Indoor positioning method using RFID and block clustering

Wenjie Zhang, Yuning Dong, Xinheng Wang

Research output: Contribution to journalArticle

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Abstract

The indoor positioning technology based on fingerprint attracts the attentions from many researchers. RFID(RadioFrequency Identification) technology is more attractive, due to its high accuracy and adaptability to different environment. However, because of the heavy consumption of the computing power, it limits the applications in practice. A new hybrid Kmeans and Weighted K-nearest Neighbor method is proposed and applied in real-world indoor positioning. The new method divided the mapping area into several classes based on a clustering method. A matching into class is done first and then location is determined. The result shows that the proposed method reduces the accumulated errors and thus reduces the computational power whist maintains reasonable accuracy.
Translated title of the contributionIndoor positioning method using RFID and block clustering
Original languageChinese
Pages (from-to)112-117
Number of pages6
JournalComputer Engineering and Applications
Volume52
Issue number10
DOIs
Publication statusPublished - 2016

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Radio frequency identification (RFID)

Cite this

Zhang, Wenjie ; Dong, Yuning ; Wang, Xinheng. / 一种利用 RFID 和块聚类的快速室内指纹定位方法. In: Computer Engineering and Applications. 2016 ; Vol. 52, No. 10. pp. 112-117.
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abstract = "The indoor positioning technology based on fingerprint attracts the attentions from many researchers. RFID(RadioFrequency Identification) technology is more attractive, due to its high accuracy and adaptability to different environment. However, because of the heavy consumption of the computing power, it limits the applications in practice. A new hybrid Kmeans and Weighted K-nearest Neighbor method is proposed and applied in real-world indoor positioning. The new method divided the mapping area into several classes based on a clustering method. A matching into class is done first and then location is determined. The result shows that the proposed method reduces the accumulated errors and thus reduces the computational power whist maintains reasonable accuracy.",
author = "Wenjie Zhang and Yuning Dong and Xinheng Wang",
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一种利用 RFID 和块聚类的快速室内指纹定位方法. / Zhang, Wenjie ; Dong, Yuning ; Wang, Xinheng.

In: Computer Engineering and Applications, Vol. 52, No. 10, 2016, p. 112-117.

Research output: Contribution to journalArticle

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T1 - 一种利用 RFID 和块聚类的快速室内指纹定位方法

AU - Zhang, Wenjie

AU - Dong, Yuning

AU - Wang, Xinheng

PY - 2016

Y1 - 2016

N2 - The indoor positioning technology based on fingerprint attracts the attentions from many researchers. RFID(RadioFrequency Identification) technology is more attractive, due to its high accuracy and adaptability to different environment. However, because of the heavy consumption of the computing power, it limits the applications in practice. A new hybrid Kmeans and Weighted K-nearest Neighbor method is proposed and applied in real-world indoor positioning. The new method divided the mapping area into several classes based on a clustering method. A matching into class is done first and then location is determined. The result shows that the proposed method reduces the accumulated errors and thus reduces the computational power whist maintains reasonable accuracy.

AB - The indoor positioning technology based on fingerprint attracts the attentions from many researchers. RFID(RadioFrequency Identification) technology is more attractive, due to its high accuracy and adaptability to different environment. However, because of the heavy consumption of the computing power, it limits the applications in practice. A new hybrid Kmeans and Weighted K-nearest Neighbor method is proposed and applied in real-world indoor positioning. The new method divided the mapping area into several classes based on a clustering method. A matching into class is done first and then location is determined. The result shows that the proposed method reduces the accumulated errors and thus reduces the computational power whist maintains reasonable accuracy.

U2 - 10.3778/j.issn.1002-8331.1407-0064

DO - 10.3778/j.issn.1002-8331.1407-0064

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JO - Computer Engineering and Applications

JF - Computer Engineering and Applications

SN - 1002-8331

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