Face Landmark-Based Drowsiness Warning System for Drivers in Intelligent Transport System to Reduce Accidents with Yolov11

Ndaru Ruseno (Universitas Teknologi Muhammadiyah Jakarta)
Miswanto (Universitas Teknologi Muhammadiyah Jakarta)
Khotimah Nurhaliza Shufiyah (Muhammadiyah University of Technology)

PIKSEL : Penelitian Ilmu Komputer Sistem Embedded and Logic
Vol. 14 No. 1 (2026): March 2026

The objective of this study was to develop a drowsiness detection system that can help to reduce traffic accidents caused by drivers who are feeling sleepy. The approach employed in this study involved the use of behavioral measures to monitor the driver’s face. The study utilized a prototyping application development model, involving five cycles of testing and refinement. The results showed that the accuracy of the system prototype achieving high accuracy rates 92% compared to previous research with Yolo v11. The system prototype that generates an alert sound for five seconds when a drowsy driver is detected. Testing of the application showed that the drowsiness detection system performed well.