February 28, 2023 | Advances in Applied Energy |
Introduction: Researchers from Cornell University in USA proposed the use of novel artificial intelligence (AI)-based control framework to enhance the energy efficiency of greenhouses while accurately regulating their indoor climate. The AI-based strategy learns from historical greenhouse climate data and adapts to current weather conditions and crop growth.
Key findings: In comparison to traditional control methods, the AI-based framework demonstrated remarkable performance. In a case study focused on controlling the greenhouse climate for tomato crops, the proposed strategy led to a substantial 57% reduction in energy consumption compared to conventional methods.
Read more: Energy-efficient AI-based Control of Semi-closed Greenhouses Leveraging Robust Optimization in Deep Reinforcement Learning
Fig. | Greenhouse simulation depicting the external disturbances, control actuators, and greenhouse states along with its components.