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DRIVER DROWSINESS
DETECTION BY USING
WEBCAM
< A Safty Based Project>
{
}
...
Table of Content
• Introduction
• Objectives of this project
• Scope of Study
• Technology used
TECHNIQUES
LIBRARIES
ALGORITHMS
Future Enhancement
Instroduction
Drowsiness is a state of near sleep, where the person has a strong desire for sleep. It
has two distinct meanings, referring both to the usual state preceding falling asleep and the
chronic condition referring to being in that state independent of a daily rhythm [16].
Sleepiness can be dangerous when performing tasks that require constant concentration,
such as driving a vehicle. When a person is sufficiently fatigue while driving, they will
experience drowsiness and this leads to increase the factor of road accident.
FIG 1 : Road Accidents In India
Figure 1 shows the statistic of road accident in India
from the year 2018 to 2023 provided by IIROS (Indian
Institute of Road Safety). The numbers of vehicles involved
in road accident keep increasing each year. From Figure 1,
car and taxi type of vehicles shows about nearly 400,000
cases of road accident has been recorded. It keeps increasing
every year and by the year 2021 it shows the number of road
accident were recorded by IIROS are nearly 500,000.
Objectives of this project
 To suggest ways to detect fatigue and drowsiness while driving.
 The project focuses on these objectives, which are:
 To study on eyes and mouth from the video images of participants in
the experiment of driving simulation conducted by MIROS that can
be used as an indicator of fatigue and drowsiness.
 To investigate the physical changes of fatigue and drowsiness.
 To develop a system that use eyes closure and yawning as a way to
detect fatigue and drowsiness.
Scope of Study
• In this project, the author will focus on these following procedures:
• Basic concept of drowsiness detection system
• Familiarize with the signs of drowsiness
• Determine the drowsiness from these parameters
• Eye blink
• Area of the pupils detect at eyes
• Yawning
• Data collection and measurement.
• Integration of the methods chosen.
• Coding development and testing.
• Complete testing and improvement.
TECHNOLOGY USED
LIBRARIES
● OpenCV
● Dlib
● Py game
● NumPy and SciPy
● Imutils
1. PYTHON
2. IMAGE PROCESSING
3. MACHINE LEARNING
ALGORITHM
• EAR
Detection
TECHNIQUES
Python is an interpreted, high-
level, general-purpose
programming language. Machine learning is the scientific study
of algorithms and statistical models that
computer systems use in order to
perform a specific task effectively
without using explicit instructions,
relying on patterns and inference
instead.
PYTHON
IMAGE PROCESSING
MACHINE LEARNING
digital image processing is the use of
computer algorithms to perform image
processing on digital images.
This program is used to find
the frontal human face and
estimate its poses using 68
landmarks
It is used for Sounding the alarm.
Pygame is a set of python modules
designed for writing video games
LIBRARIES
OpenCV (Open Source Computer
Vision Library) is essential for image
and video processing tasks etc. In driver
drowsiness detection
These libraries may be used for
numerical computations and
statistical analysis if advanced
algorithms or statistical models are
incorporated into the drowsiness
detection system.
Imutils is a Python library
that simplifies common
image processing tasks, often
used alongside OpenCV
OpenCV Dlib Py game
NumPy and SciPy Imutils
{
} ..
..
ALGORITHM
EAR Detection
• Time-of-Day Analysis:
By analyzing the time of day, the system can infer patterns in driver behavior, such as increased drowsiness during late-night or early-morning hours, allowing for adaptive alertness
thresholds.
• Duration of Alertness:
Monitoring the duration of continuous driving without breaks helps identify fatigue buildup, triggering alerts when prolonged periods of driving occur without rest.
• Blink Frequency and Duration:
Tracking the frequency and duration of eye blinks over time provides insights into changes in alertness levels, with longer or more frequent blinks indicating potential drowsiness.
• Reaction Time Analysis:
Monitoring the driver's reaction time to external stimuli over time helps detect delays, which could be indicative of decreased alertness or fatigue.
• Session Logging and Analysis:
Recording timestamps of significant events such as alerts, driver interventions, or environmental changes allows for post-session analysis to identify patterns and trends in drowsiness
occurrence.
By integrating time-related functions into the drowsiness detection system, it becomes more robust and capable of providing timely alerts and interventions to ensure driver safety on
the road.

