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Abstract: In rolling shutter-based optical camera communication (OCC), the camera’s exposure time limits the achievable reception bandwidth. In long-exposure settings, the image sensor pixels average the incident received power, producing inter-symbol interference (ISI), which is perceived in the images as a spatial mixture of the symbol bands. Hence, the shortest possible exposure configuration should be selected to alleviate ISI. However, in these conditions, the camera produces dark images with impracticable light conditions for human or machine-supervised applications. In this paper, a novel convolutional autoencoder-based equalizer is proposed to alleviate exposure-related ISI and noise. Furthermore, unlike other systems that use artificial neural networks for equalization and decoding, the training procedure is conducted offline using synthetic images for which no prior information about the deployment scenario is used. Hence the training can be performed for a wide range of cameras and signal-to-noise ratio (SNR) conditions, using a vast number of samples, improving the network fitting and the system decoding robustness. The results obtained in the experimental validation record the highest ISI mitigation potential for Manchester encoded on-off keying signals. The system can mitigate the ISI produced by exposure time windows that are up to seven times longer than the transmission symbol duration, with bit error rates (BER) lower than 10−5 under optimal SNR conditions. Consequently, the reception bandwidth improves up to 14 times compared to non-equalized systems. In addition, under harsh SNRs conditions, the system achieves BERs below the forward error correction limit for 1dB and 5 dB while operating with exposure times that are 2 and 4 times greater than the symbol time, respectively.

Abstract: Optical Camera Communication (OCC) systems have a potential application in microalgae production plants. In this work, a proof-of-concept prototype consisting of an artificial lighting photobioreactor is proposed. This reactor optimises the culture’s photosynthetic efficiency while transmitting on-off keying signals to a rolling-shutter camera. Upon reception, both signal decoding and biomass concentration sensing are performed simultaneously using image processing techniques. Moreover, the communication channel’s theoretical modelling, the data rate system’s performance, and the plant distribution requirements and restrictions for a production-scale facility are detailed. A case study is conducted to classify three different node arrangements in a real facility, considering node visibility, channel capacity, and space exploitation. Finally, several experiments comprising radiance evaluation and Signal-to-Noise Ratio (SNR) computation are performed at different angles of view in both indoor and outdoor environments. It is observed that the Lambertian-like emission patterns are affected by increasing concentrations, reducing the effective emission angles. Furthermore, significant differences in the SNR, up to 20 dB, perceived along the illuminated surface (centre versus border), gradually reduce as light is affected by greater dispersion. The experimental analysis in terms of scattering and selective wavelength attenuation for green (Arthrospira platensis) and brown (Rhodosorus marinus) microalgae species determines that the selected strain must be considered in the development of this system.

Abstract: Optical Camera Communication (OCC) Systems have a potential application for monitoring flat-panel photobioreactors in microalgae production plants. On the transmitter side, the design of pulsed optical signals in terms of light intensity, spectral composition, and temporal variation is focused on optimizing the photosynthetic efficiency of the culture. At the reception, cameras are utilized for simultaneous online monitoring and in-situ sensing of the bioreactors culture. In this work, the analysis of the node arrangement in the plant has been carried out considering node visibility, data rate, and effective space utilization. Finally, a real experiment was performed to validate the application's feasibility.

Abstract: In color-multiplexed optical camera communications (OCC) systems, data acquisition is restricted by the image processing algorithm capability for fast source recognition, region-of-interest (ROI) detection and tracking, packet synchronization within ROI, estimation of inter-channel interference and threshold computation. In this work, a novel modulation scheme for a practical RGB-LED-based OCC system is presented. The four above-described tasks are held simultaneously. Using confined spatial correlation of well-defined reference signals within the frame’s color channels is possible to obtain a fully operating link with low computational complexity algorithms. Prior channel adaptation also grants a substantial increase in the attainable data rate, making the system more robust to interferences.

Abstract: Nowadays Optical Camera Communications (OCC) have acquired an important relevance within the Visible Light Communications' (VLC) field. However, this technique faces challenges related to computational load and packet synchronization. In this work, a synchronous modulation scheme for OCC is presented. It is based on the wavelength-division multiplexing of RGB light sources for the generation of two different signals. The first one carries the data, using two of the independent channels, while the other provides the transmission clock and frame synchronization. In this way, the demodulation is significantly improved, since the clock recovery process and the frame detection are highly simplified.