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Neural Network Based Detection of Driver’s Drowsiness

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preprint
posted on 23.06.2021, 04:06 by Shraddha Bhandarkar, Tanvi Naxane, Sayli Shrungare, Shivani Rajhance
The primary purpose of this paper was to propose a way to alert sleepy drivers in the act of driving. Most of the traditional methods to detect drowsiness are based on behavioral aspects while some are intrusive and may distract drivers, while some require expensive sensors/hardware. Therefore, in this paper, driver’s drowsiness detection system is developed and implemented to aid drowsy drivers from falling asleep and to prevent accidents. The system takes images from the device as input. Using these image templates, the trained model starts execution and predicts/classifies whether the face of the person in the image is drowsy or alert. The proposed model is able to achieve accuracy of 99.93% using CNN on trained image dataset.

Funding

Mitu Skillogies

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Email Address of Submitting Author

shraddhabhandrakar3@gmail.com

Submitting Author's Institution

International Institute of Information Technology

Submitting Author's Country

India

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