Pengembangan Aplikasi Perangkat Bergerak Deteksi Kantuk Bebas Pengalihan Berkendara dengan Konsep Sadar Konteks menggunakan Google Mobile Vision dan Activity Recognition pada Android - Adya Farasadi; Agi Putra Kharisma; Herman Tolle (Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer, 2021)
High number of vehicles indirectly increases the high number of deaths due to traffic accidents. One of the factors causing traffic accidents is drowsy while driving. When drowsy, the driver's attention to the road becomes less and it also reduces his responsiveness. Another factor that causes accidents is driving distraction. Similar to drowsiness, driver distraction results in less attention of the rider on the road. Based on these problems, a drowsiness detection and driving distraction free application was developed with Android-based activity recognition. This application makes use of the camera on an Android device as well as a motion sensor to detect driving activity. The camera will record the blink duration of driver's eyes to determine whether the driver is drowsy or not, which the camera will only be active while driving and simultaneously all device notifications will be turned off. From the results of black box testing, the application has a validity level of 100% for all of its functions. Then from the accuracy test results, the accuracy of drowsiness detection is 85% during the day and 65% at night. The decrease in accuracy is caused by the difference in light intensity during the day and night. Then the usability test of five respondents obtained a score of 71 which was included in the acceptable group. From the results of compatibility testing, it states that the application can run on the target API level 23 to 30.