Advanced International Journal for Research

E-ISSN: 3048-7641   •   Impact Factor: 9.11

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Volume 7 Issue 3
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Design and Implementation of Real-Time Driver Drowsiness Detection Systems

Author(s) Yashika A. Chhatre, Prof. Puneshkumar U. Tembhare, Surbhi J. Budekar, Aachal L. Ghivtonde, Chinkita L. Patle, Ruchita M. Nandurkar
Country India
Abstract Driver drowsiness is a significant factor contributing to road accidents worldwide due to reducedalertness and delayed reaction time. This paper presents the design and implementation of a real-timedriver drowsiness detection and alert system using computer vision and machine learning techniques.The proposed system continuously monitors the driver’s facial features through an in-vehicle camera toassess alertness levels. Key parameters such as eye closure duration, blink frequency, and headmovements are extracted and analyzed in real time. Image processing algorithms and trained machinelearning models are employed to accurately detect fatigue-related patterns under varying lighting anddriving conditions. When drowsiness is detected beyond a predefined threshold, the system immediatelygenerates an audible or visual warning to alert the driver. Experimental results indicate that the systemachieves reliable detection accuracy with low processing latency. The proposed approach is non-intrusive, cost-effective, and suitable for real-time deployment in vehicles. This system can significantlyreduce fatigue-related accidents and improve overall road safety.
Keywords Driver Drowsiness Detection, Computer Vision, Machine Learning, Real-Time Systems, Fatigue Monitoring, Eye Blink Detection, Facial Landmark Analysis, Intelligent Transportation Systems, Driver Assistance Systems.
Published In Volume 7, Issue 3, May-June 2026
Published On 2026-05-28
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E-ISSN 3048-7641
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