Results based on traac accident analysis indicate that a leading cause for automobile accidents is due to a diminished vigilance on the part of the driver. Two major factors that may result in a reduction of a driver's alertness are drowsiness and intoxication. Developing eeective technologies for measuring drowsiness/intoxication is therefore imperative for reducing automobile accidents. The d...

Drowsiness and fatigue are serious problems in all transportation systems. One persistent issue is the lack of an agreed definition of these respective energetic states. Here we review the theoretical approaches (cognitive versus physiological) framing the driver fatigue problem. Known contributing factors to drowsiness include sleep debt, circadian rhythm, and shift work. However, we also sugg...

Automotive has gained several benefits from the Ambient Intelligent researches involving the deployment of sensors and hardware devices into an intelligent environment surrounding people, meeting users’ requirements and anticipating their needs. One of the main topics in automotive is to anticipate driver needs and safety, in terms of preventing critical and dangerous events. Considering the hi...

In this paper, a new Driver Assistance System (DAS) for automatic driver’s drowsiness detection based on visual information and image processing is presented. This algorithm works on several stages using Viola and Jones (VJ) object detector, expectation maximization algorithm, the Condensation algorithm and support vector machine to compute a drowsiness index. The goal of the system is to help ...

In studies concerning driver state, particularly attention loss and driver drowsiness, a phenomenon can be observed which we refer to as driving without awareness (DWA). The purpose of the study presented here is to learn more about the underlying characteristics of this symptom of driver drowsiness that occurs if the will to keep one’s eyes open overrides the physiolo gical need of a drowsy pe...

The majority of the accidents were happening perpetually due to driver drowsiness over decades. Automation has been playing key role in many fields provide conformity and improve quality life users. Though various detection systems have developed during last decade based on factors, still demanding an improvement terms efficiency, accuracy, cost, speed, availability, etc. In this paper, propose...

This paper describes the design and implementation of a driver drowsiness detection (DDD) system using modified RiscV processor on field-programmable gate array (FPGA). To detect drowsiness, Convolutional Neural Network (CNN) is implemented processor. The CNN trained to classify four primary driver’s expressions, including distraction, natural, sleep, yawn. accuracy 81.07% validation dat...

The driver felt sleepy when they don’t take proper rest while driving on long routes. restless careless mistake could be fatal to as well others’ lives. This issue has been increased such a level that system required avoid accidents and save life. alertness detection can play significant role hazards. identify the drowsiness face of generate an alarm for them stop or necessary actions. Eye stat...