Fatigue is an annoying phenomenon that can affect people’s concentration on learning or working. It will
reduce the learning efficiency of people and even cause danger in working. For example, fatigue driving
results in car accident have been reporting from the daily news. In order to avoid the accidents mentioned
above, this research design the mobile system to detect fatigue to alert people by way of the lightweight
brainwave detector, and the smartphone that everyone owns nowadays. In this system, light weight head
mounted brainwave device is adopted and the signal are transmitted to the smartphone for further
processing. Our algorithm calculates the fatigue index by focus, eyes blink frequency, δ-wave, α-wave, βwave, and θ-wave captured from the brainwave to determine human’s spiritual condition. When the
experimental results were carried out to the car drivers, the system can remind drivers when they were
tired and drowsy while driving. This system can notify people to aware his own spiritual state so as to
raise working efficacy and avoid the occurrences of accident caused by fatigue. In addition, the whole
system without complex instrument and expensive cost.
IJRET : International Journal of Research in Engineering and Technology is an international peer reviewed, online journal published by eSAT Publishing House for the enhancement of research in various disciplines of Engineering and Technology. The aim and scope of the journal is to provide an academic medium and an important reference for the advancement and dissemination of research results that support high-level learning, teaching and research in the fields of Engineering and Technology. We bring together Scientists, Academician, Field Engineers, Scholars and Students of related fields of Engineering and Technology
International Journal of Engineering Research and Applications (IJERA) is an open access online peer reviewed international journal that publishes research and review articles in the fields of Computer Science, Neural Networks, Electrical Engineering, Software Engineering, Information Technology, Mechanical Engineering, Chemical Engineering, Plastic Engineering, Food Technology, Textile Engineering, Nano Technology & science, Power Electronics, Electronics & Communication Engineering, Computational mathematics, Image processing, Civil Engineering, Structural Engineering, Environmental Engineering, VLSI Testing & Low Power VLSI Design etc.
Abstract: The aim of this project is to design an Accident Prevention System whichhelps in preventing/avoiding accidents. Accident due to cause of drowsy is preventedand controlled when the vehicle is out of control. The accidents due to thedrowsy state of the driver is prevented using automatic breaking system by using eye blink sensor. The term used here for the realization that the driveris drowsy is by using eye blink sensor of the driver. In recent times drowsiness is oneof the major problem of highway accidents. These types of accidents occurredcaused by drowsy and driver cant able to control the vehicle, when the driver wakes. The drowsiness is indented by the eye blink closure and blinking frequency through infrared sensor worn by driver by means of spectacles frame or IRS. If thedriver is drowsy, then the system will give buzzer and the speed of thevehicle is reduced in 3 to 5 sec.
Yawning analysis for driver drowsiness detectioneSAT Journals
Abstract Driver fatigue is the main reason for fatal road accidents around the world. In this paper, an efficient driver’s drowsiness detection system is designed using yawning detection.Here, we consider eye detection and mouth detection. So that road accidents can avoid successfully. Mouth features points are identified using the redness property. Firstly detecting the driver’s face using YCbCr method then face tracking will perform using canny edge detector. After that , eyes and mouth positions by using Haar features. Lastly yawning detection is perform by using mouth geometric features. This method is tested on images from videos. Also proposed system should then alert to the driver in case of inattention. Keywords: Face detection, Face tracking, Eye and Mouth detection, Yawn detection
Driver Fatigue Monitoring System Using Eye ClosureIJMER
Abstract: Now-a-days so many road accidents occur due to driver distraction while he is driving. Those accidents are broadly depends upon wide range of driver state such as drowsy state, alcoholic state, depressed state etc. Even driver distraction and conversation with passengers during driving can lead in major problems. To address the problem we propose a Driver fatigue Monitoring and
warning system based on eye-tracking, which is consider as active safety system. This system is useful and helpful for drivers to be alert while driving. Eye tracking is one of the major technologies for future driver system since human eyes contains much information. Sleepiness reduces reaction time of safe driving. The driver distraction is measured by the person eye closure rate for certain period while driving. It is implemented by comparing the image extracted from video and the video that is currently
performing. The percentage of eyes is compared from both the frames, if the driver is suspected to be sleeping then a warning alarm is given to alert the driver
IJRET : International Journal of Research in Engineering and Technology is an international peer reviewed, online journal published by eSAT Publishing House for the enhancement of research in various disciplines of Engineering and Technology. The aim and scope of the journal is to provide an academic medium and an important reference for the advancement and dissemination of research results that support high-level learning, teaching and research in the fields of Engineering and Technology. We bring together Scientists, Academician, Field Engineers, Scholars and Students of related fields of Engineering and Technology
International Journal of Engineering Research and Applications (IJERA) is an open access online peer reviewed international journal that publishes research and review articles in the fields of Computer Science, Neural Networks, Electrical Engineering, Software Engineering, Information Technology, Mechanical Engineering, Chemical Engineering, Plastic Engineering, Food Technology, Textile Engineering, Nano Technology & science, Power Electronics, Electronics & Communication Engineering, Computational mathematics, Image processing, Civil Engineering, Structural Engineering, Environmental Engineering, VLSI Testing & Low Power VLSI Design etc.
Abstract: The aim of this project is to design an Accident Prevention System whichhelps in preventing/avoiding accidents. Accident due to cause of drowsy is preventedand controlled when the vehicle is out of control. The accidents due to thedrowsy state of the driver is prevented using automatic breaking system by using eye blink sensor. The term used here for the realization that the driveris drowsy is by using eye blink sensor of the driver. In recent times drowsiness is oneof the major problem of highway accidents. These types of accidents occurredcaused by drowsy and driver cant able to control the vehicle, when the driver wakes. The drowsiness is indented by the eye blink closure and blinking frequency through infrared sensor worn by driver by means of spectacles frame or IRS. If thedriver is drowsy, then the system will give buzzer and the speed of thevehicle is reduced in 3 to 5 sec.
Yawning analysis for driver drowsiness detectioneSAT Journals
Abstract Driver fatigue is the main reason for fatal road accidents around the world. In this paper, an efficient driver’s drowsiness detection system is designed using yawning detection.Here, we consider eye detection and mouth detection. So that road accidents can avoid successfully. Mouth features points are identified using the redness property. Firstly detecting the driver’s face using YCbCr method then face tracking will perform using canny edge detector. After that , eyes and mouth positions by using Haar features. Lastly yawning detection is perform by using mouth geometric features. This method is tested on images from videos. Also proposed system should then alert to the driver in case of inattention. Keywords: Face detection, Face tracking, Eye and Mouth detection, Yawn detection
Driver Fatigue Monitoring System Using Eye ClosureIJMER
Abstract: Now-a-days so many road accidents occur due to driver distraction while he is driving. Those accidents are broadly depends upon wide range of driver state such as drowsy state, alcoholic state, depressed state etc. Even driver distraction and conversation with passengers during driving can lead in major problems. To address the problem we propose a Driver fatigue Monitoring and
warning system based on eye-tracking, which is consider as active safety system. This system is useful and helpful for drivers to be alert while driving. Eye tracking is one of the major technologies for future driver system since human eyes contains much information. Sleepiness reduces reaction time of safe driving. The driver distraction is measured by the person eye closure rate for certain period while driving. It is implemented by comparing the image extracted from video and the video that is currently
performing. The percentage of eyes is compared from both the frames, if the driver is suspected to be sleeping then a warning alarm is given to alert the driver
The Real Time Drowisness Detection Using Arm 9IOSR Journals
Abstract: The project is to monitor the driver’s eye movement by using webcam and EOG channel respectively. Embedded project is to design and develop a low cost feature which is based on embedded platform for finding the driver drowsiness. Specifically, our Embedded System includes a webcam placed on the steering column which is capable to capture the eye movements and EOG placed at the forehead of the Driver to find out the visual activity. If the driver is not paying attention on the road ahead and a dangerous situation is detected, the system will warn the driver by giving the warning sounds. Embedded System uses ARM9 32-bit micro controller has a feature of image processing technique as well as Analog to Digital Conversion. Image processing is any form of signal processing for which the input is an image, such as a photograph or video frame; the output of image processing may be either an image or a set of characteristics or parameters related to the image. Keywords:ARM 9, EOGSensor, Webcam, GSM Modem.
