Road safety is a major concern; however, a great extent of the accidents is caused due to driver fatigue. Under this approach, an effective system to detect sleepy driving is sought to structure. This type of system that delves into fatigue indicators including head pose, facial expressions, and eye tracking to identify drowsiness precisely in real time utilizes methodologies such as machine learning and computer vision. The first goal is to provide early warnings which will trigger the driver and prevent potential crashes. It is from this design that drivers and other people who control virtual devices get easy, immediate integration into vehicles and personal electronic devices as it considerably diminishes drowsy driving risks. The choice of Raspberry Pi technology used at the base of this solution is also due to the combination of performance, adaptability, and cost-efficiency, thereby providing stability and general accessibility for virtually all multipurpose vehicles. Video capture and face detection are accomplished mainly by OpenCV and Haar cascade technologies. Warnings to alert drivers when their fatigue level is still at the tolerable, acceptable level is the pivotal role our technology plays in enhancing road safety by preventing accidents caused by driver fatigue and this ultimately helps to create safer driving conditions. Our system, supported by Raspberry Pi technology stands prepared as an essential tool in combating drowsy driving - making substantial contributions towards ensuring road safety and enhancing the well-being of drivers.


    Access

    Check access

    Check availability in my library

    Order at Subito €


    Export, share and cite



    Title :

    Raspberry Pi-Based Driver Drowsiness Detection




    Publication date :

    2024-02-09


    Size :

    507548 byte




    Type of media :

    Conference paper


    Type of material :

    Electronic Resource


    Language :

    English



    Driver drowsiness detection

    YANG HSIN-HSIANG / PRAKAH-ASANTE KWAKU O | European Patent Office | 2015

    Free access

    Driver Drowsiness Detection

    Rezaei, Mahdi / Klette, Reinhard | Springer Verlag | 2017


    DRIVER DROWSINESS DETECTION

    YANG HSIN-HSIANG / PRAKAH-ASANTE KWAKU O | European Patent Office | 2015

    Free access

    Driver Drowsiness Detection

    Satish, K. / Lalitesh, A. / Bhargavi, K. et al. | IEEE | 2020


    Driver Drowsiness Detection System

    Khan, Rimsha Mehnaaz / Kumar, B P Pradeep / Kabir, Sidra et al. | IEEE | 2025