ACCIDENT PREVENTION USING EYE BLINK DETECTIONPRESENTED BY :TEJASHREE PATILBLDEA CET VIJAYAPURA KARNATAKA

INTRODUCTION: India is facing lot of problems which restricts the

development of the country. One of the problems is Road accidents.

The details of causes for the Road accidents by Government of India is summarized as follows.

Due to Driver (77%) Weather Condition (1%) Vehicle Condition (2%) Pedestrian’s fault (2%) Cyclist’s Fault (1%) Road Condition (2%) Other (14%)

DROWSINESS DETECTION TECHNIQUES Vehicle based measures: deviations from lane position, movement of the steering

wheel, pressure on the acceleration pedal, etc.

Behavioural based measures: the behaviour of the driver, including yawning, eye

closure, eye blinking, head pose, etc.

 Physiological based measures: pulse rate, heart beat and brain information.

DROWSINESS DETECTION USING IR SENSORS

WORKING It is one of the behavioural techniques and it involves

measure and control of the eye blink using IR sensor. The IR transmitter is used to transmit the infrared rays in

to our eyes. The IR receiver is used to receive the reflected infrared

rays from our eyes. If the eyes are closed it means the output of IR receiver is

high otherwise the IR receiver output is low. This is to know closing or opening position of the eyes. This output is given to logic circuit to indicate the final

output i.e. alarm.

MODULES Eye blink sensor module :

• IR transmitter and receiver both of which should be kept in a straight line.• IR receiver is connected to non-inverting input terminal of the comparator

which is made up of opamp.Reference voltage is given to inverting input terminal of comparator.

• When interrupt the IR rays between the IR transmitter and receiver, the IR receiver is not conducting and hence the non-inverting input terminal will be high.

• The comparator output is in the range of +5V.• This voltage is given to microcontroller or PC.• Based on which the alarm will buzz.

Auto upper-dipper module: It consists of LDR and opamp , whose two inputs are in

terms of voltages . Two 10K registers are used , which acts as voltage

divider .Each giving rise to 2.5V.this voltage is the threshold voltage and given to one of the input terminal of opamp.

When light falls on LDR, its resistance reduces and gives the corresponding output in terms of voltage. If this voltage increases above the threshold voltage then it activates the Op-amp.

This output is given to transistor which acts as closed switch and causes the dipper LED to glow which is a indication of danger.

Distance sensor module: Here, we have used six sensors which are installed on

the front bumper. These sensors are connected to port 2 . If any of the sensor senses the intruders and if the o/p

of any one of the sensor goes high it activates the corresponding pin of port 2 and makes the pin high.

The microcontroller makes the pin no 2.7 high which acts as an output.

It is connected to the brake of car , which apply the brake and stops the car.

Drowsiness detection using web camera

working

This approach analyses the images captured by camera to detect physical changes of drivers, such as eyelid movement, using MATLAB Software. The major challenges of the proposed technique include (a) developing a real time system (b) Face detection (c) Iris detection under various conditions like driver position,

with/without spectacles, lighting, etc (d) Blink detection (e) Economy.

System flowchart:

modules Video acquisition: Video acquisition mainly involves obtaining

the live video feed of the automobile driver. Video acquisition is achieved, by making use of a web camera. Dividing into frames and eye detection: This module is used

to take live video as its input and convert it into a series of frames/

images, which are then processed. • Video acquired is first divided into number of frames.• From each frame the region of interest i.e eye is extracted based

of image processing technique.• If the eyes are closed in alternative frames then we can conclude

that it is due to “normal eye blinking”.• If the eyes are closed in continuous frames then we can conclude

that “the driver is drowsy”.

Eye blinking : • The main feature for drowsiness detection is eye blinking. The normal eye blinking rate is vary from 12-19 per minute.• The frequency less than this normal range indicates the drowsy condition of a person/driver. • Here we consider all the possibilities of an eye. Eye may be fully open , fully closed and partially open/closed. • Instead of calculating blinking rate, we calculate average drowsiness. For eye blinking, detected eye is equated with zero, which indicates closed eye. Whereas non zero value is considered as fully open /partially open eye. Drowsiness Detection:

The average drowsiness is calculated based on blinking rate as follows: %d = No of closed eye found X 100 No of frames Where d: drowsiness

Applications The prime purpose is to provide safety measures. It can be used in wireless technology. The eye blink module of this project can be separately used

for RFID detection in industries. Focus on the driver, which is a direct way of detecting the

drowsiness A real-time system that detects face,iris, blink, and driver

drowsiness A completely non-intrusive system

LIMITATIONS The system fails, if the automobile driver is wearing

any kind of sunglasses. The system does not function if there is light falling directly on the camera. IR sensors are costly. 

CONCLUSION This presentation consist of different applications combined together to fulfill the safety precautions. This application to provide the prevention of accident due to drowsiness of the driver and disturbing intruders. We have made the vehicle and driver secure against such severe problems. It tries to look at the emerging technologies and determine the best approaches in trying to prevent the number one cause of fatal vehicle crashes. The primary goal of this topic is to develop a real time

drowsiness monitoring system in automobiles. The proposed system detects eye blinks with 99% accuracy and a 1%

false positive rate.