A 3-dimensional triangulation scheme to improve the accuracy of indoor localization for IoT services

Shan, Gaoyang; Park, Byeong-hun; Nam, Song-hyeon; Kim, Bosung; Roh, Byeong‐hee; Ko, Young-Bae

doi:10.1109/pacrim.2015.7334862

Cited by 25 publications

(18 citation statements)

References 8 publications

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“…3-D triangulation algorithm in previous studies [2][3][4] uses three beacons for triangulation. By calculating the distance of devices communicating with the Beacon, the hypotenuse of the triangular pyramid is calculated.…”

Section: -D Triangulationmentioning

confidence: 99%

Three-dimensional positioning system using Bluetooth low-energy beacons

Park

Noh

Cho

2016

International Journal of Distributed Sensor Networks

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Bluetooth low-energy-based beacons have two different roles: ''broadcasting'' (by beacon device) and ''receiving'' (by sensing devices). It allows devices to receive information over a short distance. Thus, many researchers are actively investigating positioning methods that use beacons. However, the distance value of positioning in the existing methods is not always accurate. This article proposes a novel three-dimensional positioning system using Bluetooth low-energybased beacons. While the conventional methods measure distances by obtaining two-dimensional coordinates (x, y) through the received signal strength indicator value, the proposed method improves the measurement accuracy by obtaining three-dimensional coordinate values (x, y, z). Finally, while comparing the performance of this new method with that of existing methods, the proposed three-dimensional positioning system reduces the positioning error rate by 27.3% compared to the existing two-dimensional triangulation method.

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Section: -D Triangulationmentioning

confidence: 99%

Three-dimensional positioning system using Bluetooth low-energy beacons

Park

Noh

Cho

2016

International Journal of Distributed Sensor Networks

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“…The measured signals of the black triangle in Figure 1 are shown in Table 4. The chose three closer APs based on the signals are AP1, AP3, and AP4 [10].…”

Section: Sampling Errormentioning

confidence: 99%

Analysis of Selected Indoor Location APs for in Wi-Fi Environments

Park

Hong

Zhu³

et al. 2016

Advanced Science and Technology Letters

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Abstract. Real-time indoor positioning systems based on Wi-Fi signal strength are studied. This study is about how to decide specific three target APs based on Wi-Fi RSSI signals from several APs(access point), and calculate the distance from a mobile object to the selected reference APs by ChipconCO formula. Calculated three distances are used to position the mobile object by using the triangulation method. To overcome the positioning errors, a topology which has five Aps in a square area is proposed and analyzed.

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“…The chosen three closer APs based on the signals should be AP1, AP3, and AP4 [10,18]. But some abnormal situations are observed.…”

Section: Errors Depend On Propagation Distancementioning

confidence: 99%

“…The need for indoor location tracking of mobile objects is increasing for a variety of applications, so various studies for location tracking are ongoing [9,10,16,18].…”

Section: Introductionmentioning

confidence: 99%