methods for locating devices in indoor wireless environments and we have witnessed the emergence of several positioning systems aimed for indoor environments based on this approach. However, additional efforts are required in order to improve the performance of these systems so that applications that are highly dependent on user location can provide better services to its users. In this work we discuss some improvements to the positioning accuracy of the fingerprint-based systems. Our algorithm ranks the information about the location in a hierarchical way by identifying the building, the floor, the room and the geometric position. The proposed fingerprint method uses a previously stored map of the signal strength at several positions and determines the position using similarity functions and majority rules. In particular, we compare different similarity functions to understand their impact on the accuracy of the positioning system. The experimental results confirm the possibility of correctly determining the building, the floor and the room where the persons or the objects are at with high rates, and with an average error around 3 meters. Moreover, detailed statistics about the errors are provided, showing that the average error metric, often used by many authors, hides many aspects on the system performance.
Year
DOI
Venue
2012
10.1109/IPIN.2012.6418937
Indoor Positioning and Indoor Navigation
Keywords
Field
DocType
indoor radio,signal detection,statistical analysis,wireless LAN,WiFi positioning,fingerprint-based system,geometric position,indoor wireless environment,majority rules,multibuilding positioning,multifloor positioning,signal strength,similarity function,statistics,fingerprinting,indoor positioning,mobile computing,rssi,wlan
Mobile computing,Data mining,Hybrid positioning system,Wireless,Detection theory,Signal strength,Artificial intelligence,Majority rule,Positioning system,Computer vision,Fingerprint,Engineering,Embedded system
Conference
ISSN
ISBN
Citations 
2162-7347
978-1-4673-1955-3
26
PageRank 
References 
Authors
1.58
7
3
Name
Order
Citations
PageRank
Nelson Marques1261.58
Filipe Meneses212311.66
Adriano Moreira323459.85