Driver Drowsiness Detection Using AI

Driver Drowsiness Detection Using AI

Author Name : Degala Sriram, Durge Sanjeev, Sai Prudvi Raj Yerrapragada, Adini Hemanjali, Bhargav Kumar Aathava, Masum Hossain

ABSTRACT

Drowsiness and fatigue are one of the main causes leading to road accidents. They can be prevented by taking effort to get enough sleep before driving, drink coffee or energy drink, or have a rest when the signs of drowsiness occur. The popular drowsiness detection method uses complex methods, such as EEG and ECG. This method has high accuracy for its measurement but it need to use contact measurement and it has many limitations on driver fatigue and drowsiness monitor. Thus, it is not comfortable to be used in real time driving. This paper proposes a way to detect the drowsiness signs among drivers by measuring the eye closing rate and yawning. This project describes on how to detect the eyes and mouth in a video recorded from the experiment conducted by AIROS (American Institute of Road Safety). In the video, a participant will drive the driving simulation system and a webcam will be place in front of the driving simulator. The video will be recorded using the webcam to see the transition from awake to fatigue and finally, drowsy. The designed system deals with detecting the face area of the image captured from the video. The purpose of using the face area so it can narrow down to detect eyes and mouth within the face area. Once the face is found, the eyes and mouth are found by creating the eye for left and right eye detection and also mouth detection. A computer vision based thoughts have been used for the creation of a Drowsy Driver Detection System. The little camera has been utilized by framework that concentrates straight towards the essence of driver and checks the driver's eyes with a particular ultimate objective to perceive weakness. A notice sign is issued to alert the driver, in such circumstance when exhaustion is perceived. The framework oversees using information picked up for the picture to find the facial tourist spots, which gets the area where the eyes of an individual may exist. On the off chance that the eyes of driver are discovered close for a specific measure of casings, the proposed framework accept that the driver is falling asleep and an alarm of caution has been issued. The structure can work just when the eye are found, and works in encompassing lighting conditions too.