Drowsiness Detection System
FINAL YEAR PROJECT PROPOSAL
DEPARTMENT OF COMPUTER SCIENCE F.G
DEGREE COLLEGE MEN
PROJECT: DROWSINESS DETECTION SYSTEM
PROJECT COORDINATOR: ASSOCIATE PROFESSOR
SIR IKRAMULLAH
Submitted by:
•
•
•
Syed Ishfaq Hussain (191207)
Zulqurnain Haider (191194)
Muhammad Hassan (191197)
Agenda
■Introduction:
■Literature Review:
■Problem Statement:
■Proposed Solution:
■Future Work:
■ Introduction:
Driver fatigue is a major cause of road accidents, leading to loss of
life and property. To address this problem, we developed a drowsiness
detector using Python. The system uses a camera to monitor the driver's
eyes and sounds an alarm if the driver is detected as drowsy.
■ Literature Review:
Existing literature on drowsiness detection systems highlights the
use of physiological signals and driver behavior analysis for accurate
detection. This literature review aims to provide a concise overview of the
key research findings and methodologies employed in the development of
drowsiness detection systems.
■ Problem Statement:
Drowsiness among drivers poses a significant risk to road safety,
leading to accidents and fatalities. The lack of an effective and reliable
drowsiness detection system blocks timely intervention. Therefore, there is a
need to develop a real-time drowsiness detection system that can accurately
identify drowsy states and provide timely alerts to prevent accidents caused by
driver fatigue.
■ Proposed Solution:
Our drowsiness detector uses a computer vision technique to detect the
driver's eyes and monitor their state. The objective of this project is to detect
drowsiness in a driver by monitoring their eyes using a camera and alerting
them if they are detected as drowsy.
■Future Work:
Our system was able to achieve a high level of
accuracy in detecting drowsiness in images and in real-world
scenarios. In the future, we plan to improve the accuracy of
the system by using more advanced computer vision
techniques and exploring other datasets to train the model.
■ Hardware Used:
• Camera: Connect a camera (webcam or external camera) to
your laptop. Ensure that the camera has a clear view of the driver's
face.
•
Laptop : Use your laptop as the primary hardware for
processing the camera feed and running the drowsiness detection
algorithm.
■ Software Used:
• Python
• Python Libraries
➞ OpenCV
➞ Numpy