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@article{159980,
        author = {Dhanashri Rajput and Aryan.V.Dharmadhikari and Ayush.S.Dhangar and Tanish.N.Dhangar and Manish.S.Dhane and Roshani.D.Dhembare},
        title = {Driver Drowsiness Detection and Alarming System},
        journal = {International Journal of Innovative Research in Technology},
        year = {},
        volume = {9},
        number = {12},
        pages = {1190-1194},
        issn = {2349-6002},
        url = {https://ijirt.org/article?manuscript=159980},
        abstract = {The majority of reported accidents in our nation are the result of drowsy or distracted driving on the part of the driver. If the drivers had been woken up at the appropriate time, the accidents brought on by sleep-deprived drivers would have been avoided. The accidents and fatalities could have been avoided by creating a device that can identify when the eyes are closed. We have developed a hardware and software solution that might be used to track a driver's eye locations and alert him if his eyes are closed for longer than three seconds.},
        keywords = {Sleep Deprived Driving, Python, Arduino, image processing, OpenCV, EAR (Eye Aspect Ratio)},
        month = {},
        }