RANCANG BANGUN ALAT PENDETEKSI KANTUK PADA PENGEMUDI MOBIL BERBASIS RASPBERRY PI DAN KAMERA PI DENGAN METODE HISTOGRAM OF ORIENTED GRADIENTS - Heena Jasmine Iwan Putri Dolok Saribu (2024)
In Indonesia, the number of traffic accidents continues to increase every year. Drowsiness is one of the factors that cause traffic accidents. Drowsy conditions are very dangerous when driving because they can cause physical casualties, property losses, and cause congestion. So a tool is made that can detect drowsiness in car drivers during the day and night that can provide warnings to drivers automatically. This tool uses the Histogram of Oriented Gradients (HOG) method and two parameters in detecting drowsiness, namely eyes and mouth. The stages of the process start from taking a face image with a camera pi and processed through the raspberry pi 3 B+ as a controller, then giving output in the form of a warning alarm via a buzzer when the driver is detected to close his eyes and yawn for less than 5 seconds. Based on the results obtained in this tool experiment, this tool successfully detects drowsiness in car drivers when the tool is placed right in front of the driver with a distance of 35-65 cm, then on the right dashboard, center dashboard, and above the speedometer during the day and night with an accuracy value of 100%.