Research Article
Indoor Cooperative Positioning Based on Fingerprinting and Support Vector Machines
678 downloads
@INPROCEEDINGS{10.1007/978-3-642-29154-8_10, author={Abdellah Chehri and Hussein Mouftah and Wisam Farjow}, title={Indoor Cooperative Positioning Based on Fingerprinting and Support Vector Machines}, proceedings={Mobile and Ubiquitous Systems: Computing, Networking, and Services. 7th International ICST Conference, MobiQuitous 2010, Sydeny, Australia, December 6-9, 2010, Revised Selected Papers}, proceedings_a={MOBIQUITOUS}, year={2012}, month={10}, keywords={Location-based Services Support Vector Machines Radio Mapping RSSI Underground mines}, doi={10.1007/978-3-642-29154-8_10} }- Abdellah Chehri
Hussein Mouftah
Wisam Farjow
Year: 2012
Indoor Cooperative Positioning Based on Fingerprinting and Support Vector Machines
MOBIQUITOUS
Springer
DOI: 10.1007/978-3-642-29154-8_10
Abstract
For location in indoor environments, the fingerprinting technique seems the most attractive one. It gives higher localization accuracy than the parametric technique because of the existence of multipath propagation and fast fading phenomena that are difficult to model. This paper introduces a novel positioning system based on wireless the IEEE802.15.4/ZigBee standard and employs Support Vector Machines (SVMs). The system is cost-effective since it works with real deployed IEEE 802.15.4/ZigBee sensors nodes. The whole system requires minimal setup time, which makes it readily available for real-world applications. The resulting algorithm demonstrates a superior performance compared to the conventional algorithms.
Copyright © 2010–2025 ICST
