The garlic combine harvester has essentially realized the mechanized harvesting of garlic. However， its intelligence level is relatively low. During the operation， problems such as yaw， overflow and blockage are prone to occur， which affect the operation quality and harvesting efficiency of the whole machine. To address these issues， this paper presents an STM32-Based real-time monitoring system for garlic combine harvesters， which can monitor the yawing， overflow， and blockage failure problems in real-time with high accuracy， and can also provide voice broadcast reminders. The system comprised a row assist modules， a yield monitoring module， a fault diagnosis module and an STM32 microcontroller. The row assist modules utilized an MPU6050 gyroscope to ascertain the direction of the harvester， which was then compared with the set direction angle warning and alarm threshold to determine whether the harvester had deviated from the normal operational route. The yield monitoring module multiplied the weight of a single garlic by the total number of garlic counts to calculate the total weight of the harvested garlic， and compared it with the set threshold of the full bin to ascertain whether the collection bin was indeed full. Fault diagnosis was performed by the Hall sensor， which collected the rotational speed of the follower wheel of the clamping and conveying mechanism and compared it with the set threshold to judge whether a blockage occurrs. The maximum error value of the row assist module， as determined through indoor commissioning， was 1.3°. The minimum error value was 0.2°. The yield detection module monitoring count accuracy was 96.7%. The fault diagnosis module identified the average error value of rotational speed as 0.8 r/min， with an error rate of 0.4%. This enabled the module to accurately monitor the follower wheel rotational speed changes when the clamping device was blocked. The results of the field test demonstrate that the designed monitoring system is feasible， accurate and stable. The findings of this study indicate that the proposed monitoring system can operate reliably over an extended period， issuing timely alerts when the garlic harvester is exhibiting signs of yawing， overflowing， and blocking issues. This could markedly enhance the operational quality and efficiency of traditional garlic harvesters.