Driver Drowsiness Detection Using Inceptionv3 with Automatic Whatsapp Message Sender
Keywords:
Driver drowsiness, InceptionV3, Deep learning, Facial expression, Real-time processing, Automatic message sending on WhatsAppAbstract
Human Driver drowsiness is one of the main reasons for road accidents in the world. To prevent such accidents, a driver drowsiness detection system is proposed in this research paper. InceptionV3, a deep learning architecture, is used to classify the driver's facial expressions and detect drowsiness. The system is integrated with a real time frame capturing camera, which captures the driver's face, and the model processes the images in real-time to identify drowsiness of the human driver. Once the system detects that the driver is drowsy, an automatic WhatsApp message is sent to a predefined contact to alert them of the situation. This proposed system yields higher accuracy in drowsiness detection, and the automatic WhatsApp message sending feature can provide timely assistance to prevent potential accidents.
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References
https://www.academia.edu/38928274/REAL_TIME_SLEEP_DROWSINESS_DETECTION_Project_Report
https://www.researchgate.net/publication/336878674_DRIVER_DROWSINESS_DETECTION_SYSTEM
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