Cloud-based modeling for precision light regulation and energy efficiency optimization in hydroponic leafy vegetable production systems in plant factory - Daixuan Qu; Guohua Gao; Zihua Zhang; Zhenjiang Zhu; Junshuo Cong (Smart Agricultural Technology)
Plant factories face the dual challenge of regulating crop growth and improving energy-efficiency. Using lettuce as a model crop, we developed a cloud-based framework for precision light regulation and energy efficiency optimization. The framework consists of two main components. The first is a growth prediction model based on daily light use efficiency, informed by experimental data and environmental factor analysis. The second is a multi-objective optimization module using NSGA-II to minimize fresh weight deviation and energy consumption. Together, they produce feasible lighting strategies to support energy-efficiency cultivation. The system is deployed on a cloud platform, enabling integration with order scheduling, market forecasting, and related systems to support demand-driven production. A visual interface further supports agronomists in interpreting and adjusting lighting strategies. The proposed approach demonstrates strong potential for improving resource use under variable production conditions and offers scalability for broader application.