Driver Fatigue And Alcohol Detection, Alert And Notification System Using Image Processing And Machine Learning

Abstract

Experts say that drivers who do not take regular rests when traveling long distances face a greater danger of feeling sleepy, a condition they frequently fail to identify in time. This behaviour significantly contributes to an increase in deaths and injuries globally. Additionally, many accidents result from cases of drunk driving, where drivers lose consciousness due to alcohol consumption, leading to fatal accidents. In this research, we offer a system that is intended to determine whether the driver is affected by alcohol. If the system detects alcohol consumption, it promptly sends a notification to the registered mobile number. Furthermore, the system utilises a webcam to collect real-time data, enabling it to detect whether the driver is drowsy or not. In the event of drowsiness, the system alerts the driver and sends a notification to the registered mobile number, thereby reducing the possibilities of accidents and enhancing road safety. This system sends notifications via the internet thus decreasing the hardware of the system. Here two features, Alcohol detection and Drowsiness detection are integrated in one single system design.

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