ELECTRONICS, cilt.14, sa.14, 2025 (SCI-Expanded)
It is projected that the world population will quadruple over the next century, and to meet future food demands, agricultural production will need to increase by 70%. Therefore, there has been a transition from traditional farming methods to autonomous modern agriculture. One such modern technique is aeroponic farming, in which plants are grown without soil under controlled and hygienic conditions. In aeroponic farming, plants are significantly less affected by climatic conditions, infectious diseases, and biotic and abiotic stresses, such as pest infestations. Additionally, this method can reduce water, nutrient, and pesticide usage by 98%, 60%, and 100%, respectively, while increasing the yield by 45-75% compared to traditional farming. In this study, a three-dimensional industrial design of an innovative aeroponic plant growth chamber was presented for use by individuals, researchers, and professional growers. The proposed chamber design is modular and open to further innovation. Unlike existing chambers, it includes load cells that enable real-time monitoring of the fresh weight of the plant. Furthermore, cameras were integrated into the chamber to track plant growth and changes over time and weight. Additionally, RGB power LEDs were placed on the inner ceiling of the chamber to provide an optimal lighting intensity and spectrum based on the cultivated plant species. A customizable chamber design was introduced, allowing users to determine the growing tray and nutrient nozzles according to the type and quantity of plants. Finally, system models were developed for temperature control of the chamber. Temperature control was implemented using a proportional-integral-derivative controller optimized with particle swarm optimization, radial movement optimization, differential evolution, and mayfly optimization algorithms for the gain parameters. The simulation results indicate that the temperatures of the growing and feeding chambers in the cabinet reached a steady state within 260 s, with an offset error of no more than 0.5 degrees C. This result demonstrates the accuracy of the derived model and the effectiveness of the optimized controllers.