scholarly journals Reduced Tilting Effect of Smartphone CMOS Image Sensor in Visible Light Indoor Positioning

Electronics ◽  
2020 ◽  
Vol 9 (10) ◽  
pp. 1635
Author(s):  
Md Habibur Rahman ◽  
Mohammad Abrar Shakil Sejan ◽  
Jong-Jin Kim ◽  
Wan-Young Chung
Keyword(s):  
Machine Learning ◽  
Visible Light ◽  
Light Emitting Diode ◽  
Cmos Image Sensor ◽  
Indoor Positioning ◽  
Image Sensor ◽  
Image Features ◽  
Oxide Semiconductor ◽  
Positioning System ◽  
Indoor Positioning System

Visible light positioning (VLP) using complementary metal–oxide–semiconductor (CMOS) image sensors is a cost-effective solution to the increasing demand for an indoor positioning system. However, in most of the existing VLP systems with an image sensor, researchers assume that the receiving image sensor is positioned parallel to the indoor floor without any tilting and, thus, have only focused on the high-precision positioning algorithm and ignored the proper light-emitting diode (LED)-ID recognition. To address these limitations, we present, herein, a smartphone CMOS image sensor and visible light-based indoor localization system for a receiver device in a tilted position, and we have applied a machine learning approach for optimized LED-ID detection. For detection of the LED-ID, we generated different features for different LED-IDs and utilize a machine learning method to identify each ID as opposed to using the conventional coding and decoding method. An image processing method was used for the image features extraction and selection. We utilized the rolling shutter mechanism of the smartphone CMOS image sensor in our indoor positioning system. Additionally, to improve the LED-ID detection and positioning accuracy with the tilting of the receiver, we utilized the embedded fusion sensors of the smartphone (e.g., accelerometer, gyroscope, and magnetometer, which can be used to extract the yaw, pitch, and roll angles). The experimental results for the proposed positioning system show that it can provide 2.49, 4.63, 8.46, and 12.20 cm accuracy with angles of 0, 5, 10, and 15°, respectively, within a 2 m × 2 m × 2 m positioning area.

scholarly journals High Precision Indoor Visible Light Positioning Algorithm Based on Double LEDs Using CMOS Image Sensor

2019 ◽  
Vol 9 (6) ◽  
pp. 1238 ◽  
Author(s):  
Weipeng Guan ◽  
Xinjie Zhang ◽  
Yuxiang Wu ◽  
Zekun Xie ◽  
Jingyi Li ◽  
...  
Keyword(s):  
Visible Light ◽  
Real Time ◽  
Computing Time ◽  
Computational Cost ◽  
Cmos Image Sensor ◽  
Indoor Positioning ◽  
Image Sensor ◽  
Positioning System ◽  
Satisfactory Performance ◽  
Positioning Algorithm

Visible Light Positioning (VLP) is widely recognized as a cost-effective solution for indoor positioning with increasing demand. However, the nonlinearity and highly complex relationship between three-dimensional world coordinate and two-dimensional image coordinate hinders the good performance of image-sensor-based VLP. Therefore, there is a need to develop effective VLP algorithms to locate the positioning terminal using image sensor. Besides, due to the high computational cost of image processing, most existing VLP systems do not achieve satisfactory performance in terms of real-time ability and positioning accuracy, both of which are significant for the performance of indoor positioning system. In addition, the accurate identification of the ID information of each LED (LED-ID) is important for positioning, because if the LED-ID is not recognized well, the positioning can only be achieved in a particular positioning unit and cannot be applied to a large scene with many LEDs. Therefore, an effective image-sensor-based double-light positioning system is proposed in this paper to solve the above problems. We also set up relevant experiments to test the performance of the proposed system, which utilizes the rolling shutter mechanism of the Complementary Metal Oxide Semiconductor (CMOS) image sensor. Machine learning was used to identify the LED-ID for better results. Simulation results show that the proposed double-light positioning system could deliver satisfactory performance in terms of both the real-time ability and the accuracy of positioning. Moreover, the proposed double-light positioning algorithm has low complexity and takes the symmetry problem of angle into consideration, which has never been considered before. Experiments confirmed that the proposed double-light positioning system can provide an accuracy of 3.85 cm with an average computing time of 56.28 ms, making it a promising candidate for future indoor positioning applications.

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.

scholarly journals Indoor Positioning System using LED Lights and a Dual Image Sensor

2015 ◽  
Vol 19 (6) ◽  
pp. 586-591 ◽  
Author(s):  
Myoung-geun Moon ◽  
Su-il Choi ◽  
Jaehyung Park ◽  
Jin Young Kim
Keyword(s):  
Indoor Positioning ◽  
Image Sensor ◽  
Positioning System ◽  
Dual Image ◽  
Led Lights ◽  
Indoor Positioning System
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