scholarly journals Driver Drowsiness Detection Based on Face Feature and Perclos

2021 ◽  
pp. 108-112
Author(s):  
S. Gopi ◽  
Dr. E. Punarselvam ◽  
K. Dhivya ◽  
K. Malathi ◽  
N. Sandhanaselvi
Keyword(s):  
Traffic Accidents ◽  
Road Accidents ◽  
Steering Angle ◽  
Severe Injuries ◽  
Drowsiness Detection ◽  
Risk Of Death ◽  
Driver Drowsiness ◽  
The Face ◽  
Contactless System ◽  
Left And Right

Driving vehicles are complex and require undivided attention to prevent road accidents. Fatigue and distraction are a major risk factor that causes traffic accidents, severe injuries, and a high risk of death. Some progress has been made for driver drowsiness detection using a contact-based method that utilizes vehicle parts (such as steering angle and pressure on the pedal) and physiological signals (electrocardiogram and electromyogram). However, a contactless system is more potential for real-world conditions. In this study, we propose a computer vision-based method to detect driver's drowsiness from a video taken by a camera. The method attempts to recognize the face and then detecting the eye in every frame. From the detected eye, iris regions for left and right eyes are used to calculate the PERCLOS measure (the percentage of total time that eye is closed). The proposed method was evaluated based on public YawDD video dataset. The results found that PERCLOS value when the driver is alert is lower than when the driver is drowsy.

scholarly journals TRAFFIC-RELATED MORTALITY IN MOLDOVA

2020 ◽  
pp. 140-147
Keyword(s):  
Life Expectancy ◽  
Traffic Accident ◽  
Traffic Accidents ◽  
Road Traffic ◽  
Road Accident ◽  
Road Accidents ◽  
Continuous Increase ◽  
Risk Of Death ◽  
Significant Difference ◽  
Related Mortality

This article analyses the mortality caused by road accidents in Moldova depending on the degree of involvement of pedestrians, cyclists, motorcyclists, drivers and passengers of transport units, depending on age and sex. Results suggest that traffic-related mortality in Moldova has shown an increased incidence among the young and working-age population, where a significant difference between males and females is observed. Among the youth, traffic-related deaths register between 10-27% of the overall mortality in both sexes. The risk exposure of dying in a traffic accident decreases with age and is less significant in the retired ages. During the years 1998-2015, avoidance of trafficrelated deaths would have assured an increase in life expectancy between 0.40-0.56 years in males, and 0.09-0.23 years in females. The continuous increase in the number of transport units on public roads, as well as in the number of hours spent in traffic, influences the degree of exposure to the risk of death or injury as a result of road traffic accidents. Trauma resulting from road accidents increases the incidence of premature mortality and disability among the population, which is reflected by the decrease of healthy life expectancy. It is ascertained that the road accident mortality requires a detailed and comprehensive analysis given the multitude of factors influencing deaths and injuries related to a traffic accident among the population. Thus, in order to improve road safety and reduce mortality incidence among traffic participants, a range of actions has to be implemented by the liable actors, including through the international experience.

scholarly journals Smart Real-Time Video Surveillance Platform for Drowsiness Detection Based on Eyelid Closure

2019 ◽  
Vol 2019 ◽  
pp. 1-9 ◽  
Author(s):  
Muhammad Tayab Khan ◽  
Hafeez Anwar ◽  
Farman Ullah ◽  
Ata Ur Rehman ◽  
Rehmat Ullah ◽  
...  
Keyword(s):  
Real Time ◽  
Video Surveillance ◽  
Classification Accuracy ◽  
Eyelid Closure ◽  
Drowsiness Detection ◽  
Driver Drowsiness ◽  
Sobel Operator ◽  
The Face ◽  
Uniform Background ◽  
The Subject

