Optimizing Artificial Lighting System for Indoor Farming Using Genetic Algorithm

Indoor farming based on artificial intelligence (Smart System) is a form of precision farming. The success parameter of precision farming is the accuracy in measuring and controlling agricultural environment. Holistic control over the environment of indoor farming included, but not limited to lighting, nutrition, humidity and air temperature regulation. Nonetheless, lighting system as a source of plant energy is regularly becoming major issue in indoor farming. In order to provide sufficient light for indoor plant growth, it is necessary to manipulate artificial lighting with a certain spectrum range. However, it has become a problem because the plants need different light spectrum and intensity depending on their age. The light spectrum is electromagnetic radiation visible to the human eye and is arranged based on wavelength, although intensity is the amount of light achieved by plants that is related to the height of the light source. This research aims to use genetic algorithm to engineer the optimal lighting system for plants based on their age. The object of this study is brassica rapa species, which were classified into four age groups, namely group A (0-7 days), group B (7-21 days), group C (21-27 days), and group D (27-33 days). The research results showed that the optimal lighting for group A is 100 cm height and 620-750 nm spectrum, group B is 50 cm height and 380-450 nm, group C is 25 cm height and 380-750 nm, and group D 20 cm height and 750 nm. According to the optimization of the lighting process, 33 days old brassica plants that was observed had leaves with the average length of 16.66 cm, around 2.44 cm larger than the plants with static lighting at 50 cm height and 380-450 nm spectrum at the same age.