1. Driver Sleep Detection System
Department of Computer Engineering, PC polytechnic
Pimpri Chinchwad Education Trust’s
Pimpri Chinchwad Polytechnic
(An ISO 9001:2008 Certified Institute)
Sector No. 26, Pradhikaran, Nigdi, Pune –
411044.
Phone: 27658797/27654156
Email:principal@pcpolytechnic.com
Record No. CO-R-14
Revision : 00 Date : 01-06-18
Page : 01/01
Computer Department (Odd Sem. 2021-2022)
Final Year Project Synopsis
Driver's Sleep Detection System
PROJECT SYNOPSIS ON
Driver's Sleep Detection System
DIPLOMA IN
COMPUTER ENGNEERING
SUBMITTED BY
Group No-13
Roll no Name
23 Vrushabh Bhanjewal
25 Aasim Sayyad
61 Sudhanshu Shukla
62 Aniket Khatal
Pimpri Chinchwad Polytechnic Pradhikaran, Nigdi,
Pune – 411044.
Mrs S.S.Jogdand Prof. M.S. Malkar
(Project Guide) (H.O.D.,CO Dept.)

2. Driver Sleep Detection System
Department of Computer Engineering, PC polytechnic
ProjectTitle (project name):- Driver SleepDetection System
1. Abstract/Problem Identification
Feeling sleepy while driving could cause hazardous traffic accident. However,
when driving alone on highway or driving over a long period of time, drivers are inclined to
feel bored and sleepy, or even fall asleep. Nowadays most of the products of driver anti-sleep
detection sold in the market are simply earphone making intermittent noises, which is quite
annoying and inefficient. As such, there is a high demand for cheap and efficient driver sleep
detection. Therefore, we came up with an idea and successfully developed a sleepy detection
and alarming system, which could effectively meet this demand
2. Literature Survey
There are various techniques that can be used to detect the drowsiness of drivers.
The techniques can be generally divided into the following categories: sensing of
physiological characteristics, sensing of driver operation, sensing of vehicle response,
monitoring the response of driver.
A. EYE BLINK SENSOR: It is necessary in our working to find the blinking of eye,
since it is used to drive the device and to operate events. So blink detection has to be
done, for which we can avail readily available blink detectors in market (Catalog No.
9008 of Enable devices) or we can incorporate it with a special instruction written in
image processing that, if there is no pupil found for the certain period of pre-
determined i.e. time greater than the human eye blinking time then consider an event
called “blink”, for which the set of operations will be followed.
B. ARM7LPC2148: ARM stands for Advanced RISC Machines. It is a 32bit processor core
used for high end applications. The LPC2148 microcontrollers are based on a 16-
bit/32-bit ARM7TDMI-S CPU with real-time emulation and embedded trace support,
that combine the microcontroller with embedded high speed flash memory ranging
from 32KB to 512KB. ARM (Advanced RISC Machine)T–The Thumb 16 bit
instruction set. A 128-bit wide memory interface and unique accelerator architecture
enable 32-bit code execution at the maximum clock rate [4]. For critical code size
applications, the alternative 16-bit Thumb mode reduces code by more than 30 % with
minimal performance penalty.
3. Proposal
The algorithm aims to accurately detect the sleepiness of the driver by open eye
and close eye recognition. The sleepy detection algorithm is built on C++ and OpenCV
library. The test was first implemented and tested on the computer, then on the Beagle board.
The algorithm includes two parts: daytime detection and night detection. First and Foremost,
based on the average intensity of pixels, the algorithm classifies the environment as daytime

3. Driver Sleep Detection System
Department of Computer Engineering, PC polytechnic
or night. For daytime, the image quality is good enough, therefore no image enhancement is
required; for night, because the poor contrast of the images, histogram equalization, a method
to expand the color range of the image from 0 to 255, is implemented. In this case, we need a
light the slightly illuminate the driver. In the next step, as soon as the driver has entered the
car, two base images are recorded automatically – open eye as well as close eye. These two
images are used as the base for further determination of whether the drivers’ eye is open or
close. Afterwards, the driver could start driving. The detection algorithm is in real time and
the eye portion is extracted by using the iterative Haar Classifier. After the current eye
portion is extracted, we use template matching function built in OpenCV to determine if the
eye is open or close. If the eye has been closed for more than two seconds, sleepiness is
detected and the program will send a signal to raspberry
I) Architectural model
II) Technical requirement
1. Webcam
2. Raspberrypi 3+ model
3. BuzzerwithLED
4. Wires
5. LED
III) Hardware Requirement
1. Laptop
2. Extension Board
3. Temporary Storage
IV) Software Requirement
1. Pycharm IDE
2. Eclipse IDE
4. Execution Plan

4. Driver Sleep Detection System
Department of Computer Engineering, PC polytechnic
I).Scope of Project
The scope of this project is to develop a system that can accurately detect sleepy
driving and make alarms accordingly, which aims to prevent the drivers from drowsy driving
and create a safer driving environment. The project was accomplished by a Webcam that
constantly takes image of driver, a raspberry board that implement image processing
algorithm of sleepy detection, and a feedback circuit that could generate alarm and a power
supply system.
II). Plan For Project Implementation(Plan start from Sep-March month)
5. References
[1] "CT-1205CL-SMT Buzzer." Retrieved from http://www.digikey.com/product-
detail/en/CT-1205CL-SMT/102-1267-1-ND/610975.
[2] "XM7 USB port Data sheet." Retrieved from http://www.digikey.com/product-
detail/en/XM7A-0442A/OR1070-ND/2755612
[3] "TPS61032 (ACTIVE) 5-V Output, 1-A, 96% Efficient Boost Converter." Texas
Instruments, Jan 2012. . [4] "LM 2679-5.0 (ACTIVE) 5-V Output, 5-A, 96% Efficient Buck
Converter." Texas Instruments, Jan 2012. .
[4]“IEEE Code of Ethics” Retrieved from
http://www.ieee.org/about/corporate/governance/p7-8.html
[5] “Eye Sensor Info” www.ijstr.org