Monitoring and Control in Solar Drying Systems: A Review of Sensors, Control Strategies and Digital Architectures

Solar thermal energy for drying applications offers a sustainable pathway to help reduce post-harvest losses and decarbonize low-temperature heat processes. However, the design of solar drying systems has advanced faster than the development of robust control and monitoring strategies. Nevertheless, these advances have generated extensive reviews on dryer configurations, thermal storage, modeling tools, and product-quality outcomes, dedicated syntheses of monitoring and control remain limited. This review synthesizes recent developments in control and monitoring for solar drying systems, covering distribution, integration, and mixed configurations operating in passive and active modes. A structured search of the recent literature in major scientific databases was used to identify studies that report explicit control or monitoring strategies, including rule-based and PID controllers, fuzzy and networked control schemes, automatic monitoring systems based on low-cost microcontrollers and IoT platforms, and smart sensing approaches for estimating moisture content and drying rate. The review analyses the process variables most frequently measured and controlled (air temperature, relative humidity, airflow rate, and product moisture) and how these choices affect drying time, product quality, and energy performance. Most practical solar drying applications still use basic rule-based or PID control and data logging, while advanced control and data-driven methods are largely limited to experimental systems. The sensor limitations and the standardized metrics and measurements remain key challenges. This paper concludes with recommendations and research opportunities for developing robust, scalable, and economically viable control architectures for solar drying.