RESUMO
We propose and demonstrate a received-signal-strength (RSS) based visible light positioning (VLP) system using a low-cost organic photovoltaic cell (OPVC) receiver (Rx). The OPVC is a passive device without the need of external power supply. It could detect VLC signal and harvest energy. Our developed OPVC has a high power conversion efficiency (PCE) of 9.8%. The VLP system can be operated at a low illumination of 130 lux. The regression machine learning (ML) algorithm is used to enhance the positioning accuracy.
RESUMO
We propose and demonstrate a light-panel and rolling-shutter-effect (RSE) camera-based visible light communication (VLC) system using Z-score normalization, red/green/blue (RGB) color channel separation, and 1-D artificial neural network (ANN). The proposed scheme can mitigate the high inter-symbol interference (ISI) generated by the RSE pattern due to the low pixel-per-bit and high noise-ratio (NR) of the display contents.
RESUMO
We demonstrate a visible light communication (VLC) system using light emitting diode (LED) backlight display panel and mobile-phone complementary-metal-oxide-semiconductor (CMOS) camera. The panel is primarily used for displaying advertisements. By modulating its backlight, dynamic contents (i.e. secondary information) can be transmitted wirelessly to users based on rolling shutter effect (RSE) of the CMOS camera. As different display content will be displayed on the panel, the VLC performance is significantly limited if the noise-ratio (NR) is too high. Here, we propose and demonstrate a CMOS RSE pattern demodulation scheme using grayscale value distribution (GVD) and machine learning algorithm (MLA) to significantly enhance the demodulation.