Accuracy Study of Indoor Positioning with Bluetooth Low Energy Beacons

Phutcharoen, Kanyanee; Chamchoy, Monchai; Supanakoon, Pichaya

doi:10.1109/ectidamtncon48261.2020.9090691

Cited by 24 publications

(12 citation statements)

References 5 publications

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“…Nowadays, there are already many indoor positioning technologies including WIFI [10,11], LED visible light [12], Geomagnetism [13], Image Identification [14], and Bluetooth [15] that can be used for commercial purposes. Some of these technologies can be directly located by mobile phones after the device has been deployed based on the indoor layout, such as WIFI, Bluetooth, etc.…”

Section: Indoor Positioning Technologiesmentioning

confidence: 99%

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Comparison between the Ultra-wide Band based indoor positioning technology and other technologies

2022

J. Phys.: Conf. Ser.

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In recent decades, there have been many applications of positioning and navigation systems, the most representative of which is GPS (Global Positioning System). This technique is very accurate for outdoor navigation, but it cannot provide reliable positioning data indoors. This paper firstly compares the different indoor positioning technologies and analyses their bottleneck. Then the suitable algorithm of UWB based on indoor positioning technology (IPT) is discussed including Angle of arrival (AoA), Time of arrival (ToA), Time difference of arrival (TDoA), and Received Signal Strength (RSS). Eventually, the paper finds that although UWB-based indoor positioning technology still has many problems such as high deployment equipment costs to be solved, it is suitable for widespread applications due to its special advantages such as strong resistance to multipath effects.

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Section: Indoor Positioning Technologiesmentioning

confidence: 99%

“…This technology mainly uses a trilateral positioning algorithm like WIFI, and estimates the distance based on RSS [15]. Its cost is relatively low, so the accuracy can be improved by increasing the deployment density.…”

Section: Bluetoothmentioning

confidence: 99%

Comparison between the Ultra-wide Band based indoor positioning technology and other technologies

2022

J. Phys.: Conf. Ser.

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“…The main challenge in fingerprinting- and model-based IPS is that accuracy is affected by several factors, such as signal-related and environment-related factors [ 15 ]. In terms of signal-related factors, the following can often occur: Large fluctuations, reflection, path loss, non-line-of-sight conditions and multipath fading, and many of these factors also depend on the type of material present in the environment [ 23 ]. For environment-related factors, the main ones are changes in hardware or furniture, the presence of people, or ambient humidity conditions [ 24 ].…”

Section: Introductionmentioning

confidence: 99%

An Automated Indoor Localization System for Online Bluetooth Signal Strength Modeling Using Visual-Inertial SLAM

Tomažič

Škrjanc

2021

Sensors

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Indoor localization is becoming increasingly important but is not yet widespread because installing the necessary infrastructure is often time-consuming and labor-intensive, which drives up the price. This paper presents an automated indoor localization system that combines all the necessary components to realize low-cost Bluetooth localization with the least data acquisition and network configuration overhead. The proposed system incorporates a sophisticated visual-inertial localization algorithm for a fully automated collection of Bluetooth signal strength data. A suitable collection of measurements can be quickly and easily performed, clearly defining which part of the space is not yet well covered by measurements. The obtained measurements, which can also be collected via the crowdsourcing approach, are used within a constrained nonlinear optimization algorithm. The latter is implemented on a smartphone and allows the online determination of the beacons’ locations and the construction of path loss models, which are validated in real-time using the particle swarm localization algorithm. The proposed system represents an advanced innovation as the application user can quickly find out when there are enough data collected for the expected radiolocation accuracy. In this way, radiolocation becomes much less time-consuming and labor-intensive as the configuration time is reduced by more than half. The experiment results show that the proposed system achieves a good trade-off in terms of network setup complexity and localization accuracy. The developed system for automated data acquisition and online modeling on a smartphone has proved to be very useful, as it can significantly simplify and speed up the installation of the Bluetooth network, especially in wide-area facilities.

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“…Distance that is calculated by using path loss model plays an important role in estimating the position of the user [14], [15]. The IPS using trilateration technique is easy to build and low-cost system as the RSSI value are easy to extract by the receiver [16], [17]. The accuracy of the IPS using the trilateration method can be increase if it is combined with other algorithm or technique.…”

Section: Introductionmentioning

confidence: 99%

Indoor positioning utilizing bluetooth low energy (BLE) RSSI on LoRa system

Suseenthiran

Ja'afar

Heng

et al. 2021

IJEECS

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Indoor positioning systems has become popular in this era where it is a network of devices used to locate people or object especially in indoor environment instead of satellite-based positioning. The satellite-based positioning global positioning system (GPS) signal is affected and loss incurred by the wall of the building causes the GPS lack of precision which leads to large positioning error. As a solution to the indoor area coverage problem, an indoor positioning based on bluetooth low energy (BLE) and long range (LoRa) system utilising the receive signal strength indicator (RSSI) is proposed, designed and tested. In this project, the prototype of indoor positioning system is built using node MCU ESP 32, LoRa nodes and BLE beacons. The node MCU ESP 32 will collect RSSI data from each BLE beacons that deployed at decided position around the area. Then, linear regression algorithm will be used in distance estimation. Next, particle filteris implemented to overcome the multipath fading effect and the trilateration technique is applied to estimate the user’s location. The estimated location is compared to the actual position to analyze the root mean square error (RMSE) and cumulative distribution function (CDF). Based on the experiment result, implementing the particle filter reduces the error of location accuracy. The particle filter achieves accuracy with 90% of the time the location error is lower than 2.6 meters.

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Accuracy Study of Indoor Positioning with Bluetooth Low Energy Beacons

Cited by 24 publications

References 5 publications

Comparison between the Ultra-wide Band based indoor positioning technology and other technologies

Comparison between the Ultra-wide Band based indoor positioning technology and other technologies

An Automated Indoor Localization System for Online Bluetooth Signal Strength Modeling Using Visual-Inertial SLAM

Indoor positioning utilizing bluetooth low energy (BLE) RSSI on LoRa system

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