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Robust Floor Determination Algorithm for Indoor Wireless Localization Systems under Reference Node Failure
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Document Title
Robust Floor Determination Algorithm for Indoor Wireless Localization Systems under Reference Node Failure
Author
Maneerat K., Kaemarungsi K., Prommak C.
Name from Authors Collection
Affiliations
School of Telecommunication Engineering, Suranaree University of Technology, Nakhon Ratchasima, Thailand; National Electronics and Computer Technology Center, NSTDA, Pathumthani, Thailand
Type
Article
Source Title
Mobile Information Systems
ISSN
1574017X
Year
2016
Volume
2016
Open Access
All Open Access, Gold, Green
Publisher
Hindawi Limited
DOI
10.1155/2016/4961565
Format
Abstract
One of the challenging problems for indoor wireless multifloor positioning systems is the presence of reference node (RN) failures, which cause the values of received signal strength (RSS) to be missed during the online positioning phase of the location fingerprinting technique. This leads to performance degradation in terms of floor accuracy, which in turn affects other localization procedures. This paper presents a robust floor determination algorithm called Robust Mean of Sum-RSS (RMoS), which can accurately determine the floor on which mobile objects are located and can work under either the fault-free scenario or the RN-failure scenarios. The proposed fault tolerance floor algorithm is based on the mean of the summation of the strongest RSSs obtained from the IEEE 802.15.4 Wireless Sensor Networks (WSNs) during the online phase. The performance of the proposed algorithm is compared with those of different floor determination algorithms in literature. The experimental results show that the proposed robust floor determination algorithm outperformed the other floor algorithms and can achieve the highest percentage of floor determination accuracy in all scenarios tested. Specifically, the proposed algorithm can achieve greater than 95% correct floor determination under the scenario in which 40% of RNs failed. © Copyright 2016 Kriangkrai Maneerat et al.
Industrial Classification
Knowledge Taxonomy Level 1
Knowledge Taxonomy Level 2
Knowledge Taxonomy Level 3
License
N/A
Rights
N/A
Publication Source
Scopus