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@article{170176,
        author = {Arati V. Deshpande and Soham Kalambarkar and Aditya Kale and Raghav Joshi and Sanika Kadam and Vedika Kadam and Neel Kale},
        title = {A Hybrid Approach to Drowsiness Detection Using MediaPipe and YOLOv5},
        journal = {International Journal of Innovative Research in Technology},
        year = {2024},
        volume = {11},
        number = {6},
        pages = {3556-3561},
        issn = {2349-6002},
        url = {https://ijirt.org/article?manuscript=170176},
        abstract = {Drowsiness detection is a important factor which is used in the driving system for drivers and passengers safety to reduce the harmful accidents . This paper present a hybrid drowsiness detection system combining MediaPipe for facial landmark analysis and YOLOv5 fort face detection. The purpose of this is to strength the technology and to monitor the drivers real time drowsiness and to give appropriate alert by calculating the Eye Aspect Ratio (EAR) which calculate the eye closure of the driver},
        keywords = {Drowsiness Detection, Eye Aspect Ratio, MediaPipe, YOLOv5, Face Detection, Real-Time Monitoring.},
        month = {December},
        }