An FPGA-in-the-Loop Simulation of a Neural Network-based Optimization of Greenhouse Supplemental Illumination

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—Greenhouse crops depend on sufficient amount of light to achieve photosynthetic efficiency resulting to their full development and growth. So supplemental illumination is needed when insufficient light has accumulated throughout the day to help achieve the required Daily Light Integral (DLI) for the crops. The lighting schedule and the energy usage are the top concerns of the crop growers in their supplemental lighting operations. In this study, an FPGA-based system was developed to manage the operations of the supplemental illumination, giving the crop growers the option to set the lighting schedule and the target DLI supplementation by selecting the desired energy saving mode. The designed system was able to control the lighting operation within the lighting schedule set by the user. Its capability of saving energy is dependent on the daytime lighting. In testing, the system was able to save energy when high to average energy saving mode selected for low to average target DLI, but not when selecting low energy saving mode for high target DLI supplementation. The system was capable of achieving the target DLI value based on the chosen target DLI requirement for the crops.