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Real-Time Torpidity Detection for Drivers in Machine Learning Environments
Abstract
The World Health Organization (WHO) has conducted a survey on road accidents around the world. According to the survey, 13.5 lakh die each year due to road casualties and more concerning is that India accounts around 1.5 lakh road deaths every year. Major factors to blame on road accidents are driver carelessness, drowsiness, traffic discipline, vehicle faults, or even animal crossing. Different sensors, stability control systems, anti-breaking systems, navigation are added in the vehicles to make driving easier. Still, road accidents happen due to human mistakes. Drinking and driving and tiredness may cause a driver to go for torpidity. A machine learning system is developed to monitor the eye movements to detect if the driver is sleepy or not. If found, an alarm is issued to warn the driver to wake up or else to stop the vehicle and have a nap. In addition, if neither response is made, water sprinkling is automated on the driver's face.
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