Real time detection system of driver distraction.pdfReena_Jadhav
There is accumulating evidence that driver distrac- tion is a leading cause of vehicle crashes and incidents. In par- ticular, increased use of so-called in-vehicle information systems (IVIS) have raised important and growing safety concerns. Thus, detecting the driver’s state is of paramount importance, to adapt IVIS, therefore avoiding or mitigating their possible negative effects. The purpose of this presentation is to show a method for the nonintrusive and real- time detection of visual distraction, using vehicle dynamics data and without using the eye-tracker data as inputs to classifiers. Specifically, we present and compare different models that are based on well-known machine learning (ML) methods. Data for training the models were collected using a static driving simulator, with real human subjects performing a specific secondary task [i.e., a surrogate visual research task (SURT)] while driving. Different training methods, model characteristics, and feature selection criteria have been compared. Based on our results, using a BSN has outperformed all the other ML methods, providing the highest classification rate for most of the subjects.
Index Terms—Accident prevention, artificial intelligence and machine learning (ML), driver distraction and inattention, intel- ligent supporting systems.
This project represents a way of developing an
interface to detect driver drowsiness based on continuously
monitoring eyes and DIP algorithms. Micro sleeps that are short
period of sleeps lasting 2 to 3 seconds are good indicator of
fatigue state. Thus by continuously monitoring the eyes of the
driver by using camera one can detect the sleepy state of driver
and timely warning is issued.
Aim of the project is to develop the hardware which is very
advanced product related to driver safety on the roads using
controller and image processing. This product detects driver
drowsiness and gives warning in form of alarm and as well as
decreases the speed of vehicle.Along with the drowsiness
detection process there is continuous monitoring of the distance
done by the Ultrasonic sensor. The ultrasonic sensor detects the
obstacle and accordingly warns the driver as well as decreases
speed of vehicle.
Driving without license is the major cause for the road accident and the equivalent monetary losses. This paper is based on virtual reality based driving system which would enhance road safety and vehicle security. This paper helps to limit the vehicle operation on the basics of two parameters-Learn the driving by our own, category (car or bike) of the vehicle for which the driving license is issued. The hardware and software system required to improve our safety and security is developed. This driving system is apt for getting the license without bribe by gathering eye-gaze, Electroencephalography and peripheral physiological data.
Real Time Detection System of Driver FatigueIJCERT
The leading cause of vehicle crashes and accidents is the driver distraction. With the rapid development of motorization, driver fatigue has become a very serious traffic problem. Reasons for traffic accidents are driving after alcohol consumption, driving at night, driving without taking rest, aging, sleepiness, and fatigue occurred due to continuous driving, long working hours and night shifts. So to reduce rate of accidents due to above reasons, is aim of this project. This paper presents a method for detection of early signs of fatigue using feature extraction, Haar classifier and delivering of information and whereabouts of the driver to the emergency contact numbers.
Intelligent fatigue detection and automatic vehicle control systemijcsit
This paper describes method for detecting the early signs of fatigue in train drivers. As soon as the train
driver is falling in symptoms of fatigue immediate message will be transfer to the control room indicating the
status of the drivers. In addition of the advance technology of heart rate sensors is also added in the system
for correct detection of status of driver if in either case driver is falling to fatigue due to any sever medical
problems .The fatigue is detected in the system by the image processing method of comparing the
image(frames) in the video and by using the human features we are able to estimate the indirect way of
detecting fatigue. The technique also focuses on modes of person when driving the train i.e. awake, drowsy
state or sleepy and sleep state. The system is very efficient to detect the fatigue and control the train also
train can be controlled if it cross any such signal by which the train may collide on another train.
E YE S CRUTINIZED W HEEL C HAIR FOR P EOPLE A FFECTED W ITH T ETRAPLEGIAijcsit
Nowadays the requirement for developing a wheel cha
ir control which is useful for the physically disab
led
person with Tetraplegia. This system involves the c
ontrol of the wheel chair with the eye moment of th
e
affected person. Statistics suggest that there are
230,000 cases of Tetraplegia in India. Our system h
ere is
to develop a wheelchair which make the lives of the
se people easier and instigate confidence to live i
n
them. We know that a person who is affected by Tetr
aplegia can move their eyes alone to a certain exte
nt
which paves the idea for the development of our sys
tem. Here we have proposed the method for a device
where a patient placed on the wheel chair looking
in a straight line at the camera which is permanent
ly
fixed in the optics, is capable to move in a track
by gazing in that way. When we change the directio
n, the
camera signals are given using the mat lab script t
o the microcontroller. Depends on the path of the e
ye,
the microcontroller controls the wheel chair in all
direction and stops the movement. If there is any
obstacle to be found before the wheel chair the sen
sor mind that and it stop and move in right directi
on
immediately. The benefit of this system is too easi
ly travel anywhere in any direction which is handle
d by
physically disabled person with Tetraplegia
Development of A Smart Interface For Safety and Protection of AutomotivesCSCJournals
This paper is mainly directed towards the safety and protection of the human beings by synchronizing both the software and hardware modules. Automotive safety sensors are mainly streamed towards the application in automobiles. The safety and protection of the automobile driver is monitored and abnormalities are detected by these sensors. These abnormalities are highlighted and alerts are provided to the driver, by the combinational synchronization of hardware and software.
Image processing based eye detection methods a theoretical reviewjournalBEEI
Lately, many of the road accidents have been attributed to the driver stupor. Statistics revealed that about 32% of the drivers who met with such accidents demonstrated the symptoms of tiredness before the mishap though at varying levels. The purpose of this research paper is to revisit the various interventions that have been devised to provide for assistance to the vehicle users to avert unwarranted contingencies on the roads. The paper tries to make a sincere attempt to encapsulate the body of work that has been initiated so far in this direction. As is evident, there are numerous ways in which one can identify the fatigue of the driver, namely biotic or physiological gauges, vehicle type and more importantly the analysis of the face in terms of its alignment and other attributes.
Driver Alertness On Android With Face And Eye Ball MovementsIJRES Journal
Drowsiness is a big problem while in driving specially in long and continues driving. This is a main cause for accidents. Maximum accidents found by the driver’s ignorance of seeing the road and focus on other thing that will divert the concentration. This project used to find sleepy drivers and lazy driver by monitoring them periodically. Main objective of the project to develop entire system in to smart phone and make it as user friendly to the driver and try to support the system on Smartphone have the Android Operating System. There are major things are considered for measure the fatigue level when monitoring driver, Eye movement driver. Smartphone camera capture the drives image, A Dynamic decision making used for find the drivers fatigue level. When driver reaches threshold level of fatigue, then alert is triggered to avoid accident and awake the driver. If driver ignores the alert and continue with drowsy driving, the alert system takes further steps to stop the vehicle. It may be find nearest coffee shop to refresh driver and also if he need other choices to refresh the map will help them.GPS and Navigation Service of the Android phones used for assist the driver to overcome his drowsy driver.
The Real Time Drowisness Detection Using Arm 9IOSR Journals
Abstract: The project is to monitor the driver’s eye movement by using webcam and EOG channel respectively. Embedded project is to design and develop a low cost feature which is based on embedded platform for finding the driver drowsiness. Specifically, our Embedded System includes a webcam placed on the steering column which is capable to capture the eye movements and EOG placed at the forehead of the Driver to find out the visual activity. If the driver is not paying attention on the road ahead and a dangerous situation is detected, the system will warn the driver by giving the warning sounds. Embedded System uses ARM9 32-bit micro controller has a feature of image processing technique as well as Analog to Digital Conversion. Image processing is any form of signal processing for which the input is an image, such as a photograph or video frame; the output of image processing may be either an image or a set of characteristics or parameters related to the image. Keywords:ARM 9, EOGSensor, Webcam, GSM Modem.
