Employing DIALux to relieve machine-learning training data collection when designing indoor positioning systems

Song, Shao-Hua; Lin, Dong-Chang; Liu, Yang; Chow, Chi‐Wai; Chang, Yun-Han; Lin, Kon‐Ping; Wang, Yichang; Chen, Yiyuan

doi:10.1364/oe.422851

Cited by 20 publications

(8 citation statements)

References 13 publications

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“…Sensors are installed on the left and right sides of the intelligent robot. During the specific travel process, the sensors collect the corresponding rotational speed and position data to calculate the speed of the wheels, and then transmit the corresponding rotational speed data to the server for fusion through the corresponding electronic compass data, to achieve the measurement and calculation of the robot coordinates and position in the moving distance [23,24]. In addition, the analysis of sensor data is required to analyze the specific model of Bluetooth positioning and realize the specific calculation of indoor position by classifying and inputting the data.…”

Section: System Analysis Of Mobile Positioningmentioning

confidence: 99%

Research on Indoor Environment Positioning System considering Multisensor in the Multi-Information Data Fusion

2022

Mobile Information Systems

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Outdoor positioning can often achieve accurate positioning according to GPS and mobile phone signaling, while indoor positioning is difficult to meet the needs of practical application due to the limitations of satellite reception. In order to effectively solve the problem of large error in the individual positioning strategy in the indoor environment, this paper applies multisensor in the multisource information fusion indoor positioning system. By using the positioning results of multiple sensors to limit the range of geomagnetic matching for combined matching, the matching error can be effectively reduced. Then, the global optimal value of indoor network is calculated by using the multi-information data fusion algorithm, which can optimize the initial value and threshold of the multi-information data fusion algorithm, improve the network accuracy as much as possible, and accelerate the convergence speed at the same time. After completing the optimization processing, the indoor network can obtain the combined positioning and predicted positioning results, so as to facilitate the fusion training to the actual position coordinates, and finally obtain the optimal positioning results. The simulation results show that the mean square error predicted by the multi-information data fusion algorithm calculated by the multi-information data fusion algorithm can be effectively reduced by 76%, and the fusion positioning accuracy can be improved by 48% compared with the accuracy of a single positioning strategy. The method proposed in this paper effectively improves the positioning accuracy, indicating that the positioning performance is better.

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Section: System Analysis Of Mobile Positioningmentioning

confidence: 99%

Research on Indoor Environment Positioning System considering Multisensor in the Multi-Information Data Fusion

2022

Mobile Information Systems

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“…In the visible light positioning system, the noise in the link has a great influence on the positioning accuracy, and the noise described in this section is the interference caused by other factors in removing the reflected light part of the wall received by the receiving end PD, which is defined as narrow noise [ 21 ].…”

Section: Channel Characteristics and Received Power Distributionmentioning

confidence: 99%

Research and Implementation of Indoor 3D Positioning Algorithm Based on LED Visible Light Communication and Corresponding Parameter Estimation

2022

Computational Intelligence and Neuroscience

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In the era of mobile Internet, the application of various positioning-based location service systems is becoming more and more common. In addition, the traditional radio positioning system is limited in the use of special environments such as mines, hospitals, and gas stations, and long-term electromagnetic radiation can cause potential damage to the human body. Compared with the traditional wireless positioning technology, VLC-based positioning technology has a good application prospect in the field of indoor wireless positioning. Compared with traditional radio positioning technology, the use of VLC technology to achieve indoor positioning is different in that the system design and layout need to consider the basic needs of indoor lighting; that is, the layout of multiple visible light sources in the room should meet the minimum illumination requirements of any area of the room. Since the layout structure of the light source that only considers the lighting requirements or only considers the positioning accuracy requirements is not the same, in the design process of the indoor visible light wireless positioning system, it is necessary to consider the overall optimization layout of multiple indoor visible light sources under the conditions of lighting and positioning constraints. This paper mainly optimizes indoor positioning from the aspects of light source layout, reflected light intensity distribution, and noise model.

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“…The human eye cannot detect intensity modulation pulses and preserves them as a constant light [ 9 ]. Additionally, LEDs can be utilized in many fascinating applications, including localization, positioning [ 10 , 11 ], intelligent transportation systems [ 6 ], underwater communication [ 12 ], etc. LEDs have an extended lifetime, low power consumption (they conserve energy by 80% [ 13 ]), low cost, and a smaller carbon footprint in comparison with traditional lighting sources [ 14 ].…”

Section: Introductionmentioning

confidence: 99%

A Superimposed QD-Based Optical Antenna for VLC: White LED Source

2022

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Visible light communication (VLC) is a versatile enabling technology for following high-speed wireless communication because of its broad unlicensed spectrum. In this perspective, white light-emitting diodes (LED) provide both illumination and data transmission simultaneously. To accomplish a VLC system, receiver antennas play a crucial role in receiving light signals and guiding them toward a photodetector to be converted into electrical signals. This paper demonstrates an optical receiver antenna based on luminescent solar concentrator (LSC) technology to exceed the conservation of etendue and reach a high signal-to-noise ratio. This optical antenna is compatible with all colors of LEDs and achieves an optical efficiency of 3.75%, which is considerably higher than the similar reported antenna. This antenna is fast due to the small attached photodetector—small enough that it can be adapted for electronic devices—which does not need any tracking system. Moreover, numerical simulation is performed using a Monte Carlo ray-tracing model, and results are extracted in the spectral domain. Finally, the fate of each photon and the chromaticity diagram of the collected photons’ spectra are specified.

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Employing DIALux to relieve machine-learning training data collection when designing indoor positioning systems

Cited by 20 publications

References 13 publications

Research on Indoor Environment Positioning System considering Multisensor in the Multi-Information Data Fusion

Research on Indoor Environment Positioning System considering Multisensor in the Multi-Information Data Fusion

Research and Implementation of Indoor 3D Positioning Algorithm Based on LED Visible Light Communication and Corresponding Parameter Estimation

A Superimposed QD-Based Optical Antenna for VLC: White LED Source

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