V3I5P152

Driver Drowsiness Detection System

Tanmay Shrivastava^1*, Shailendra Singh Tomer², Dr Praveen Kumar Srivastava³

Abstract

Drowsiness of drivers is among the primary reasons behind road accidents that cause serious injuries, deaths, and financial losses around the world. Conventional monitoring tools are incapable of recognizing the indicators of fatigue in real-time; hence, there is a need to develop a more effective solution for road accident prevention. This paper provides a comprehensive overview of the Driver Drowsiness Detection System that utilizes computer vision and machine learning to ensure safe driving. The proposed system uses facial recognition to monitor eye blink rate, eye closure time, yawning frequency, and head movement. The data collected from the video is analysed using image processing and classification methods in order to estimate the driver’s alertness levels.

The Driver Drowsiness Detection System includes a camera-based video acquisition device, facial landmark detection algorithms, fatigue detection techniques, as well as alert notification mechanisms. In case the drowsiness indicators exceed certain pre-defined thresholds, an alert will be generated, which will include audio and visual notifications to inform the driver. The proposed solution is suitable for operation in different light environments and can be implemented using low-cost hardware. The experiment reveals that the system has good accuracy and low latency, which makes it fit for real-time implementation. The outcomes show that the fusion of artificial intelligence and computer vision has improved the safety of the drivers and decreased the likelihood of fatigue-related accidents. The design of the Driver Drowsiness Detection System offers a cost-efficient and intelligent way to ensure safety for future smart vehicles [3].

Keywords:

Driver Drowsiness Detection, Computer Vision, Machine Learning, Facial Landmark Detection, Eye Blink Detection, Fatigue Monitoring, Road Safety, Real-Time Alert System, Artificial Intelligence.