## 1 Introduction
In addition, during the drying process, the problems are exacerbated due to the use of single control variables, insufficient application of intelligent control strategies, and unstable sensor accuracy [17]. These challenges make the improvement of automated control technology in the grain-drying process an urgent issue to be addressed. In recent years, with the rapid development of technologies such as AI, IoT, and big data, automated control technology for the grain-drying process has been greatly enhanced. The extensive application of smart sensors allows the system to collect and analyze various data in the drying process in real time, ensuring precise control. The introduction of advanced control algorithms such as adaptive control [18], fuzzy logic control [19], and artificial neural networks [20] further improves the system's response speed and adaptability, making the drying process more efficient and stable. In addition, the application of IoT technology enables the remote monitoring and operation of drying equipment, greatly facilitating the management and scheduling of large-scale grain production enterprises. Nevertheless, the application of automated control technology in the domestic grain-drying process still faces many challenges. Firstly, the stability and accuracy of the control system need further improvement, especially in responding to complex environmental changes, where the system's response speed and adaptability urgently need to be enhanced [21]. Secondly, most of the current domestic drying equipment control systems are still based on simple open-loop control, with a low level of intelligence, making it difficult to achieve the refined management of the drying process. In addition, the stability and durability of sensor technology directly affect the performance of the control system, especially under harsh conditions such as high temperatures and humidity, where the reliability of sensors is particularly important. Faced with these challenges, the future development of automated control technology for the grain-drying process will move towards a more intelligent, remote, and energy-saving direction. By introducing advanced control algorithms, optimizing sensor performance, and improving system integration and stability, the grain-drying process will achieve a higher level of automation, further improving drying efficiency and reducing energy consumption [22]. At the same time, with the application of green energy technology, future grain-drying equipment is expected to reduce the environmental impact while achieving efficient drying, promoting the sustainable development of agricultural production. In summary, automated control technology for the grain-drying process is not only an important means of improving drying efficiency and quality but also a key link in achieving agricultural modernization. This article will systematically review the research status of domestic and foreign automated control technology for the grain-drying process, analyze the main problems and technical gaps, and put forward targeted optimization suggestions to provide theoretical guidance and technical support for future development directions.