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Advanced driver fatigue detection by integration of OpenCV, DNN module and deep learning
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Academic Editor: VIJAYAKUMAR ANAND
Published:
13 March 2023
by MDPI
in Holography Meets Advanced Manufacturing
session Industry Applications
Abstract:
Road safety is significantly impacted by drowsiness or weariness, which is a primary contributor to auto accidents. If drowsy drivers are informed in advance, many fatal incidents can be avoided. Over the past 20 to 30 years, the number of road accidents and injuries in India has been rising alarmingly. According to the experts, the main cause of this issue is that drivers who do not take frequent rests when travelling long distances run a great danger of becoming drowsy, which they frequently fail to identify early enough. There are several drowsiness detection techniques that track a driver's level of tiredness while they are operating a vehicle and alert them if they are not paying attention to the road. This study describes a noncontact way for determining a driver's tiredness utilising detecting techniques
Keywords: OpenCV , DNN , Deep learning, Drowsy driver fatigue
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