We propose drowsiness detection in real-time surveillance videos by determining if a person’s eyes are open or closed. As a first step, the face of the subject is detected in the image. In the detected face, the eyes are localized and filtered with an extended Sobel operator to detect the curvature of the eyelids. Once the curves are detected, concavity is used to tell whether the eyelids are closed or open. Consequently, a concave upward curve means the eyelid is closed whereas a concave downwards curve means the eye is open. The proposed method is also implemented on hardware in order to be used in real-time scenarios, such as driver drowsiness detection. The evaluation of the proposed method used three image datasets, where images in the first dataset have a uniform background. The proposed method achieved classification accuracy of up to 95% on this dataset. Another benchmark dataset used has significant variations based on face deformations. With this dataset, our method achieved classification accuracy of 70%. A real-time video dataset of people driving the car was also used, where the proposed method achieved 95% accuracy, thus showing its feasibility for use in real-time scenarios.

scholarly journals Driver Drowsiness Detection System using Machine Learning

2021 ◽  
Vol 9 (VI) ◽  
pp. 2270-2272
Author(s):  
Charan M
Keyword(s):  
Real Time ◽  
Web Application ◽  
Detection System ◽  
Smart Phone ◽  
Learning Approaches ◽  
Drowsiness Detection ◽  
Driver Drowsiness ◽  
The Face ◽  
Bounding Boxes ◽  
Traditional Image

We propose a Driver drowsiness detection system, the purposes of which are to prevent from dangerous cause and to avoid accidents. Since all the processes on image recognition performed on a smart phone, the system does not need to send images to a server and runs on an android smart phone in a real-time way. Automatic image-based recognition is a particularly challenging task. Traditional image analysis approaches have achieved low classification accuracy in the past, whereas deep learning approaches without human supervision real-time drowsiness detection. This model classifies whether the person’s eyes are opened or closed. To recognize the face, a user should have to adjust camera such a way that it covers his face first, and then the system starts recognition within the indicated bounding boxes. In addition, the system estimates the actions of the person. This recognition process is performed repeatedly about every second. We will implement this system as Web application effectively for real-time recognition.

scholarly journals Driver Drowsiness Detection and Alert System

2021 ◽  
pp. 583-588
Author(s):  
Swapnil Titare ◽  
Shubham Chinchghare ◽  
K. N. Hande
Keyword(s):  
Traffic Accidents ◽  
Learning Algorithm ◽  
Text Message ◽  
Secondary Data ◽  
Driving Safety ◽  
Drowsiness Detection ◽  
Detection Systems ◽  
Driver Drowsiness ◽  
Human Image ◽  
Day By Day

Nowadays, accidents occur during drowsy road trips and increase day by day; It is a known fact that many accidents occur due to driver fatigue and sometimes inattention, this research is primarily devoted to maximizing efforts to identify drowsiness. State of the driver under real driving conditions. The aim of driver drowsiness detection systems is to try to reduce these traffic accidents. The secondary data collected focuses on previous research on systems for detecting drowsiness and several methods have been used to detect drowsiness or inattentive driving.Our goal is to provide an interface where the program can automatically detect the driver's drowsiness and detect it in the event of an accident by using the image of a person captured by the webcam and examining how this information can be used to improve driving safety can be used. . a vehicle safety project that helps prevent accidents caused by the driver's sleep. Basically, you're collecting a human image from the webcam and exploring how that information could be used to improve driving safety. Collect images from the live webcam stream and apply machine learning algorithm to the image and recognize the drowsy driver or not.When the driver is sleepy, it plays the buzzer alarm and increases the buzzer sound. If the driver doesn't wake up, they'll send a text message and email to their family members about their situation. Hence, this utility goes beyond the problem of detecting drowsiness while driving. Eye extraction, face extraction with dlib.

scholarly journals Risks of road accidents in Irkutsk region

2020 ◽  
Vol 5 (4) ◽  
pp. 411-420
Author(s):  
Svetlana S. Timofeeva ◽  
◽  
Semen S. Timofeev ◽  
Aleksey А. Taskaev ◽  
◽  
...  
Keyword(s):  
Road Safety ◽  
Traffic Accidents ◽  
Statistical Data ◽  
Road Traffic ◽  
Road Traffic Accidents ◽  
Road Accidents ◽  
Accident Rate ◽  
Risk Of Death ◽  
Road Users ◽  
Irkutsk Region

