Geometry-Aided BLE-Based Smartphone Positioning for Indoor Location-Based Services

Rudic, Branislav; Klaffenböck, Maria Anneliese; Pichler-Scheder, Markus; Efrosinin, Dmitry; Kastl, Christian

doi:10.1109/icmim48759.2020.9299009

Cited by 4 publications

(2 citation statements)

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“…Location-based services (LBS) play a crucial role in modern life [1,2]. Positioning is a fundamental technology utilized for LBS, as well as various applications within the Internet of Things (IoT) and artificial intelligence (AI) [1].…”

Section: Introductionmentioning

confidence: 99%

An Up-View Visual-Based Indoor Positioning Method via Deep Learning

Chen,

Zhu

et al. 2024

Remote Sensing

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Indoor positioning plays a crucial role in various domains. It is employed in various applications, such as navigation, asset tracking, and location-based services (LBS), in Global Navigation Satellite System (GNSS) denied or degraded areas. The visual-based positioning technique is a promising solution for high-accuracy indoor positioning. However, most visual positioning research uses the side-view perspective, which is susceptible to interferences and may cause concerns about privacy and public security. Therefore, this paper innovatively proposes an up-view visual-based indoor positioning algorithm. It uses the up-view images to realize indoor positioning. Firstly, we utilize a well-trained YOLO V7 model to realize landmark detection and gross extraction. Then, we use edge detection operators to realize the precision landmark extraction, obtaining the landmark pixel size. The target position is calculated based on the landmark detection and extraction results and the pre-labeled landmark sequence via the Similar Triangle Principle. Additionally, we also propose an inertial navigation system (INS)-based landmark matching method to match the landmark within an up-view image with a landmark in the pre-labeled landmark sequence. This is necessary for kinematic indoor positioning. Finally, we conduct static and kinematic experiments to verify the feasibility and performance of the up-view-based indoor positioning method. The results demonstrate that the up-view visual-based positioning is prospective and worthy of research.

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Section: Introductionmentioning

confidence: 99%

An Up-View Visual-Based Indoor Positioning Method via Deep Learning

Chen,

Zhu

et al. 2024

Remote Sensing

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“…Conversely, the localization process can be realized by visible light positioning (VLP) systems using visible light signals. Position estimation can be achieved by using photodiode-based VLC receivers, utilizing the signals emitted by an LED transmitter at a known location [ 6 , 7 , 8 ]. VLP systems based on VLC may also be equipped with a variety of multiplexing schemes, including time-division multiplexing (TDM) and space-division multiplexing (SDM) [ 9 , 10 ].…”

Section: Introductionmentioning

confidence: 99%

Li-Pos: A Light Positioning Framework Leveraging OFDM for Visible Light Communication

Haider

Irshad

et al. 2021

Sensors

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The design of solid-state lighting is vital, as numerous metrics are involved in their exact positioning, and as it is utilized in various processes, ranging from intelligent buildings to the internet of things (IoT). This work aims to determine the power and delay spread from the light source to the receiver plane. The positions of the light source and receiver were used for power estimation. We focus on analog orthogonal frequency-division multiplexing (OFDM) in visible light communication (VLC) and assess the area under the curve (AUC). The proposed system was designed using modulation techniques (i.e., quadrature amplitude modulation; QAM) for visible light communication (VLC) and pulse-width modulation (PWM) for dimming sources. For the positioning and spreading of brightness, the proof-of-concept was weighted equally over the entire area. Therefore, the receiver plane was analyzed, in order to measure the power of each light-emitting diode (LED) in a given area, using the delayed mean square error (MSE). A framework was applied for the placement of LEDs, using full-width at half-maximum (FWHM) parameters with varying distances. Then, the received power was confirmed. The results show that the AUC using DRMS values for LEDs significantly increased (by 30%) when the number of source LEDs was changed from four to three. These results confirm that our system, associated with the simple linear lateration estimator, can achieve better energy consumption.

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