Achmadha, Zharvi (2024) RANCANG BANGUN APLIKASI PENDETEKSI KANTUK PENGEMUDI MOBIL BERBASIS ANDROID MENGGUNAKAN METODE FACE RECOGNITION DAN FACE LANDMARK. Undergraduate thesis, UPN Veteran Jawa Timur.
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Abstract
The traffic accidents caused by driver drowsiness or fatigue pose a serious threat to road safety. One effort to prevent such accidents is by accurately and early detecting signs of drowsiness in drivers. This research develops a drowsiness detection system using face recognition and face landmark methods integrated into a mobile application. The primary objective of this study is to identify the driver's face using the MobileFaceNet machine learning model and detect signs of drowsiness, such as closed eyes or yawning, through face landmarks. The application includes a warning notification before activating the drowsiness detection feature and an alarm that sounds when signs of drowsiness are detected in the driver. The results of this research demonstrate the effectiveness of applying face recognition and face landmark methods in identifying the driver's face and detecting signs of drowsiness with a quick response time of 2.2 seconds. By analyzing the patterns of driver drowsiness, this system can provide early warnings, enabling the implementation of preventive measures before hazardous situations occur on the road. The lightweight application, with a size of 29 MB, operates stably without requiring high resources, making a potential contribution to minimizing the risk of traffic accidents caused by driver drowsiness.
| Item Type: | Thesis (Undergraduate) | ||||||||||||
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| Subjects: | R Medicine > R Medicine (General) T Technology > T Technology (General) > T385 Computer Graphics |
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| Divisions: | Faculty of Computer Science > Departemen of Information Systems | ||||||||||||
| Depositing User: | Zharvi Achmadha | ||||||||||||
| Date Deposited: | 22 Jan 2024 02:57 | ||||||||||||
| Last Modified: | 22 Jan 2024 02:57 | ||||||||||||
| URI: | http://repository.upnjatim.ac.id/id/eprint/20448 |
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