Driver Drowsiness Detection

Authors: Prof. M.S. Khan, Tejas Belekar, Prasad Halde, Vishal Kushare, Vishnu Labhade

Country: India

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Abstract: This system presents an innovative approach leveraging the Raspberry Pi platform for the simultaneous detection of driver drowsiness and alcohol levels, aimed at enhancing road safety. The integration of computer vision and sensor technologies establishes a robust framework capable of real-time monitoring and alerting within vehicular environments.The drowsiness detection module employs a Raspberry Picompatible camera to track facial landmarks, monitoring key indicators such as eye closure duration and head position. Machine learning algorithms, including facial recognition and pattern analysis, ascertain driver fatigue, triggering timely alerts or interventions to prevent potential accidents.In parallel, the alcohol detection system incorporates sensor modules interfaced with the Raspberry Pi to measure alcohol vapors within the vehicle cabin. Utilizing gas sensors or breathalyzers, this module continuously samples air quality, identifying alcohol presence and quantifying levels exceeding legal limits. Integration with vehicle control systems enables proactive measures like disabling ignition or notifying authorities when necessary.The proposed system amalgamates these functionalities into a cohesive framework, offering a comprehensive solution for proactive safety measures in automobiles. By leveraging the computational capabilities of the Raspberry Pi and amalgamating sensor technologies, this approach aims to significantly reduce the risks associated with drowsy and inebriated driving, ultimately contributing to the overall enhancement of road safety.

Keywords: Raspberry Pi platform, Driver drowsiness, Alcohol detection, Road safety, Computer vision, Sensor technologies, Real-time monitoring

Paper Id: 230622

Published On: 2024-05-03

Published In: Volume 12, Issue 3, May-June 2024

Cite This: Driver Drowsiness Detection - Prof. M.S. Khan, Tejas Belekar, Prasad Halde, Vishal Kushare, Vishnu Labhade - IJIRMPS Volume 12, Issue 3, May-June 2024.

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