Visible-Light-Based Hybrid Communication and Positioning System for Radio-Frequency-Prohibited Environment

Author(s):  
Zhitong Huang ◽  
Kaiyu Zhuang ◽  
Runmei Zhao ◽  
Yuefeng Ji
2019 ◽  
Vol 9 (6) ◽  
pp. 1048 ◽  
Author(s):  
Huy Tran ◽  
Cheolkeun Ha

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.


IEEE Access ◽  
2019 ◽  
Vol 7 ◽  
pp. 168922-168933 ◽  
Author(s):  
Mehyar Najla ◽  
Pavel Mach ◽  
Zdenek Becvar ◽  
Petr Chvojka ◽  
Stanislav Zvanovec

2021 ◽  
Author(s):  
Chin-Wei Hsu ◽  
Shang-Jen Su ◽  
You-Wei Chen ◽  
Qi Zhou ◽  
Yahya Alfadhli ◽  
...  

Author(s):  
Chun Lin ◽  
Bangjiang Lin ◽  
Xuan Tang ◽  
Zhenlei Zhou ◽  
Haiguang Zhang ◽  
...  

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