부산대학교 도서관

Drowsiness is one of the main causes of traffic accidents. This work presents a Raspberry Pi 4-based drowsiness detection system that uses closed eyes detection to identify drowsy drivers. The system uses a camera module to capture images of the driver's face and then applies the Haar cascade algorithm to detect if the driver's eyes are closed for more than a certain amount of time, in case of exceeding that time, the system will sound an alarm to alert the driver, and with this, it can prevent accidents by promptly alerting the driver if they have fallen asleep. Furthermore, it is highlighted that the device does not pose a visual obstruction or cause any discomfort due to its size and operation.