Improving Accuracy and Simplifying Training in Fingerprinting-Based Indoor Location Algorithms at Room Level
Joint Authors
Muñoz-Organero, Mario
Brito-Pacheco, Claudia
Source
Issue
Vol. 2016, Issue 2016 (31 Dec. 2016), pp.1-16, 16 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2016-02-02
Country of Publication
Egypt
No. of Pages
16
Main Subjects
Telecommunications Engineering
Abstract EN
Fingerprinting-based algorithms are popular in indoor location systems based on mobile devices.
Comparing the RSSI (Received Signal Strength Indicator) from different radio wave transmitters, such as Wi-Fi access points, with prerecorded fingerprints from located points (using different artificial intelligence algorithms), fingerprinting-based systems can locate unknown points with a few meters resolution.
However, training the system with already located fingerprints tends to be an expensive task both in time and in resources, especially if large areas are to be considered.
Moreover, the decision algorithms tend to be of high memory and CPU consuming in such cases and so does the required time for obtaining the estimated location for a new fingerprint.
In this paper, we study, propose, and validate a way to select the locations for the training fingerprints which reduces the amount of required points while improving the accuracy of the algorithms when locating points at room level resolution.
We present a comparison of different artificial intelligence decision algorithms and select those with better results.
We do a comparison with other systems in the literature and draw conclusions about the improvements obtained in our proposal.
Moreover, some techniques such as filtering nonstable access points for improving accuracy are introduced, studied, and validated.
American Psychological Association (APA)
Muñoz-Organero, Mario& Brito-Pacheco, Claudia. 2016. Improving Accuracy and Simplifying Training in Fingerprinting-Based Indoor Location Algorithms at Room Level. Mobile Information Systems،Vol. 2016, no. 2016, pp.1-16.
https://search.emarefa.net/detail/BIM-1111397
Modern Language Association (MLA)
Muñoz-Organero, Mario& Brito-Pacheco, Claudia. Improving Accuracy and Simplifying Training in Fingerprinting-Based Indoor Location Algorithms at Room Level. Mobile Information Systems No. 2016 (2016), pp.1-16.
https://search.emarefa.net/detail/BIM-1111397
American Medical Association (AMA)
Muñoz-Organero, Mario& Brito-Pacheco, Claudia. Improving Accuracy and Simplifying Training in Fingerprinting-Based Indoor Location Algorithms at Room Level. Mobile Information Systems. 2016. Vol. 2016, no. 2016, pp.1-16.
https://search.emarefa.net/detail/BIM-1111397
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1111397