Real time detection system of driver distraction.pdfReena_Jadhav
There is accumulating evidence that driver distrac- tion is a leading cause of vehicle crashes and incidents. In par- ticular, increased use of so-called in-vehicle information systems (IVIS) have raised important and growing safety concerns. Thus, detecting the driver’s state is of paramount importance, to adapt IVIS, therefore avoiding or mitigating their possible negative effects. The purpose of this presentation is to show a method for the nonintrusive and real- time detection of visual distraction, using vehicle dynamics data and without using the eye-tracker data as inputs to classifiers. Specifically, we present and compare different models that are based on well-known machine learning (ML) methods. Data for training the models were collected using a static driving simulator, with real human subjects performing a specific secondary task [i.e., a surrogate visual research task (SURT)] while driving. Different training methods, model characteristics, and feature selection criteria have been compared. Based on our results, using a BSN has outperformed all the other ML methods, providing the highest classification rate for most of the subjects.
Index Terms—Accident prevention, artificial intelligence and machine learning (ML), driver distraction and inattention, intel- ligent supporting systems.
This project represents a way of developing an
interface to detect driver drowsiness based on continuously
monitoring eyes and DIP algorithms. Micro sleeps that are short
period of sleeps lasting 2 to 3 seconds are good indicator of
fatigue state. Thus by continuously monitoring the eyes of the
driver by using camera one can detect the sleepy state of driver
and timely warning is issued.
Aim of the project is to develop the hardware which is very
advanced product related to driver safety on the roads using
controller and image processing. This product detects driver
drowsiness and gives warning in form of alarm and as well as
decreases the speed of vehicle.Along with the drowsiness
detection process there is continuous monitoring of the distance
done by the Ultrasonic sensor. The ultrasonic sensor detects the
obstacle and accordingly warns the driver as well as decreases
speed of vehicle.
Driving without license is the major cause for the road accident and the equivalent monetary losses. This paper is based on virtual reality based driving system which would enhance road safety and vehicle security. This paper helps to limit the vehicle operation on the basics of two parameters-Learn the driving by our own, category (car or bike) of the vehicle for which the driving license is issued. The hardware and software system required to improve our safety and security is developed. This driving system is apt for getting the license without bribe by gathering eye-gaze, Electroencephalography and peripheral physiological data.
Real Time Detection System of Driver FatigueIJCERT
The leading cause of vehicle crashes and accidents is the driver distraction. With the rapid development of motorization, driver fatigue has become a very serious traffic problem. Reasons for traffic accidents are driving after alcohol consumption, driving at night, driving without taking rest, aging, sleepiness, and fatigue occurred due to continuous driving, long working hours and night shifts. So to reduce rate of accidents due to above reasons, is aim of this project. This paper presents a method for detection of early signs of fatigue using feature extraction, Haar classifier and delivering of information and whereabouts of the driver to the emergency contact numbers.
Intelligent fatigue detection and automatic vehicle control systemijcsit
This paper describes method for detecting the early signs of fatigue in train drivers. As soon as the train
driver is falling in symptoms of fatigue immediate message will be transfer to the control room indicating the
status of the drivers. In addition of the advance technology of heart rate sensors is also added in the system
for correct detection of status of driver if in either case driver is falling to fatigue due to any sever medical
problems .The fatigue is detected in the system by the image processing method of comparing the
image(frames) in the video and by using the human features we are able to estimate the indirect way of
detecting fatigue. The technique also focuses on modes of person when driving the train i.e. awake, drowsy
state or sleepy and sleep state. The system is very efficient to detect the fatigue and control the train also
train can be controlled if it cross any such signal by which the train may collide on another train.
E YE S CRUTINIZED W HEEL C HAIR FOR P EOPLE A FFECTED W ITH T ETRAPLEGIAijcsit
Nowadays the requirement for developing a wheel cha
ir control which is useful for the physically disab
led
person with Tetraplegia. This system involves the c
ontrol of the wheel chair with the eye moment of th
e
affected person. Statistics suggest that there are
230,000 cases of Tetraplegia in India. Our system h
ere is
to develop a wheelchair which make the lives of the
se people easier and instigate confidence to live i
n
them. We know that a person who is affected by Tetr
aplegia can move their eyes alone to a certain exte
nt
which paves the idea for the development of our sys
tem. Here we have proposed the method for a device
where a patient placed on the wheel chair looking
in a straight line at the camera which is permanent
ly
fixed in the optics, is capable to move in a track
by gazing in that way. When we change the directio
n, the
camera signals are given using the mat lab script t
o the microcontroller. Depends on the path of the e
ye,
the microcontroller controls the wheel chair in all
direction and stops the movement. If there is any
obstacle to be found before the wheel chair the sen
sor mind that and it stop and move in right directi
on
immediately. The benefit of this system is too easi
ly travel anywhere in any direction which is handle
d by
physically disabled person with Tetraplegia
Development of A Smart Interface For Safety and Protection of AutomotivesCSCJournals
This paper is mainly directed towards the safety and protection of the human beings by synchronizing both the software and hardware modules. Automotive safety sensors are mainly streamed towards the application in automobiles. The safety and protection of the automobile driver is monitored and abnormalities are detected by these sensors. These abnormalities are highlighted and alerts are provided to the driver, by the combinational synchronization of hardware and software.
Image processing based eye detection methods a theoretical reviewjournalBEEI
Lately, many of the road accidents have been attributed to the driver stupor. Statistics revealed that about 32% of the drivers who met with such accidents demonstrated the symptoms of tiredness before the mishap though at varying levels. The purpose of this research paper is to revisit the various interventions that have been devised to provide for assistance to the vehicle users to avert unwarranted contingencies on the roads. The paper tries to make a sincere attempt to encapsulate the body of work that has been initiated so far in this direction. As is evident, there are numerous ways in which one can identify the fatigue of the driver, namely biotic or physiological gauges, vehicle type and more importantly the analysis of the face in terms of its alignment and other attributes.
Driver Alertness On Android With Face And Eye Ball MovementsIJRES Journal
Drowsiness is a big problem while in driving specially in long and continues driving. This is a main cause for accidents. Maximum accidents found by the driver’s ignorance of seeing the road and focus on other thing that will divert the concentration. This project used to find sleepy drivers and lazy driver by monitoring them periodically. Main objective of the project to develop entire system in to smart phone and make it as user friendly to the driver and try to support the system on Smartphone have the Android Operating System. There are major things are considered for measure the fatigue level when monitoring driver, Eye movement driver. Smartphone camera capture the drives image, A Dynamic decision making used for find the drivers fatigue level. When driver reaches threshold level of fatigue, then alert is triggered to avoid accident and awake the driver. If driver ignores the alert and continue with drowsy driving, the alert system takes further steps to stop the vehicle. It may be find nearest coffee shop to refresh driver and also if he need other choices to refresh the map will help them.GPS and Navigation Service of the Android phones used for assist the driver to overcome his drowsy driver.
IJRET : International Journal of Research in Engineering and Technology is an international peer reviewed, online journal published by eSAT Publishing House for the enhancement of research in various disciplines of Engineering and Technology. The aim and scope of the journal is to provide an academic medium and an important reference for the advancement and dissemination of research results that support high-level learning, teaching and research in the fields of Engineering and Technology. We bring together Scientists, Academician, Field Engineers, Scholars and Students of related fields of Engineering and Technology.
Driver-centered pervasive application for heart rate measurementIJECEIAES
People spend a significant amount of time daily in the driving seat and some health complexity is possible to happen like heart-related problems, and stroke. Driver’s health conditions may also be attributed to fatigue, drowsiness, or stress levels when driving on the road. Drivers’ health is important to make sure that they are vigilant when they are driving on the road. A driver-centered pervasive application is proposed to monitor a driver’s heart rate while driving. The input will be acquired from the interaction between the driver and embedded sensors at the steering wheel, which is tied to a Bluetooth link with an Android smartphone. The driver can view his historical data easily in tabular or graph form with selected filters using the application since the sensor data are transferred to a real-time database for storage and analysis. The application is coupled with the tool to demonstrate an opportunity as an aftermarket service for vehicles that are not equipped with this technology.
