DLI and PPFD throughput of Solar and AI-Based Smart Lighting Apply on Illumination Stratums

Abstract

This paper aimed to address the Sustainable Development Goals (SDGs) stated by the United Nation for Food Security and create a smart lighting system that is more affordable, power-efficient, and useful by utilizing Arduino and renewable energy sources resembling solar energy. Artificial intelligence (AI) was incorporated with machine learning concepts to create a solar-sharing smart lighting system tested that was on lettuce and automatically adjusted LED illumination stratums to be suitable for indoor vertical farming, particularly with regard to high-value foods was applied on lettuce (Lactuca sativa). This paper intended to scrutinize how different illumination controls affected the growth performance, measured in terms of weekly plant growth in terms of its height. As a result, intelligent LED lighting was created to robotically alter the light intensity needed by the plants to grow indoors utilizing a hydroponics system employing Arduino technology and the Internet of Things (IoT). The study was to provide an artificial intelligence (AI) system as artificial sunlight for photosynthesis, which includes the different wavelengths of light needed by the lettuce to grow in a room or indoor setting using a hydroponics system and a solar sharing environment. It also determine the various AI models' DLI and PPFD. At different stages of growth, it provides the light needed for photosynthesis. The complete system's microprocessor manages the timing of the LEDs' on and off states as well as their brightness in response to the amount of sunlight. The growth performance of the lettuce increased after the system's effective implementation.