The article deals with the issue of road safety. The aim is to analyze the accident rate on the roads of rkutsk region and assess the risk of road traffic accidents (RTA). The research is based on statistical data. A comparative analysis of the risks of road accidents and the risks of death of road users is carried out. The risk of death in accidents is higher in Slyudyanka district than in Irkutsk region, which is due to the complex route and mountainous areas. The damage caused by road traffic accidents is increasing every year.

scholarly journals Foreign and national experience in organizing tertiary medical care for injured in road accidents

2019 ◽  
Vol 100 (3) ◽  
pp. 464-468
Author(s):  
D A Bugayev
Keyword(s):  
Medical Care ◽  
Russian Federation ◽  
Traffic Accidents ◽  
Road Traffic ◽  
Trauma Centers ◽  
Road Traffic Accidents ◽  
Road Accidents ◽  
Severe Injuries ◽  
The Russian Federation ◽  
The Creation

As a result of road accidents in the Russian Federation, up to 30 thousand people are killed every year, which causes significant demographic and socio-economic damage to the state. The World Health Organization considers road traffic injuries as one of the global problems associated with 1.25 million deaths. In many countries, the leading direction of development of medical care for victims of road traffic accidents is the creation of trauma systems. The main volume of medical care for victims of road traffic accidents and those with severe injuries under other circumstances is provided by trauma centers of the 2nd and 1st levels. The implementation of the federal targeted programs «Improving road safety in 2006-2012» allowed the creation of a network of trauma centers in a number of subjects of the Russian Federation, whose work reduced mortality and disability among victims with severe injuries, but the problem cannot be considered solved because there are no national database of the victims of road accidents (register), system for assessing the severity of injuries and recording long-term results of non-fatal injuries, which excludes the possibility to compare the clinical effectiveness of the Russian trauma centers among themselves and with foreign counterparts.

scholarly journals DRIVER DROWSINESS DETECTION USING PYTHON

2021 ◽  
Vol 6 (4) ◽  
Author(s):  
Bhumika Rajput
Keyword(s):  
Eye Tracking ◽  
Correlation Coefficient ◽  
Facial Features ◽  
Drowsiness Detection ◽  
Driver Drowsiness ◽  
The Face

When the driver does not get proper sleep, rest or fell sleepy, they sleep while driving and it could be fatal to driver and even the passengers. This issue should have a solution in form of a system in which they can identify drowsiness on the face of a driver and then could ring an alarm so that driver can take necessary actions after that. The detection is done mainly in three steps, in beginning the system should identify the face and then facial features and then followed by eye tracking. In this we use correlation coefficient template. The extracted eye image and template is then matched so that the system can know if the driver is sleeping or not. The blinking is then recognized and if it fall within a certain range, the alarm will go off.

scholarly journals Real Time Driver Drowsiness Detection App using ML

2021 ◽  
pp. 526-530
Author(s):  
Vaibhav Mandavkar ◽  
Prasad Ligade ◽  
Shreyas Kulkarni ◽  
Chaitanya Mane ◽  
Prof. Varsha Rasal
Keyword(s):  
Machine Learning ◽  
High Speed ◽  
Threshold Value ◽  
Drinking And Driving ◽  
Road Accidents ◽  
Driver Drowsiness ◽  
Full Control ◽  
The Face ◽  
Main Factors ◽  
User Friendly

Every year road accidents are increasing rapidly as technological and mechanical advancements in vehicles permits drivers to drive at high speed. Approximately 1.35 million people die each year as a result of road accidents in India alone 151 thousand casualties were recorded last year. From this nearly 78% road accidents are caused due to driver's fault. Main factors for this accidents are drowsiness, drunk and drive and over speeding from which nearly 40% of the accidents caused due to drowsiness. People are conscious about the risk of drinking and driving but don’t realize the dangerous of drowsiness because no instruments exist to measure the driver drowsiness. If the Driver fails to concentrate on driving it reduces the driver reaction time and impairs steering behavior To solve this problem we are going to use the power of machine learning to identify if the driver is drowsy or not. Generally when someone feels drowsy his\hers eye blinking speed decreases by specifying threshold value we can detect if the driver is drowsy or not. This programme provides a mechanism for scanning facial landmarks and then using the essential landmarks for eye tracking after recognising the face. this insures that the driver is in full control of his vehicle. The system make use of device’s front camera to monitor drivers’s face to detect drowsiness and alarms the driver if system founds him drowsy. More functionality will be added to the system, such as issuing an SOS if something occurs to a car in a remote location. The software also has emergency numbers, so that in the event of an emergency, the driver may call the appropriate authorities as needed. This system may also be used for navigating by utilising the app's map functionality. Flutter will be utilised to provide a native and user-friendly system interface. As a result, the software will be available for both Android and iOS smartphones. The use of as little hardware as possible will ensure seamless processing. This technology may be employed in a variety of circumstances, including cab services, state transportation and on-road goods delivery.

