Intelligent Greenhouse Temperature Management: A Closed-Loop Perspective on Sensing, Modeling, Control, and Deployment

Greenhouse cultivation plays an important role in food security, resource-use efficiency, and sustainable agricultural development. Temperature management is particularly critical because it directly affects crop growth, yield and quality, energy consumption, and environmental control. To clarify the technological pathways, application boundaries, and future directions of intelligent greenhouse temperature management, this review synthesizes recent studies from a closed-loop perspective. A structured narrative approach was adopted to organize the literature around an integrated framework linking multi-source sensing and data governance, predictive modeling, control strategies, system deployment, and feedback-based operation and maintenance. The review first examines the roles of sensors, Internet of Things (IoT) technologies, wireless sensor networks, and multi-source data fusion in reliable greenhouse state perception. It then compares mechanistic, machine-learning, deep-learning, hybrid and physics-guided models in terms of prediction capability, interpretability, generalization, uncertainty, and control compatibility. Control strategies ranging from rule-based and fuzzy control to model predictive control, reinforcement learning, and RL-MPC are further evaluated with respect to constraints, adaptability, energy efficiency, and operational safety. Finally, edge–cloud collaboration, digital twins, safety fallback, and model lifecycle management are discussed as key enablers for translating prediction and control methods into deployable closed-loop systems. Overall, recent advances indicate that high prediction accuracy alone is insufficient for practical greenhouse management; reliable sensing, trustworthy modeling, safe control, system integration, and long-term maintainability must be considered jointly. Future research should therefore move toward crop-oriented, energy-efficient, trustworthy, and practically deployable closed-loop systems for intelligent greenhouse temperature management.