Vigilance of an operator is compromised in performing many monotonous activities like workshop and manufacturing floor tasks, driving, night shift workers, flying, and in general any activity which requires keen attention of an individual over prolonged periods of time. Driver or operator fatigue in these situations leads to drowsiness and lowered vigilance which is one of the largest contributors to injuries and fatalities amongst road accidents or workshop floor accidents. Having a vigilance monitoring system to detect drop in vigilance in these situations becomes very important.
REAL TIME VIGILANCE DETECTION USING FRONTAL EEGijcsit
Vigilance of an operator is compromised in performing many monotonous activities like workshop and manufacturing floor tasks, driving, night shift workers, flying, and in general any activity which requires keen attention of an individual over prolonged periods of time. Driver or operator fatigue in these situations leads to drowsiness and lowered vigilance which is one of the largest contributors to injuries and fatalities amongst road accidents or workshop floor accidents. Having a vigilance monitoring system to detect drop in vigilance in these situations becomes very important.
Real Time Eye Blinking and Yawning Detectionijtsrd
Detecting eye blink and yawning is important, for example in systems that monitor the vigilance of the human operator, eg Driver's drowsiness. Driver fatigue is one of the leading causes of the worlds deadliest road accidents. This shows that in the transport sector in particular, where a driver of heavy vehicles is often open to hours of monotonous driving which causes fatigue without frequent rest periods. It is therefore essential to design a road accident prevention system that can detect the drivers drowsiness, determine the drivers level of carelessness and warn when an imminent danger occurs. In this article, we propose a real time system that uses eye detection techniques, blinking and yawning. The system is designed as a non intrusive real time monitoring system. The priority is to improve driver safety without being intrusive. In this work, the blink of an eye and the drivers yawn are detected. If the drivers eyes remain closed for more than a certain time and the drivers mouth is open to yawning, the driver is said to be fatigue. Ohnmar Win "Real Time Eye Blinking and Yawning Detection" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Volume-3 | Issue-5 , August 2019, URL: https://www.ijtsrd.com/papers/ijtsrd28004.pdfPaper URL: https://www.ijtsrd.com/engineering/electrical-engineering/28004/real-time-eye-blinking-and-yawning-detection/ohnmar-win
International Journal of Engineering Research and Applications (IJERA) is an open access online peer reviewed international journal that publishes research and review articles in the fields of Computer Science, Neural Networks, Electrical Engineering, Software Engineering, Information Technology, Mechanical Engineering, Chemical Engineering, Plastic Engineering, Food Technology, Textile Engineering, Nano Technology & science, Power Electronics, Electronics & Communication Engineering, Computational mathematics, Image processing, Civil Engineering, Structural Engineering, Environmental Engineering, VLSI Testing & Low Power VLSI Design etc.
Towards a system for real-time prevention of drowsiness-related accidentsIAESIJAI
Traffic accidents always result in great human and material losses. One of the main causes of accidents is the human factor, which usually results from driver’s fatigue or drowsiness. To address this issue, several methods for predicting the driver’s state and behavior have been proposed. Some approaches are based on the measurement of the driver’s behavior such as: head movement, blinking time, mouth expression note, while others are based on physiological measurements to obtain information about the internal state of the driver. Several works used machine learning / deep learning to train models for driver behavior prediction. In this paper, we propose a new deep learning architecture based on residual and feature pyramid networks (FPN) for driver drowsiness detection. The trained model is integrated into a system that aims to prevent drowsinessrelated accidents in real-time. The system can detect drivers’ drowsiness in real time and alert the driver in case of danger. Experiment results on benchmarking datasets shows that our proposed architecture achieves high detection accuracy compared to baseline approaches.
Effective driver distraction warning system incorporating fast image recognit...IJECEIAES
Modern cars are equipped with advanced automatic technology featuring various safety measures for car occupants. However, the growing density of vehicles, especially in areas where infrastructure development lags, poses potential dangers, particularly accidents caused by driver subjectivity. These incidents may occur due to driver distraction or the presence of high-risk obstacles on the road. This article presents a comprehensive solution to assist drivers in mitigating these risks. Firstly, the study introduces a novel method to enhance the recognition of a driver's facial features by analyzing benchmarks and the whites of the eyes to assess the distraction level. Secondly, a domain division method is proposed to identify obstacles and lanes in front of the vehicle, enabling the assessment of the danger level. This information is promptly relayed to the driver and relevant individuals, such as the driver's manager or supervisor. An experimental device has also been developed to evaluate the effectiveness of the algorithms, solutions, and processing capabilities of the system.
Real-Time Fatigue Analysis of Driver through Iris RecognitionIJECEIAES
In recent days, the driver’s fault accounted for about 77.5% of the total road accidents that are happening every day. There are several methods for the driver’s fatigue detection. These are based on the movement of the eye ball using eye blinking sensor, heart beat measurement using Electro Cardio Gram, mental status analysis using ElectroEncephaloGram, muscle cramping detection, etc. However the above said methods are more complicated and create inconvenience for the driver to drive the vehicle. Also, these methods are less accurate. In this work, an accurate method is adopted to detect the driver’s fatigue based on status of the eyes using Iris recognition and the results shows that the proposed method is more accurate (about 80%) compared to the existing methods such as Eye blink Sensor method.
Mental State Monitoring System for the Professional Drivers Based on Heart Ra...Reno Filla
The consequences of tiredness, drowsiness, stress and lack of concentration caused by a variety of different factors such as illness, sleep depletion, drugs and alcohol is a serious problem in traffic and when operating industrial equipment. This is especially important for professional drivers since both expensive equipment and lives may be at stake, e.g. in mining, construction and personal transportation, reduced concentration, stress or tiredness are known to be the cause of many accidents. A system which recognizes the state of the driver and e.g. suggests breaks when stress level is too high or driver is too tired would enable large savings and reduces accident. Today different sensors enable clinician to determine a driver’s status with high accuracy. The aim of the paper is to develop an intelligent system that can monitor drivers’ stress depending on psychological and behavioral conditions/status using heart rate variability. An experienced clinician is able to diagnose a person’s stress level based on sensor readings. Here, we propose a solution using case-based reasoning to diagnose individual driver’s stress. During calibration a number of individual parameters are established. The system also considers the feedback from the driver’s on how well the test was performed The validation of the approach is based on close collaboration with experts and measurements from 18 driver’s from Volvo Construction Equipment are used as reference.
http://www.mrtc.mdh.se/index.php?choice=publications&id=3046
When driving long distances, drivers who do not take frequent rests are more likely to get sleepy, a condition that experts say they often fail to identify early enough. Based on eye condition, this research proposes a system for detecting driver sleepiness in real time. A camera is often used to take a sequence of images by the system. In our system, these capture images may be saved as individual frames. The resulting frame is sent into facial recognition software as an input. The image's needed feature (eye) is then extracted. The method creates a condition for each eye and suggests a certain number of frames with the same condition that can be registered.
Automobile Management System Project Report.pdfKamal Acharya
The proposed project is developed to manage the automobile in the automobile dealer company. The main module in this project is login, automobile management, customer management, sales, complaints and reports. The first module is the login. The automobile showroom owner should login to the project for usage. The username and password are verified and if it is correct, next form opens. If the username and password are not correct, it shows the error message.
When a customer search for a automobile, if the automobile is available, they will be taken to a page that shows the details of the automobile including automobile name, automobile ID, quantity, price etc. “Automobile Management System” is useful for maintaining automobiles, customers effectively and hence helps for establishing good relation between customer and automobile organization. It contains various customized modules for effectively maintaining automobiles and stock information accurately and safely.
When the automobile is sold to the customer, stock will be reduced automatically. When a new purchase is made, stock will be increased automatically. While selecting automobiles for sale, the proposed software will automatically check for total number of available stock of that particular item, if the total stock of that particular item is less than 5, software will notify the user to purchase the particular item.
Also when the user tries to sale items which are not in stock, the system will prompt the user that the stock is not enough. Customers of this system can search for a automobile; can purchase a automobile easily by selecting fast. On the other hand the stock of automobiles can be maintained perfectly by the automobile shop manager overcoming the drawbacks of existing system.