A driver drowsiness and distraction warning system based on raspberry Pi 3 Kit

2019 ◽  
Vol 70 (3) ◽  
pp. 184-192
Author(s):  
Toan Dao Thanh ◽  
Vo Thien Linh
Keyword(s):  
Processing System ◽  
Warning System ◽  
Raspberry Pi ◽  
Data Set ◽  
Lower Lip ◽  
Driver Drowsiness ◽  
Image Sensing ◽  
The Face ◽  
The Common ◽  
University Laboratory

In this article, a system to detect driver drowsiness and distraction based on image sensing technique is created. With a camera used to observe the face of driver, the image processing system embedded in the Raspberry Pi 3 Kit will generate a warning sound when the driver shows drowsiness based on the eye-closed state or a yawn. To detect the closed eye state, we use the ratio of the distance between the eyelids and the ratio of the distance between the upper lip and the lower lip when yawning. A trained data set to extract 68 facial features and “frontal face detectors” in Dlib are utilized to determine the eyes and mouth positions needed to carry out identification. Experimental data from the tests of the system on Vietnamese volunteers in our University laboratory show that the system can detect at realtime the common driver states of “Normal”, “Close eyes”, “Yawn” or “Distraction”

Utilising Indigenous Knowledge or Crime against Humanity?: A Critical Engagement with the Debate Generated by Alick Macheso’s Use of Manhood to Treat Nhova (Sunken Fontanelle)

2019 ◽  
Vol 7 (1) ◽  
Author(s):  
Charles Tembo ◽  
Allan Maganga ◽  
Peterson Dewah
Keyword(s):  
Ethical Issues ◽  
General Tendency ◽  
Ethical Values ◽  
Ethical Considerations ◽  
Lower Back ◽  
African Ethics ◽  
Cultural Grounding ◽  
The Face ◽  
Left And Right ◽  
Points Of View

 This article presents various points of view regarding the treatment of sunken fontanelle by various communities as ignited by the controversial practice of kutara(a practice that involves the father of a child sliding his penis from the lower part of the left and right cheeks to the top of the head, as well as from the lower part of the face to the top of the head, and from the lower back part of the head to the top). The story of Alick Macheso’s use of his manhood to treat nhova (sunken fontanelle) opened a Pandora’s box. The story not only attracted the attention of critics from diverse cultural and ethical backgrounds, but revealed multi-ethnic positions. That is, reactions were steeped in a multiplicity of intellectual, religious and even cultural grounding. Reactions ranged from accusations of backwardness and absurdity, through to medical and Christian orientations toward the treatment of nhova. The overarching idea is that there is a general tendency to dismiss the age-old practice of kutara,coupled with an uncritical celebration of certain positions. The debate that ensued following publication of the story seemed to revolve around ethical considerations. The school of thought that dismisses kutara with disdain regards it as unethical and unimaginable in the present-day world—it is redolent with insinuations of absurdity on the part of those that live and celebrate it. We contend that the raging debate that followed the publication of the story can best be conceptualised within the context of African ethics. We note that kutara has relevance to the spirituality, ethical values, privacy, and protection of children’s rights, among other ethical issues. It is hoped that the article will stir further debate and encourage more research among information practitioners, scholars and researchers into the ethical issues surrounding the treatment of sunken fontanelle in various African communities. It argues for an Afrocentric conceptualisation of phenomena in order to contribute to debates on the renaissance of African cultures, and stresses that it is imperative to harness the life-furthering age-old traditions in African ontological existence.

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