Real Time Implementation of Driver Drowsiness Monitoring System Using SVM Classifier
نویسندگان
چکیده
منابع مشابه
A Real Time Driver Drowsiness Detection System
Driving with drowsiness is one of the main causes of traffic accidents. Driver fatigue is a significant factor in a large number of vehicle accidents. The development of technologies for detecting or preventing drowsiness at the wheel is a major challenge in the field of accident avoidance systems. Due to the hazard that drowsiness presents on the road, methods need to be developed for countera...
متن کاملReal Time Implementation for Monitoring Drowsiness Condition of a Train Driver using Brain Wave Sensor
Driver fatigue and lack of sleep of drivers especially those who drive for a longer period of time as train accidents are a longer standing problem. It has been observed that each year numerous train accidents and fatalities may occur around the world due to driver falling asleep while driving the train. There are various traditional methods that may facilitate to detect drowsiness state of the...
متن کاملReal-time Nonintrusive Detection of Driver Drowsiness
Driver drowsiness is one of the major causes of serious traffic accidents, which makes this an area of great socioeconomic concern. Continuous monitoring of drivers’ drowsiness thus is of great importance to reduce drowsiness-caused accidents. This proposed research developed a real-time, nonintrusive driver drowsiness detection system by building biosensors on the automobile steering wheel and...
متن کاملReal-Time Warning System for Driver Drowsiness Detection Using Visual Information
Traffic accidents due to human errors cause many deaths and injuries around the world. To help in reducing this fatality, in this research, a new module for Advanced Driver Assistance System (ADAS) for automatic driver drowsiness detection based on visual information and Artificial Intelligence is presented. The aim of this system is to locate, to track and to analyze the face and the eyes to c...
متن کاملDriver Drowsiness Detection System Using Image Processing
Drivers who do not take regular breaks when driving long distances run a high risk of becoming drowsy a state which they often fail to recognize early enough according to the experts. Studies show that around one quarter of all serious motorway accidents are attributable to sleepy drivers in need of a rest, meaning that drowsiness causes more road accidents than drink-driving. Attention assist ...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ژورنال
عنوان ژورنال: International Journal of Engineering and Manufacturing
سال: 2023
ISSN: ['2306-5982', '2305-3631']
DOI: https://doi.org/10.5815/ijem.2023.03.05