Courier management system project report.pdfKamal Acharya
It is now-a-days very important for the people to send or receive articles like imported furniture, electronic items, gifts, business goods and the like. People depend vastly on different transport systems which mostly use the manual way of receiving and delivering the articles. There is no way to track the articles till they are received and there is no way to let the customer know what happened in transit, once he booked some articles. In such a situation, we need a system which completely computerizes the cargo activities including time to time tracking of the articles sent. This need is fulfilled by Courier Management System software which is online software for the cargo management people that enables them to receive the goods from a source and send them to a required destination and track their status from time to time.
Cosmetic shop management system project report.pdfKamal Acharya
Buying new cosmetic products is difficult. It can even be scary for those who have sensitive skin and are prone to skin trouble. The information needed to alleviate this problem is on the back of each product, but it's thought to interpret those ingredient lists unless you have a background in chemistry.
Instead of buying and hoping for the best, we can use data science to help us predict which products may be good fits for us. It includes various function programs to do the above mentioned tasks.
Data file handling has been effectively used in the program.
The automated cosmetic shop management system should deal with the automation of general workflow and administration process of the shop. The main processes of the system focus on customer's request where the system is able to search the most appropriate products and deliver it to the customers. It should help the employees to quickly identify the list of cosmetic product that have reached the minimum quantity and also keep a track of expired date for each cosmetic product. It should help the employees to find the rack number in which the product is placed.It is also Faster and more efficient way.
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Water scarcity is the lack of fresh water resources to meet the standard water demand. There are two type of water scarcity. One is physical. The other is economic water scarcity.
Event Management System Vb Net Project Report.pdfKamal Acharya
In present era, the scopes of information technology growing with a very fast .We do not see any are untouched from this industry. The scope of information technology has become wider includes: Business and industry. Household Business, Communication, Education, Entertainment, Science, Medicine, Engineering, Distance Learning, Weather Forecasting. Carrier Searching and so on.
My project named “Event Management System” is software that store and maintained all events coordinated in college. It also helpful to print related reports. My project will help to record the events coordinated by faculties with their Name, Event subject, date & details in an efficient & effective ways.
In my system we have to make a system by which a user can record all events coordinated by a particular faculty. In our proposed system some more featured are added which differs it from the existing system such as security.
CFD Simulation of By-pass Flow in a HRSG module by R&R Consult.pptxR&R Consult
CFD analysis is incredibly effective at solving mysteries and improving the performance of complex systems!
Here's a great example: At a large natural gas-fired power plant, where they use waste heat to generate steam and energy, they were puzzled that their boiler wasn't producing as much steam as expected.
R&R and Tetra Engineering Group Inc. were asked to solve the issue with reduced steam production.
An inspection had shown that a significant amount of hot flue gas was bypassing the boiler tubes, where the heat was supposed to be transferred.
R&R Consult conducted a CFD analysis, which revealed that 6.3% of the flue gas was bypassing the boiler tubes without transferring heat. The analysis also showed that the flue gas was instead being directed along the sides of the boiler and between the modules that were supposed to capture the heat. This was the cause of the reduced performance.
Based on our results, Tetra Engineering installed covering plates to reduce the bypass flow. This improved the boiler's performance and increased electricity production.
It is always satisfying when we can help solve complex challenges like this. Do your systems also need a check-up or optimization? Give us a call!
Work done in cooperation with James Malloy and David Moelling from Tetra Engineering.
More examples of our work https://www.r-r-consult.dk/en/cases-en/
Democratizing Fuzzing at Scale by Abhishek Aryaabh.arya
Presented at NUS: Fuzzing and Software Security Summer School 2024
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Welcome to WIPAC Monthly the magazine brought to you by the LinkedIn Group Water Industry Process Automation & Control.
In this month's edition, along with this month's industry news to celebrate the 13 years since the group was created we have articles including
A case study of the used of Advanced Process Control at the Wastewater Treatment works at Lleida in Spain
A look back on an article on smart wastewater networks in order to see how the industry has measured up in the interim around the adoption of Digital Transformation in the Water Industry.
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LIGHTWEIGHT HEADGEAR BRAIN WAVES FOR FATIGUE DETECTION IN SMARTPHONE
1. International Journal of Computer Science & Information Technology (IJCSIT) Vol 11, No 5, October 2019
DOI: 10.5121/ijcsit.2019.11501 1
LIGHTWEIGHT HEADGEAR BRAIN WAVES FOR
FATIGUE DETECTION IN SMARTPHONE
Yung Gi Wu, Jwu Jenq Chen and Rui Hsin Wang
Department of Computer Science & Information Engineering,
Chang Jung Christian University, Taiwan.
ABSTRACT
Fatigue is an annoying phenomenon that can affect people’s concentration on learning or working. It will
reduce the learning efficiency of people and even cause danger in working. For example, fatigue driving
results in car accident have been reporting from the daily news. In order to avoid the accidents mentioned
above, this research design the mobile system to detect fatigue to alert people by way of the lightweight
brainwave detector, and the smartphone that everyone owns nowadays. In this system, light weight head
mounted brainwave device is adopted and the signal are transmitted to the smartphone for further
processing. Our algorithm calculates the fatigue index by focus, eyes blink frequency, δ-wave, α-wave, β-
wave, and θ-wave captured from the brainwave to determine human’s spiritual condition. When the
experimental results were carried out to the car drivers, the system can remind drivers when they were
tired and drowsy while driving. This system can notify people to aware his own spiritual state so as to
raise working efficacy and avoid the occurrences of accident caused by fatigue. In addition, the whole
system without complex instrument and expensive cost.
KEYWORDS
Brainwave Device, Fatigue Detecting, Smartphone, headgear
1. INTRODUCTION
Fatigue is a feeling of extreme mental and physical tiredness. The causes to fatigue could be
disease, long-term activities, drug treatment, pain, muscle weakness, over-doing, low-mood, poor
diet, hunger…etc. Most of us feel tired in monotonous activity or a long time working and
people can recover and improve this kind of fatigue after rest. Therefore, many companies or
factories make regulation to let the employees to rest after a period time of working and that can
raise company’s productivity and decrease the risk of operation caused by fatigue. However;
some jobs don’t allow employees to take a break in regular period, such as long trip drivers.
3,000~4,000 people die on the roads every day in the world and tens of millions of people are
injured or disabled every year according to report from WHO[1]. Road traffic crashes will
become the seventh cause to make people to die in the future. Traffic Safety at the American
Automobile Association (AAA) announced that driver’s fatigue is the second biggest factor to
cause road accident [2]. It leads to 100,000 car accidents every year in the USA. Most risky
driving time are between 11 p.m. to 8 a.m. For most people, our circadian rhythms tell our bodies
2. International Journal of Computer Science & Information Technology (IJCSIT) Vol 11, No 5, October 2019
2
that it’s time for sleep during that time just mentioned above. In addition, long distance driving
and take drug are all the causes to drowsy. Fatigue is fatal in some scenarios.
In general, fatigued people experience frequent yawning, heavy eyelids, misjudging operation, In
general, fatigued people experience frequent yawning, heavy eyelids, misjudging operation,
fluctuating seeing, daydreaming…etc. From the literature, we know the methods to detect fatigue,
such as eye movement patterns, face recognition analysis, and monitoring the breathing and heart
rate. The technology for detecting fatigue driving have been researching to raise the safety of
people and car. Therefore, some cars equipped with the fatigue detection system. They analyse
various clues, including steering behavior, pedal usage, and vehicle acceleration, to automatic
assess the driver's driving mental or physical states. If the system detects that the driver may be in
a state of insufficient attention, a warning light from the coffee cup will be displayed on the
driver’s screen to remind him to resting for a while. Some cars accumulate the driving times to
notify the driver to rest to recover his attention. Most of the detection system judge the state of
the driver by his external behaviours. In this paper, we detect the brainwaves of person and
analyse the signal it outputs to acquire current mental or body state. The fatigue index is
displayed on the mobile phone. If it exceeds the alarm threshold for more than 5 seconds, it will
alert by sounding alarm. At the same time, the system establishes a database to store the data after
brainwave analysis to provide users with a history for querying, to know when they are prone to
fatigue to avoid accident during periods of easy to be fatigue so as to reduce the risk of accidents.
his fatigue detection system can be used for the driver, students or operator. In the following, we
will depict some products that are adopted in real world now.
