Indoor Positioning inside an Office Building Using BLE

Radoi, Ioana; Gutu, Gabriel; Rebedea, Traian; Neagu, Cristian; Popa, M.

doi:10.1109/cscs.2017.29

Cited by 16 publications

(8 citation statements)

References 6 publications

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“…In [ 37 ] the authors make a comparison between BLE with particle filtering and fingerprinting. Their results show that fingerprinting outperforms particle filtering in a 1.5 m × 12 m corridor, but particle filtering outperforms fingerprinting with an accuracy of less than 4 m in 90% of time in an 8 m × 6 m room.…”

Section: Related Workmentioning

confidence: 99%

A Bluetooth Low Energy Indoor Positioning System with Channel Diversity, Weighted Trilateration and Kalman Filtering

Paterna

Calveras

Paradells

et al. 2017

Sensors

163

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Indoor Positioning Systems (IPS) using Bluetooth Low Energy (BLE) technology are currently becoming real and available, which has made them grow in popularity and use. However, there are still plenty of challenges related to this technology, especially in terms of Received Signal Strength Indicator (RSSI) fluctuations due to the behaviour of the channels and the multipath effect, that lead to poor precision. In order to mitigate these effects, in this paper we propose and implement a real Indoor Positioning System based on Bluetooth Low Energy, that improves accuracy while reducing power consumption and costs. The three main proposals are: frequency diversity, Kalman filtering and a trilateration method what we have denominated “weighted trilateration”. The analysis of the results proves that all the proposals improve the precision of the system, which goes up to 1.82 m 90% of the time for a device moving in a middle-size room and 0.7 m for static devices. Furthermore, we have proved that the system is scalable and efficient in terms of cost and power consumption. The implemented approach allows using a very simple device (like a SensorTag) on the items to locate. The system enables a very low density of anchor points or references and with a precision better than existing solutions.

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Section: Related Workmentioning

confidence: 99%

A Bluetooth Low Energy Indoor Positioning System with Channel Diversity, Weighted Trilateration and Kalman Filtering

Paterna

Calveras

Paradells

et al. 2017

Sensors

163

View full text Add to dashboard Cite

show abstract

“…Inverse Fingerprinting (Inv-FP) and Pedestrian Dead Reckoning (PDR) [21]. Particle Filtering [22]. Cell of Origin (CoO) algorithm and Kalman Filter [23].…”

Section: Fingerprinting Methodsmentioning

confidence: 99%

Indoor Positioning System Using Combination of Trilateration and Fingerprinting Methods

Saputra¹

2020

IJATCSE

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Positioning technology continues to develop. Positioning which is widely used and can work very well outdoors is to use GPS (Global Positioning System). However, GPS cannot run well indoors because of many obstacles in a building. The study was conducted with the topic "indoor positioning system". This research using BLE (Bluetooth Low Energy) technology because it consumes the least energy and can last a very long time. The focus of this research is to use a combination of trilateration and fingerprinting methods to improve accuracy performance. The first stage determines the reference point and forms a radio map. The second stage consists of estimation using the trilateration method. The log distance path loss model/Log-normal shadowing model was used for the propagation model. The evaluation of the proposed method is in a room with a size of 21m x 12 m, 100 sample data for each reference point, and 10 sample data for each test point. Error performance is evaluated using average error, min error, max error, median and 90th percentile. The results of this study if compared with results that only use the trilateration method show that the proposed hybrid method has better accuracy performance and fewer errors rate.

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“…Radoi et al [ 18 ] performed some experiments in an office environment. The authors analyzed two methods: fingerprinting and particle filtering.…”

Section: Related Workmentioning

confidence: 99%

Obstruction-Aware Signal-Loss-Tolerant Indoor Positioning Using Bluetooth Low Energy

Taşkan

Alemdar

2021

Sensors

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Indoor positioning is getting increased attention due to the availability of larger and more sophisticated indoor environments. Wireless technologies like Bluetooth Low Energy (BLE) may provide inexpensive solutions. In this paper, we propose obstruction-aware signal-loss-tolerant indoor positioning (OASLTIP), a cost-effective BLE-based indoor positioning algorithm. OASLTIP uses a combination of techniques together to provide optimum tracking performance by taking into account the obstructions in the environment, and also, it can handle a loss of signal. We use running average filtering to smooth the received signal data, multilateration to find the measured position of the tag, and particle filtering to track the tag for better performance. We also propose an optional receiver placement method and provide the option to use fingerprinting together with OASLTIP. Moreover, we give insights about BLE signal strengths in different conditions to help with understanding the effects of some environmental conditions on BLE signals. We performed extensive experiments for evaluation of the OASLTool we developed. Additionally, we evaluated the performance of the system both in a simulated environment and in real-world conditions. In a highly crowded and occluded office environment, our system achieved 2.29 m average error, with three receivers. When simulated in OASLTool, the same setup yielded an error of 2.58 m.

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Indoor Positioning inside an Office Building Using BLE

Cited by 16 publications

References 6 publications

A Bluetooth Low Energy Indoor Positioning System with Channel Diversity, Weighted Trilateration and Kalman Filtering

A Bluetooth Low Energy Indoor Positioning System with Channel Diversity, Weighted Trilateration and Kalman Filtering

Indoor Positioning System Using Combination of Trilateration and Fingerprinting Methods

Obstruction-Aware Signal-Loss-Tolerant Indoor Positioning Using Bluetooth Low Energy

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