<![CDATA[Microsleep is a brief state of sleep that occurs suddenly without the person being aware of it and poses a serious risk to drivers, especially on long journeys. This study developed an intelligent alert system based on the YOLOv8 algorithm for the early detection of microsleep in drivers in real time by analyzing the state of the eyes and the position of the head. Using 3,458 annotated facial images as training data, the model was implemented on the Raspberry Pi platform for local processing without cloud dependency. The system activates a buzzer and warning light when it detects signs of drowsiness. Test results show the effectiveness of this method in the early detection of microsleep with 90.3% precision, 91.3% accuracy, 96.8% recall, and an F1 score of 93.9%. It has been shown to function optimally in a variety of lighting conditions to improve road safety.]]>
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