First of all, this research compares the existing fatigue-related methods. Japan, Australia, and
Spain all have been researching on detecting fatigue for various kinds of operators. Then, we
survey several available commercially brainwave meters and compare in terms of cost, accuracy,
ease of carrying (mobility), ease of operation for comprehensive evaluation to select the proper
brainwave meter instrument that meets the our requirements.
Japanese eyewear manufacturer JIN published a glasses product JINS MEME on 2014 [3]. It
measures the eight directions of the eyeball by using the electrooculography sensing technology.
The potential difference caused by changes in the eyeball and the movement of the eye in all
directions can be detected and calculated to determine the direction of movement of the line of
sight and other information.The weight of this glasses is about 40 grams. A little heavier than the
glasses that most people wear. Not all users have the habit of wearing this kind of glasses.
A seeing machines company in Canberra, Australia, designed and developed the Fatigue
Monitoring System for mine truck drivers in 2013 [4]. The size used for the mine truck driver is
so large that it can easily cause staff to be masked by the vehicle next to him. This system
consists of a set of infrared cameras that can be detected even when driving with sunglasses that
cover the eyes. It also includes an image processor that records the duration, frequency, and
speed of eyes blink to evaluate if distraction or involuntary fragment sleep happened. Once the
system determines that the mental condition is poor, the chair not only makes strong vibrations
but also sounds harsh alarms. However, if the driver's eyes cannot be detected by the camera
because of occasional bowing his head, the alarm will sound as well.
The Valencia Institute of Biomechanics in Valencia developed the "HARKEN" smart seat belt,
which detects the breathing and heartbeat frequency of driving and warns in times of crisis; this
3. International Journal of Computer Science & Information Technology (IJCSIT) Vol 11, No 5, October 2019
3
equipment consists of three main parts, first the seat belt The heartbeat sensor is followed by a
breathing detector near the back of the chair, and finally the signal processing unit "SUP" under
the seat, which is responsible for analysing the data of all electronic detectors [5]. Endurance
athletes, whose heartbeat is lower than the normal people may make the smart seat belt misjudge.
At the 2014 Consumer Electronics Show (CES) in Las Vegas, Xuan Rui Technology from
Taiwan demonstrated a device called U-Wake, a standard human-machine interface wearing
device that can detect dangerous driving through the change of brainwaves. The brainwave
fatigue detector uses brain-computer interface technology. The degree of user fatigue can be
instantly displayed on the mobile phone's APP, and reminds the user to stay awake [6], but the
system is very expensive.
The above four products are available in the market to remind the mental or physical fatigue state
for the operator during his operation. We depict various kinds of brainwave-meter instruments in
the following. The first one is the traditional headgear device. When performing brainwave
measurement in traditional way, people should wear a special headgear as shown in Figure 1 to
collect the signal. There are multiple electrode pads in the headgear to contact the scalp, and the
scalp should be wet-adhesive. The test site must be manipulated in a specific and non-interfering
environment, such as in hospital. It is difficult for car drivers or mechanical operator’s usage.
Figure 1. Headgear style brainwave meter [7]
The second whole brain covered high density brainwave instrument by dEEG. dEEG is a medical
device company that uses the most advanced EEG technology to create a brain-covered high-
density brainwave instrument as shown in Figure 2[8]. It has accurate and convenient recording
system. In addition, it has 32, 64, 128 or 256 channels to select. The operator of this instrument is
required to have the original and complete training to operate it correctly. It is not suitable for
general usage either.
Figure 2. Whole brain covered high density brainwave instrument by dEEG[8]
4. International Journal of Computer Science & Information Technology (IJCSIT) Vol 11, No 5, October 2019
4
The third one is mindwave mobile starter brain cube as shown in Figure 3 [9]. It is a lightweight
research-grade EEG headset. Wear it like listening to music with headphones so that it is suitable
for various kind of operators to use. The embedded bio-sensor chip can read EEG signalsby non-
invasive dry electrodes, filter out nearby noise and electrical interference, and convert the
measured signals into digital signal [10].Measured data obtained through this device contain raw
brainwaves, concentration, blink detection, relaxation and even more including detecting whether
the device is worn in poor contact. These data can assist to analyse brainwaves in relatively
simple way and develop a variety of applicable functionalities. This device owns the advantage
of easy to carry and highsensing precision. Moreover; the cost of this equipment is only a small
portion of research-grade equipment but it reaches 96% accuracy compared to research-grade
instrument.
Figure 3. Mindwave mobile starter brain cube
Table 1 shows the comparisons among the three brainwave instruments depicted above.
Table 1 Comparisons of brainwave meters
Type
Traditional
headgear style
Whole brain
covered high
density style
Mobile starter
brain cube
cost high high low
precision high high high
mobility no no yes
operation&
manipulation
complicated
Professional
training
easy
conditions for
measurements
undisturbed
environment
uncomfortable unlimited
After considering all perspectives, we adopt mobile starter brain cube to be our brainwave meter
instrument.
In [10], they conducted a study to measure the changes in mental workload of EEG in a non-
invasive manner situation. Based on the simulation of the driving platform, the brainwave is used
to analyse and estimate the driver's driving situation. Time-frequency analysis and other
technologies are used to construct a system to estimate the driver's psychological state by
brainwaves. In [11], it’s a study on driver’s brainwave cognitive response estimation through
non-invasively recorded brainwave analysis to identify the human brain's response to event
stimuli and to estimate the driver's spiritual alert level to dynamically measure the driver's mental
state change, and simultaneously measure the corresponding cognitive, vehicle control and
5. International Journal of Computer Science & Information Technology (IJCSIT) Vol 11, No 5, October 2019
5
driving behaviour changes to maintain the driver's in good spirt mode to prevent driving accidents
in driving. In [12], it used EEG components to evaluate the algorithm for detecting fatigue. It
confirmed that the ratio of slow wave to fast wave in EEG activity increased with time, and the
results of this study have the significance of detecting fatigue. In [13], it claimed that as a person
fatigues, the brain loses capacity and slowdown his activity behaviour, and that attempts to
maintain vigilance levels leading to increased β wave activity. According to the literature survey,
most of the researches are in the academic field of biological category. They research and find
out relationship between the brainwave and fatigue condition. However, no one uses the
brainwave data to make a convenient device system for users to measure fatigue while operating
or working. In this research, we detect and driver’s fatigue and record the brainwave data in the
database. We can not only detect the fatigue condition but also recording the data for long term
observation in easy and convenient way.
In this paper, we adopt SQLite to record the data. SQLite is an open source database library, and
complies with the standards of ACID-related database. It uses a standard SQL syntax to provide
a stand-alone database system that does not require a connecting to environment. It is widely
used in various operating systems, embedded systems and browsers. Android supports the
SQLite database, so that each application can create its own database, store the data in the SQLite
database file, the developers can use the API library provided by Android to access the data in the
database for specified applications, including query, add, delete and update standard SQL access
syntax, it can also set the version of the database, you can also copy and migrate the database in
the new version, so we chose it to build database.
2. THE PROPOSED METHOD AND SYSTEM ESTABLISHMENT
2.1 Brainwave detection
The whole system comprises two major stages. The first stage is to collect the signals from
mobile starter brain cube meter. The signals are transmitted to the smartphone to process by
Bluetooth. Brainwave analysis and recording in the smartphone are the major topics in the
second stage. The brainwave acquired by brain cube meter is divided into different bands by
Fourier transform. This device has embedded an eSense algorithm that can generate the
following data: original brainwave signal, concentration, relaxation indices, brainwave band data
(δ, θ, α, β) and blink detection. Physical and psychological conditions represented by various
frequency bands of brainwaves can be found easily from web. The general properties and
frequency ranges of the δ, θ, α, β waves are given in Table 2[14].