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Introduction to Java Programming for High School by Slidesgo.pptx

  • 1. DRIVER DROWSINESS DETECTION BY USING WEBCAM < A Safty Based Project> { } ...
  • 2. Table of Content • Introduction • Objectives of this project • Scope of Study • Technology used TECHNIQUES LIBRARIES ALGORITHMS Future Enhancement
  • 3. Instroduction Drowsiness is a state of near sleep, where the person has a strong desire for sleep. It has two distinct meanings, referring both to the usual state preceding falling asleep and the chronic condition referring to being in that state independent of a daily rhythm [16]. Sleepiness can be dangerous when performing tasks that require constant concentration, such as driving a vehicle. When a person is sufficiently fatigue while driving, they will experience drowsiness and this leads to increase the factor of road accident.
  • 4. FIG 1 : Road Accidents In India Figure 1 shows the statistic of road accident in India from the year 2018 to 2023 provided by IIROS (Indian Institute of Road Safety). The numbers of vehicles involved in road accident keep increasing each year. From Figure 1, car and taxi type of vehicles shows about nearly 400,000 cases of road accident has been recorded. It keeps increasing every year and by the year 2021 it shows the number of road accident were recorded by IIROS are nearly 500,000.
  • 5. Objectives of this project  To suggest ways to detect fatigue and drowsiness while driving.  The project focuses on these objectives, which are:  To study on eyes and mouth from the video images of participants in the experiment of driving simulation conducted by MIROS that can be used as an indicator of fatigue and drowsiness.  To investigate the physical changes of fatigue and drowsiness.  To develop a system that use eyes closure and yawning as a way to detect fatigue and drowsiness.
  • 6. Scope of Study • In this project, the author will focus on these following procedures: • Basic concept of drowsiness detection system • Familiarize with the signs of drowsiness • Determine the drowsiness from these parameters • Eye blink • Area of the pupils detect at eyes • Yawning • Data collection and measurement. • Integration of the methods chosen. • Coding development and testing. • Complete testing and improvement.
  • 7. TECHNOLOGY USED LIBRARIES ● OpenCV ● Dlib ● Py game ● NumPy and SciPy ● Imutils 1. PYTHON 2. IMAGE PROCESSING 3. MACHINE LEARNING ALGORITHM • EAR Detection
  • 8. TECHNIQUES Python is an interpreted, high- level, general-purpose programming language. Machine learning is the scientific study of algorithms and statistical models that computer systems use in order to perform a specific task effectively without using explicit instructions, relying on patterns and inference instead. PYTHON IMAGE PROCESSING MACHINE LEARNING digital image processing is the use of computer algorithms to perform image processing on digital images.
  • 9. This program is used to find the frontal human face and estimate its poses using 68 landmarks It is used for Sounding the alarm. Pygame is a set of python modules designed for writing video games LIBRARIES OpenCV (Open Source Computer Vision Library) is essential for image and video processing tasks etc. In driver drowsiness detection These libraries may be used for numerical computations and statistical analysis if advanced algorithms or statistical models are incorporated into the drowsiness detection system. Imutils is a Python library that simplifies common image processing tasks, often used alongside OpenCV OpenCV Dlib Py game NumPy and SciPy Imutils { } .. ..
  • 10. ALGORITHM EAR Detection • Time-of-Day Analysis: By analyzing the time of day, the system can infer patterns in driver behavior, such as increased drowsiness during late-night or early-morning hours, allowing for adaptive alertness thresholds. • Duration of Alertness: Monitoring the duration of continuous driving without breaks helps identify fatigue buildup, triggering alerts when prolonged periods of driving occur without rest. • Blink Frequency and Duration: Tracking the frequency and duration of eye blinks over time provides insights into changes in alertness levels, with longer or more frequent blinks indicating potential drowsiness. • Reaction Time Analysis: Monitoring the driver's reaction time to external stimuli over time helps detect delays, which could be indicative of decreased alertness or fatigue. • Session Logging and Analysis: Recording timestamps of significant events such as alerts, driver interventions, or environmental changes allows for post-session analysis to identify patterns and trends in drowsiness occurrence. By integrating time-related functions into the drowsiness detection system, it becomes more robust and capable of providing timely alerts and interventions to ensure driver safety on the road.