An Accurate Visible Light Positioning System Using Regenerated Fingerprint Database Based on Calibrated Propagation Model

2019 ◽  
Vol 68 (8) ◽  
pp. 2714-2723 ◽  
Author(s):  
Fakhrul Alam ◽  
Moi Tin Chew ◽  
Tapiwanashe Wenge ◽  
Gourab Sen Gupta
Keyword(s):  
Visible Light ◽  
Propagation Model ◽  
Positioning System ◽  
Fingerprint Database

scholarly journals Light positioning: A high-accuracy visible light indoor positioning system based on attitude identification and propagation model

2018 ◽  
Vol 14 (2) ◽  
pp. 155014771875826 ◽  
Author(s):  
Qu Wang ◽  
Haiyong Luo ◽  
Aidong Men ◽  
Fang Zhao ◽  
Xile Gao ◽  
...  
Keyword(s):  
Visible Light ◽  
Light Propagation ◽  
Light Emitting Diode ◽  
Indoor Positioning ◽  
Propagation Model ◽  
Small Scale ◽  
Positioning System ◽  
Light Emitting ◽  
Algorithm Construct ◽  
Indoor Positioning System

With the booming development of green lighting technology, visible light-based indoor localization has attracted a lot of attention. Visible light-based indoor positioning technology leverages a light propagation model to pinpoint target location. Compared with the radio localization technology, visible light-based indoor positioning not only can achieve higher location accuracy, but also no electromagnetic interference. In this article, we propose LIPOS, a three-dimensional indoor positioning system based on attitude identification and visible light propagation model. The LIPOS system takes advantage of the existing lighting infrastructures to localize mobile devices that have light-sensing capabilities (e.g. a smartphone) using light emitting diode lamps as anchors. The system can accurately identify the attitude of a smartphone using its integrated sensors, distinguish different light emitting diode beacons using the fast Fourier transform algorithm, construct a position cost-function based on a visible light radiative decay model, and apply a nonlinear optimizing method to acquire the optimal estimation of final location. We have implemented the LIPOS system and evaluated it with a small-scale hardware testbed, as well as moderate-sized simulations. Extensive experiments are performed in three representative indoor environments—open-plan office, cubicle, and corridor, which not only demonstrate that the LIPOS can effectively avoid the negative effects of dynamic change of a smartphone’s attitude angle, but also show better locating accuracy and robustness, and obtain sub-meter level positioning accuracy.

scholarly journals Improved Visible Light-Based Indoor Positioning System Using Machine Learning Classification and Regression

2019 ◽  
Vol 9 (6) ◽  
pp. 1048 ◽  
Author(s):  
Huy Tran ◽  
Cheolkeun Ha
Keyword(s):  
Machine Learning ◽  
Visible Light ◽  
Noise Reduction ◽  
Indoor Positioning ◽  
Computational Time ◽  
Dual Function ◽  
Positioning System ◽  
Positioning Accuracy ◽  
Positioning Systems ◽  
Machine Learning Classification

Recently, indoor positioning systems have attracted a great deal of research attention, as they have a variety of applications in the fields of science and industry. In this study, we propose an innovative and easily implemented solution for indoor positioning. The solution is based on an indoor visible light positioning system and dual-function machine learning (ML) algorithms. Our solution increases positioning accuracy under the negative effect of multipath reflections and decreases the computational time for ML algorithms. Initially, we perform a noise reduction process to eliminate low-intensity reflective signals and minimize noise. Then, we divide the floor of the room into two separate areas using the ML classification function. This significantly reduces the computational time and partially improves the positioning accuracy of our system. Finally, the regression function of those ML algorithms is applied to predict the location of the optical receiver. By using extensive computer simulations, we have demonstrated that the execution time required by certain dual-function algorithms to determine indoor positioning is decreased after area division and noise reduction have been applied. In the best case, the proposed solution took 78.26% less time and provided a 52.55% improvement in positioning accuracy.

Real-time Demonstration of 5G MMW Beamforming and Tracking Using Integrated Visible Light Positioning System

2021 ◽  
Author(s):  
Chin-Wei Hsu ◽  
Shang-Jen Su ◽  
You-Wei Chen ◽  
Qi Zhou ◽  
Yahya Alfadhli ◽  
...  
Keyword(s):  
Visible Light ◽  
Real Time ◽  
Positioning System
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