JOURNAL ARTICLE

Driver Drowsiness Detection System with OpenCV and Keras

Alok Kumar SinghAditya V. MadaneShubham S. Fargade

Year: 2024 Journal:   International Journal of Advanced Research in Science Communication and Technology Pages: 232-239   Publisher: Shivkrupa Publication's

Abstract

This Drowsy Driver Detection System is based on the idea of computer vision-based thinking. The camera serves as the system's starting point by giving the framework that concentrates it the driver's live feed. directly at the driver's face and examines their eyes with the specific goal of detecting any signs of drowsiness. In situations where the analysis reveals drowsiness, the driver receives an alert from the live video. Using information gleaned from the image, the Framework advances the program's control to locate the facial touristspots, which assist the system in determining an individual's eye location. The suggested framework determines that the driver is feeling sleepy and that a safety alarm is sound if the driver's eyes are closed for a predetermined period of time. After a face is first identified and eyes are identified, the system functions effectively in low light levels

Keywords:
Computer vision ALARM Artificial intelligence Computer science Face (sociological concept) Face detection Point (geometry) Facial recognition system Engineering Feature extraction Mathematics

Metrics

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Cited By
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FWCI (Field Weighted Citation Impact)
13
Refs
0.24
Citation Normalized Percentile
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Topics

Video Surveillance and Tracking Methods
Physical Sciences →  Computer Science →  Computer Vision and Pattern Recognition
Fire Detection and Safety Systems
Physical Sciences →  Engineering →  Safety, Risk, Reliability and Quality
Vehicle License Plate Recognition
Physical Sciences →  Engineering →  Media Technology
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