This paper presents a non-intrusive approach for monitoring driver drowsiness using the fusion of several optimized indicators based on driver physical and driving performance measures, obtained from ADAS (Advanced Driver Assistant Systems) in simulated conditions. The paper is focused on real-time drowsiness detection technology rather than on long-term sleep/awake regulation prediction techno...

Fatigue driving is an invisible killer in car accidents and one of the main causes traffic accidents. In order to reduce caused by fatigue, this research has developed a safety assist device prevent such research, non-contact driver drowsiness detection alert system established vehicle cabin. The real-time facial image obtained through camera installed front driver, then input NVIDIA Jetson TX2...

There are a variety of potential uses for the classification eye conditions, including tiredness detection, psychological condition evaluation, etc. Because its significance, many studies utilizing typical neural network algorithms have already been published in literature, with good results. Convolutional networks (CNNs) employed real-time applications to achieve two goals: high accuracy and s...

The recent technology in digital computing created many ways of drowsiness detection. This is important because of the increased numbers of accidents caused by drowsy drivers. In this paper, an approach for detecting drowsiness state by continuously analyzing EEG signals is proposed. Using a single dry-sensor EEG headset, a real-time system that monitors and analyzes the EEG signal of the drive...

Driver drowsiness is a serious issue that poses significant threat to road safety, as it can lead accidents and injuries. In response this problem, thorough review of machine learning techniques for detecting driver was conducted. The examined range techniques, including more recent approaches use deep algorithms well different types data sources behaviours, physiological signals, vehicle behav...

This paper presents the method of detecting driver’s drowsiness level from the facial expression. The motivation for this research is to realize the novel safety system which can detect the driver’s slight drowsiness and keep the driver awake while driving. The brain wave is commonly used as the drowsiness index. However, it is not suitable for the in-vehicle system since it is measured with se...

BACKGROUND Major injuries and death in accidents have roots in drowsiness. Sleepiness is a main result of insufficient sleep. It is vital to explore drowsiness and its level. There are various sorts of methods in the forms of subjective and objective approaches. The goal of this study was to detect the association of subjective and interpretive drowsiness with facial dynamic changes. METHODS ...