This is the self controlled wheel chair which does not require any human effort.It will move according with pupil.

1. EYE CONTROLLED WHEEL CHAIR
USING RASPBERRY PI
Presented by
Name: D.MANOJ KUMAR
Class: III B.TECH
Reg.no: 141FA05074
Saturday, 22 July 2017
Department of Electronics Communication Engineering
Under The Guidance Of:
Name: Mr S.RAVI SHANKAR Sir.
SEMINAR TOPIC

2. CONTENTS:
 OBJECTIVE
 INTRODUCTION
 BLOCK DIAGRAM
 EXPLANATION
 ADVANTAGES & DISADVANTAGES
 APPLICATIONS
 CONCLUSION
 REFERENCES
Saturday, 22 July 2017Department of Electronics Communication Engineering
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3. OBJECTIVE:
● The world population is increasing faster and at the same
time people with disabilities also increases.
● The purpose of this eye controlled wheelchair is to
eliminate the assistance required for the disabled person .
● This is independent and cost effective wheelchair
system.
Saturday, 22 July 2017Department of Electronics Communication Engineering
SEMINAR TOPIC

4. INTRODUCTION:
Saturday, 22 July 2017Department of Electronics Communication Engineering
SEMINAR TOPIC
Person who are unable to walk and are using wheelchair
exert great amount of energy using physical strength to
turn the wheels.
Currently there are different eye based method will be
use for controlling wheelchair such as EOG, ECG, EEG
based, Eyeball sensing method.
To decide the location of eye pupil depends on voltage
variation. But for different output voltage will be
generates for different user, which gives wrong location of
the eye pupil. So we are introducing a new method.

5. BLOCK DIAGRAM:
Saturday, 22 July 2017Department of Electronics Communication Engineering
SEMINAR TOPIC
RASPBERRY
PI B+
LCD
DISPLAY
L293D DC
MOTOR
DRIVER
POWER
SUPPLY
ULTRASONIC
SENSOR
CAMERA
DC
MOTOR 2
DC
MOTOR 1
EMERGENCY
SWITCH

6. Saturday, 22 July 2017Department of Electronics Communication Engineering
SEMINAR TOPIC

7. HARDWARE DESCRIPTION:
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8. FEATURES OF RASPBERRY PI
Saturday, 22 July 2017Department of Electronics Communication Engineering
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CPU: ARM CORTEX A53 ,1.2GHz
RAM:1Gb
NETWORKING:ETHERNET,WIFI,BLUETOOTH 4.1 CLASSIC.
STORAGE:MICRO SD CARD.
GPIO PINS:40 PINS.
PORTS: HDMI,3.5 mm AUDIO VIDEO JACK,CAMERA SERIAL
INTERFACE,DISPLAY SERIAL INTERFACE,4*USB PORTS(2.0).

9. INTERFACING ULTRASONIC SENSOR.
Saturday, 22 July 2017Department of Electronics Communication Engineering
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10. Saturday, 22 July 2017Department of Electronics Communication Engineering
SEMINAR
Ultrasonic sensor is used to detect obstacle in the path of
wheelchair. Sensor is directly connected to the raspberry pi
board.
It receives the data and measuring the distance between
wheelchair and obstacle. If any obstacle is detected very close
to wheelchair, motors will stop to run the wheels.
 Ultrasonic sensor is a very affordable proximity / distance
sensor that has been used mainly for object avoidance in various
robotics projects.

11. INTERFACING DC MOTOR USING L293D:
Saturday, 22 July 2017Department of Electronics Communication Engineering
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12. SOFTWARE SPECIFICATIONS:
Saturday, 22 July 2017Department of Electronics Communication Engineering
SEMINAR
It also need some operating system namely raspbian
jessy or pixel .
Raspberry pi should contains the following softwares for
image processing….
PYTHON
OPEN CV
 SCILAB
OCTAVE

13. FLOW CHART:

14. WORKING:
Saturday, 22 July 2017Department of Electronics Communication Engineering
SEMINAR
Raspberry pi board is soul of the system, which control the complete
system operation.
Camera is directly connected with raspberry pi board and
continuously captures the images, distance between eye and camera
device is fixed. It may be 10 to 15 cm. Face and eye detected by Haar
cascade algorithm and find out the exact pupil location. This gives the
correct information eye movements.
Image processing based data signal sent to the raspberry pi, raspberry
pi received the data and analyse it and send the control signal to motor
driving circuit, based on the location of eye pupil.

15. Saturday, 22 July 2017Department of Electronics Communication Engineering
SEMINAR
This will decide motor run either in clockwise or
anticlockwise direction or stop. Two individual motors are
fixed on each wheel.
Ultrasonic sensor is mounted on the wheelchair for
obstacle detection.
If sensor gets any obstacle very close to the wheelchair, it
indicates to the raspberry pi and it will sends the signal to
motor driving circuit to stop the motor.

16. CONCLUSION:
Saturday, 22 July 2017Department of Electronics Communication Engineering
SEMINAR
In this project we developed a wheelchair system which enables the
disabled patient to move their wheelchair independently in their own
direction. In the real time application, we can use camera, emergency
switch and ultrasonic sensor depends on their application.
The wheelchair movement operation with some delay time. Dark light
places affect the performance of wheelchair, difficult to track the eye
pupil in dark light.

17. ADVANTAGES:
Saturday, 22 July 2017Department of Electronics Communication Engineering
SEMINAR
By using this system, the disable persons does not need
any human help.
They can save their energy which was wasted for
roatating wheels of normal wheel chair.
It is cost effective.

18. DISADVANTAGES:
Saturday, 22 July 2017Department of Electronics Communication Engineering
SEMINAR
It is useful to move only on the flat surfaces .
The camera may not dectect the eye properly in the
absence of light.

19. Saturday, 22 July 2017Department of Electronics Communication Engineering
SEMINAR
To make the system more interact with patient we need to add some
additional sensors. Delay time may be further reducing to a second.
Operation of system depends on eye movement of totally paralyze
patients. Thus wheelchair moves in all required direction with good
response.
FUTURE SCOPE:

20. Saturday, 22 July 2017Department of Electronics Communication Engineering
SEMINAR
REFERENCES:
1) Sarangi, P., Grassi, V., Kumar, V., Okamoto, J.:‖Integrating Human Input with
autonomous behaviours on an Intelligent Wheelchair Platform‖, Journal of IEEE
Intelligent System, 22, 2, 33-41, [2007].
2) Matt Bailey, ET. Al, ―Development of Vision Based Navigation for a Robotic
Wheelchair‖, in Proceedings of 2007 IEEE 10th International conference on
rehabilitation robotics.
3) Shafi. M, Chung. P. W. H:‖A Hybrid Method for Eyes Detection in Facial Images‖,
International Journal of Electrical, Computer, and Systems Engineering, 231-236,
[2009].
4) Automation of wheelchair using ultrasonic and body kinematics, Preethika Britto,
Indumathi. J, Sudesh Sivarasu, Lazar Mathew, CSIO Chandigarh, INDIA, 19-20 March
2010.