Table 2 Brainwaves properties and frequency ranges
Brainwaves Frequency Property
Delta (δ) 0.1~3 Hz Unconscious condition.
Occurs during the third phase of non-rapid eye
movement sleep.
Theta (θ) 4~7 Hz Denote subconscious condition
There are memories, perceptions and
emotions.
Affect attitudes, expectations, beliefs,
behaviors.
6. International Journal of Computer Science & Information Technology (IJCSIT) Vol 11, No 5, October 2019
6
The source of creativity and inspiration. Deep
sleep, deep meditation.
Psychic awareness, strong personal
knowledge, strong personality
Alpha(α) Low range 8~9Hz A state of mind before going to sleep.
Consciousness is gradually drowsy.
Middle
range
9~12Hz Inspiration, intuition or idea raising.
Relaxed but focused
High range 12~14Hz Highly alert.
Beta(β) Low range 12.5~16Hz Relax but concentrated.
Middle
range
16.5~20 Hz Thinking, dealing with external messages.
High range 20.5~28 Hz Excitement, anxiety
The brainwave used to represent the body health can be brief depicted as follows. δ wave: rest
wave. Deep sleep state will appear generally in high value.θ wave: repair wave. Extremely
relaxed, also known as the Buddha brainwave, strong repair. αwave: healthy wave. Relax
brainwaves, high immune status, secrete morphine in the brain, and have self-healing ability. β
wave: sick wave. Nervous brainwaves, low immunity, easy to get sick.
The TGAT chip in the mindwave mobile starter brain cube, which is a highly integrated system
single-chip brain inductor that can perform analogy-to-digital conversion, which can detect
abnormalities in poor contact, and filter out abnormal eye movements and 50hz and 60hz AC
signal interference in circuit; eSense is an algorithm that is capable of measuring the mental state
and collects the user's concentration index and blink strength. In this research, the four frequency
bands signal (δ, θ, α, β), concentration index and the blink strength are transmitted by Bluetooth
to smartphone for further fatigue detection and stored for long term observation.
2.2 SQLite database establishment
We develop an APP that can be installed in smartphone to increase the mobility of this system.
APP is a convenient way to any end users to use because it has the advantage of mobility. For the
diver, all he has to do is to install the APP in his smartphone and open this APP while driving. Of
course, he must wear the brain cube in his head. The following section will give you a brief
depict about our SQLite database design in smartphone side. We adopt the Android Studio to
implement the system including user interface, Bluetooth connection and SQLite database.
Note that the user must register an account to keep his own data. The historic data can be
observer by user to know his own mental condition in every driving. If his friend wants to use this
smartphone to raise the driving safety, his friend can register another account.
In this the research, the whole project has six activities named Main Activity, register, Bluetooth,
show_result, record and Record DBHelper. The functions are the main page, registration screen,
Bluetooth connection screen, display measurement data screen, history record andlayout
respectively. Below figure shows the project structure (Figure 4).
7. International Journal of Computer Science & Information Technology (IJCSIT) Vol 11, No 5, October 2019
7
Figure 4.Project configuration of this APP
The database created by SQLite is used to store the user's basic data and usage records. The
project first creates a database named "brainwaves". The database contains two data tables named
"User" and "Data" (Figure 5). "User" table includes _id, name, gender, age, phone, account and
password. The "Data" data table is used to store the relevant data of the driver's use process. The
nine fields includes _id, date, time, alpha, beta, delta, theta, focus and wink. The primary key is
_id. Note that the value ranges of alpha, beta, delta, theta, focus and wink are from 1~100.
Figure 5. Brainwaves database fields
Use SQLite to add DATABASE named "brainwave". Create a "user" data table under
"brainwave", and in the on Create method, after getting the SQLite Database object, call the
execSQL method to create a "user" data table. Using the above method in "brainwave" to create
a "data" datatable under the "brainwave" database by calling the execSQL.
When the user registers, system will confirm whether the data entered by the user are all filled in.
The name, gender, age, mobile phone number, account number and password must not be null
before the file can be written. Using getWritableDatabase() to construct the database,
ContentValues values = new ContentValues() to store the data to be added, and db.insert() to
write the data to the database. Figure 6 shows how they work.
8. International Journal of Computer Science & Information Technology (IJCSIT) Vol 11, No 5, October 2019
8
Figure 6. Program codes for user registration
2.3 Fatigue detection criteria
Common features of fatigue include: body and limbs feeling heavy and difficult to move, flu-like
feelings of exhaustion, eyelids are heavy, feeling energy has drained away slowly. When fatigue
is severe, it can lead to feelings of energy complete exhaustion, or ‘wipe-out’. Then, you have to
sit or lie down to try to recover. Otherwise, it can lead to dangerous no matter in driving or
operating machine. For the students, it can obstruct the learning in classroom or self-learning.
In this paper, aiming at our goal to detect fatigue before body physical lie down. The mindwave
mobile starter brain cube reads the brainwave in the sampling rate of 512 Hz. But, we just take
one data per second in case occupying too much data storage in smartphone. After the data is
written into the database, the obtained δ, θ, α and β. Note that α and β values that we acquire
from brainwave are α_mid and β_low which presenting the awaken state. However; the middle
frequency of α wave(α_mid) and the low frequency of β wave (β_low) are the representative
values of focus and concentration. While the δ and θ waves denote the unconscious state. Under
the brainwave pattern, the purpose of this project is to detect the degree of fatigue by measuring
brainwaves under awake conditions. Therefore, the α_mid and β_low represent the sobriety and
concentration are placed in the denominator, δ and θ represent the unconscious state are placed in
the numerator. If a person is feeling fatigued or drowsy, his eye blinking pattern changes that is
varied from the average blinking period. When we wear this device, we calculate the averaged
wink (winkavg) value in the first minute. Therefore, the signal of focus and blink values (wink)
are integrated together also to obtain the fatigue index as in (1).
𝑓𝑎𝑡𝑖𝑔𝑢𝑒_𝑖𝑛𝑑𝑒𝑥 =
δ+θ
αmin+βlow
∗ 𝑤1+
1
𝑓𝑜𝑐𝑢𝑠
∗ 𝑤2 + |𝑤𝑖𝑛𝑘 − 𝑤𝑖𝑛𝑘 𝑎𝑣𝑔| ∗ 𝑤3(1)
Higher fatigue_index denotes the mental or physical state is drowsy. If the fatigue indices exceed
the threshold value and lasting for the time that we set, the APP in the smartphone will sound
alarm to remind us to be careful or rest to avoid any dangerous event happened. The parameters
(w1, w2, w3) in (1) are set to (10,5,5) after repeated experiments.
9. International Journal of Computer Science & Information Technology (IJCSIT) Vol 11, No 5, October 2019
9
3. EXPERIMENTAL RESULTS
Fatigue is one of the significant factors to cause harm, accidents, and hazard in industries.
Especially to the jobs such as mining, transportation, construction, manufacturing and healthcare.
To the students in classroom or the employees in company, fatigue obstructs the learning and
working efficiency as well. In order to avoid the occurrences of dangerous during the
experiments, we exclude experiments that lead to a fatal crisis to carry out. The students,
employees in office and the driver are invited to participant the experiments.
Most of the people feel drowsy after lunch; therefore, most of the companies provide one or two
hours rest time to the employees to lunch and take a nap. Twelve students and eight employees in
office whose ages are from 18 to 37 took part in the experiment. The fatigue-index threshold to
alert alarm we set in this research is 40. They were requested to take the lightweight brainwave
device after lunch. Two of them felt uncomfortable because the device must clamp to the left ear
lobe while wearing it so as to fail to the test. The other eighteen participants were reminded by
smartphone when they felt drowsy to sleep.
Next experiment was kind of risky. Because fatigue driving harms to human life seriously, we
made the experiment to drivers. In this test, ten people whose ages are from 20 to 50 were invited
to participant this research. The driving time was from pm 10:00 to 11:00 because circadian
rhythms tell our bodies that it’s time for sleep for normal people. Nine people completed the test.
