Deteksi Kantuk Untuk Keamanan Berkendara Berbasis Pengolahan Citra
DOI:
https://doi.org/10.32492/jeetech.v4i1.4107Keywords:
Raspberry Pi, Drowsiness Detection, Facial Landmark, Image ProcessingAbstract
Traffic accidents are increasing in Indonesia. One of the main causes of accidents is driver fatigue. Drowsiness generally occurs at night when the body needs rest. However, some are caused by fatigue during activities. When driving a car, this situation must be taken into account to avoid the number of accidents caused by fatigue. Because of these problems, we need a tool that can detect automatically whether the driver is asleep or conscious using the facial landmark method. The initial process starts with streaming the camera by the webcam which will be processed by the raspberry pi 3b to detect the face area using the eye aspect ratio then the algorithm on the eye aspect ratio is used to detect sleepy eyes with the output in the form of a speaker, where the speaker will emit a sound that can be changed according to at the will of the driver. This research succeeded in designing a drowsiness detection device and obtaining data from tests that have been carried out by detecting closed or closed eyes with accuracy results using the facial landmark method and eye aspect ratio detecting drowsiness with an average accuracy of 90.4%.
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