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@article{161830,
        author = {Sagar Kawale and Divya Surve and Saurabh Bandal and Aishwarya Bhosale},
        title = {DRIVER DROWSINESS DETECTION SYSTEM WITH MANY ALERTS SOUNDS IN MACHINE LEARNING},
        journal = {International Journal of Innovative Research in Technology},
        year = {},
        volume = {10},
        number = {6},
        pages = {315-318},
        issn = {2349-6002},
        url = {https://ijirt.org/article?manuscript=161830},
        abstract = {Drivers who do not take regular breaks when driving long distances run a high risk of becoming drowsy, a state which they often fail to recognize early enough according to the experts. According to research it is proven that more than one quarter of the road accidents happen due to the drowsiness of the driver which means that more accidents are caused due to tired drivers rather than the drivers who are drunk. In state of extended speed range, a system can notify drivers about their inattentiveness and state of fatigue with the help of an alarm. There are many such alarm systems which are focusing on alerting the driver because accidents caused due to human error are increasing day by day and causing many deaths and injuries worldwide. The main reasons that cause fatal crashes and highway accidents these days are the drowsiness and sleeping of the driver. Driver drowsiness detection system is a safety technology that can prevent accidents that are caused by drivers who fell asleep while driving. This system will alert the driver when the drowsiness is detected and hence prevent the accidents from taking place.},
        keywords = {Haar Classifier, Face Detection, Eye Tracking, Eye Detection, blink pattern, Driver Drowsiness Detection.},
        month = {},
        }