Seven of them agreed that it had a remind effect. Two of the testers who are young drivers
thought that there was no feeling about this system. They are accompanied by friends and chatted
with them while driving. One tester claimed that she was not used to reacting with this device
because of the clamping to the left ear lobe, she felt uncomfortable and could not finish the test.
Figure7 illustrates the fatigue-index curve of a tester who is 50 years old man. He was asked not
to turn on the radio in car and driving alone. There are 3600 seconds in one hour recording.
Those values that are suddenly abnormally high in the earlier time could be the device error. It
could be the error caused by poor contact of the measuring point or the light from the opposite
road. When the fatigue-index exceeded the threshold for more than 5 seconds, it alerted the
driver by sounding alarm. It can be observed that he could only concentrate on driving at the
early stage.
Figure 7. Fatigue-index data for 3600 seconds
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To sum up, twenty five testers were reminded when they felt fatigue successfully. The
experiments demonstrated that the system can remind people when they felt drowsy. In addition,
even though the device is lightweight but it need to clamp to the left ear lobe, some of testing
people experienced it uncomfortable.
4. CONCLUSION
Fatigue could be a fatal crisis in real world. It is a mental or physical tired state for human so as
to cause dangerous to operating machine or obstruct the learning or working efficiency. Some
researchers have been carrying out to the apparent behaviours analysis to detect the fatigue;
however, it could be too late once the apparent behaviours happened. This research adopt
brainwave to detect fatigue and hope to remind people before crisis occurred. Most of brainwave
measure instruments are expensive and professional operators are required to operate them. In
addition, they are not easy to wear to head so that they are suitable for general usage. In this
paper, we use a lightweight brainwave device which is easy to use and wear to head to detect
fatigue. Experiments demonstrated that it’s capable to detect the fatigue for school students and
employees in company. Furthermore, the crisis of injury caused by fatigue driving is getting
more and more serious. When big accident occurred, the government institute always review
driver’s driving regulation, such as forcing the tour bus driver to rest after driving one to two
hours. However; the physical fitness and mental state of each driver are different. We don’t know
whether the driver take drug or drink wine before driving. Even enough resting time, fatigue
driving still may occur. Therefore, the most important thing to avoid fatigue driving is immediate
detection and reminding. The brainwave detection driving fatigue system built by the research
can remind the driver by sounding alarm when fatigue occurs. Drivers only need to buy a
headgear brainwave and smartphone then equipping this APP. The system has two features of
low cost and easy to operation which can raise the user's willingness to purchase and use. We
want to encourage drivers to adopt this technology and use it to decrease accidents caused by
fatigue. As to the further development, the brainwave device and the hat can be integrated on the
hardware to facilitate the driver's willingness to use. The long term historic record can also be
applied to other mental–related issues.
ACKNOWLEDGEMENTS
The authors would like to appreciate the partial support from the Minister of Science &
Technology, Taiwan under the project no. 106-2813-C-309-002-E. The preliminary paper was
presented in the ICAIT 2019 [15].
REFERENCES
[1] World Health Organization. (2018).Road traffic injuries. Available at:
https://www.who.int/violence_injury_prevention/road_traffic/en/ [Accessed 10 Nov. 2018].
[2] Collision, W. (2018).The Leading Causes of Car Accidents - Causes and Statistics. Waterdown
Collision. Available at: https://www.waterdowncollision.com/blog/safe-driving/leading-causes-of-
car-accidents/ [Accessed 10 Nov. 2018].
[3] JINS MEME. (2018).JINS MEME: The world’s first wearable eyewear that lets you see yourself.
Available at: https://jins-meme.com/en/ [Accessed 10 Nov. 2018].
11. International Journal of Computer Science & Information Technology (IJCSIT) Vol 11, No 5, October 2019
11
[4] Seeing Machines. (2018).Driver monitoring technology for automotive, transport & logistics
industries. Available at: https://www.seeingmachines.com/ [Accessed 10 Nov. 2018].
[5] Harken.ibv.org. (2018).Wouldn't you want an alarm to go off if you fall asleep driving?. Available
at: http://harken.ibv.org/ [Accessed 10 Nov. 2018].
[6] Digital Trends. (2018).U-Wake | Wearable brainwave sensor alerts fatigued drivers | Digital Trends.
Available at: https://www.digitaltrends.com/cars/u-wake-wearable-brainwave-sensor/ [Accessed 11
Nov. 2018].
[7] Evolving Science. (2017).Monitoring the Brain Outside the Lab. Evolving Science. Available at:
https://www.evolving-science.com/bioengineering-brain-computer-interfaces/monitoring-brain-
outside-lab-00129 [Accessed 11 Nov. 2018].
[8] Nutronic Techtronic Co. (2018).dEEG whole brain covered high density brain wave. Available at:
http://nutronicltd.com/?deeg%E5%85%A8%E8%85%A6%E8%A6%86%E8%93%8B%E5%BC%8
F%E9%AB%98%E5%AF%86%E5%BA%A6%E8%85%A6%E6%B3%A2%E5%84%80,177
[Accessed 11 Nov. 2018].
[9] NeuroKky. (2018).EEG Headsets | NeuroSky Store. Available at: https://store.neurosky.com/
[Accessed 12 Nov. 2018].
[10] Teng-Yi Huang,“Development of dynamic VR driving platform and its application on driver's
cognitive state estimation,”Master dissertation, Dept. Elect. & Ctrl. Eng., National Chiao Tung
Univ., Hsinchu City, Taiwan, 2003.
[11] Ruei-Cheng Wu, “EEG-Based Assessment of Driver Cognitive Responses and Its Application to
Driving Safety,” Ph.D. dissertation, Dept. Elect. & Ctrl. Eng., National Chiao Tung Univ., Hsinchu
City, Taiwan, 2005.
[12] Jap, B. T., Lal, S., Fischer, P., &Bekiaris, E., (2009)“Using EEG spectral components to assess
algorithms for detecting fatigue”, Expert Systems with Applications,Vol. 36, No. 2, pp2352-2359.
[13] Craig, A., Tran, Y., Wijesuriya, N., & Nguyen, H., (2012)“Regional brain wave activity changes
associated with fatigue”, Psychophysiology, Vol 49, No 4,pp574-582.
[14] Wikipedia. (2018).Brainwave - Wikipedia, the free encyclopaedia. Available at:
https://zh.m.wikipedia.org/zh-tw/%E8%85%A6%E6%B3%A2 [Accessed 12 Nov. 2018].
[15] Yung Gi Wu, JwuChenq Chen, RuiHsin Wang ,'The System Design for Fatigue Driving Detection by
Brainwaves Analysis in Smartphone', 8th International Conference on Advanced Computer Science
and Information Technology (ICAIT 2019) , Mar. 2019 , pp. 1-11 ,Zurich.
AUTHORS
Yung Gi Wu. He received Ph. D. degree from the Institute of Electrical
Engineering. National Cheng Kung University. Tainan, Taiwan, 2000. He is now a
professor with the Department of Computer Science & Information Engineering.
Chang Jung Christian University in Taiwan. His research fields includes data
compression, optimization, information retrieval, digital signal processing, AI& IoT
applications.
12. International Journal of Computer Science & Information Technology (IJCSIT) Vol 11, No 5, October 2019
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Jwu-Jenq Chen was born in Tainan County in Taiwan. He obtained a MS degree
from the Graduate Institute of computer science, Ohio University in U.S.A., 1996 and
then received a Ph.D. from the Graduate School of Business and Operations
Management, Chang Jung Christian University in Taiwan.He had worked as
technician and supervisor on computer system for 13 years. At this time, he is
anAssociate Professor at the department of Computer Science and Information
Engineering at the Chang Jung Christian University in Taiwan. Hisresearch fields
includes management information system and website.
Rui Hsin Wang. She received the bachelor degree from the Department of Computer
Science and Information Engineering at the Chang Jung Christian University in
Tainan, Taiwan, 2017. She is now a student in the Institute of Information
Engineering. National Chung Hsing University. Taichung. Taiwan.Her research
fields includes digital signal processing and mobile computing.