Iot-aided indoor positioning based on fingerprinting

Rashmi Sharan Sinha; Jingjun Chen; Seung Hoon Hwang

Iot-aided indoor positioning based on fingerprinting

Rashmi Sharan Sinha, Jingjun Chen, Seung Hoon Hwang

Department of Electronics & Electrical Engineering

Dongguk University

Research output: Contribution to journal › Article › peer-review

2 Scopus citations

Abstract

With the increasing demand of localization, WiFi fingerprint-based indoor positioning has great attraction because of its effective cost and easy deployment. Additionally, internet of thing (IoT) is considered as one of 5G services in the 4^th industrial revolution era. In this paper, we develop IoT-aided fingerprint localization system. Furthermore, two kinds of algorithms are introduced based on K-nearest neighbor (KNN) and those performances are validated through the experiments. The numerical results show both schemes outperform the existing KNN approach.

Original language	English
Pages (from-to)	15772-15776
Number of pages	5
Journal	International Journal of Applied Engineering Research
Volume	12
Issue number	24
State	Published - 2017

Keywords

Fingerprint
Indoor localization
IoT
KNN
RSSI
WiFi

Cite this

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title = "Iot-aided indoor positioning based on fingerprinting",

abstract = "With the increasing demand of localization, WiFi fingerprint-based indoor positioning has great attraction because of its effective cost and easy deployment. Additionally, internet of thing (IoT) is considered as one of 5G services in the 4th industrial revolution era. In this paper, we develop IoT-aided fingerprint localization system. Furthermore, two kinds of algorithms are introduced based on K-nearest neighbor (KNN) and those performances are validated through the experiments. The numerical results show both schemes outperform the existing KNN approach.",

keywords = "Fingerprint, Indoor localization, IoT, KNN, RSSI, WiFi",

author = "Sinha, {Rashmi Sharan} and Jingjun Chen and Hwang, {Seung Hoon}",

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year = "2017",

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AU - Sinha, Rashmi Sharan

AU - Chen, Jingjun

AU - Hwang, Seung Hoon

N1 - Publisher Copyright: © Research India Publications.

PY - 2017

Y1 - 2017

N2 - With the increasing demand of localization, WiFi fingerprint-based indoor positioning has great attraction because of its effective cost and easy deployment. Additionally, internet of thing (IoT) is considered as one of 5G services in the 4th industrial revolution era. In this paper, we develop IoT-aided fingerprint localization system. Furthermore, two kinds of algorithms are introduced based on K-nearest neighbor (KNN) and those performances are validated through the experiments. The numerical results show both schemes outperform the existing KNN approach.

AB - With the increasing demand of localization, WiFi fingerprint-based indoor positioning has great attraction because of its effective cost and easy deployment. Additionally, internet of thing (IoT) is considered as one of 5G services in the 4th industrial revolution era. In this paper, we develop IoT-aided fingerprint localization system. Furthermore, two kinds of algorithms are introduced based on K-nearest neighbor (KNN) and those performances are validated through the experiments. The numerical results show both schemes outperform the existing KNN approach.

KW - Fingerprint

KW - Indoor localization

KW - IoT

KW - KNN

KW - RSSI

KW - WiFi

UR - http://www.scopus.com/inward/record.url?scp=85057648378&partnerID=8YFLogxK

M3 - Article

AN - SCOPUS:85057648378

SN - 0973-4562

VL - 12

SP - 15772

EP - 15776

JO - International Journal of Applied Engineering Research

JF - International Journal of Applied Engineering Research

IS - 24

ER -

Iot-aided indoor positioning based on fingerprinting

Abstract

Keywords

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Fingerprint

Cite this