VOICE CONTROLLED WHEEL CHAIR USING · PDF fileVOICE CONTROLLED WHEEL CHAIR USING ARDUINO ... The HM2007 Speech Recognition IC performs speech recognition or voice recognition process

International Journal of Science, Technology & Management www.ijstm.com

Volume No.04, Issue No. 06, June 2015 ISSN (online): 2394-1537

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VOICE CONTROLLED WHEEL CHAIR USING

ARDUINO

Kharka Bahadur Rai1, Jeetendra Thakur

2, Nirmal Rai

3

1,2 Student,

3Asst. Professor, Department of Electronics and Communication Engineering,

Sikkim Manipal Institute of Technology (SMIT), Rangpoo Majhitar, East Sikkim (India)

ABSTRACT

This journals represent the “voice control wheel chair” for the physically handicapped person were the voice

command controls the movements of the wheel chair. Voice Recognition Kit (HM2007 Module) is being used to

recognize the voice command. The voice command given is converted to binary numbers by Voice Recognition

Kit and those binary data is given to the arduino board for the control of the wheel chair. For example when the

user says „forward‟ than chair will move in Forward direction and when he says „Backward‟ than the chair will

move in backward direction and similarly for left, right and stop. We have used LCD display unit to display the

direction in which direction of the wheel chair.

Keyword: Arduino Uno, Hm 2007, Ir Sensor, L293d Ic, Lcd, Motor.

I. INTRODUCTION

The advancement and development of technology has always influenced several aspects of our lives since a very

long time and will continue to do so in the future with more capacity and more unexpected development. In our

project we have tried our best to correlate between the advancement of technology and the human requirement,

for human ease. The main aim of this project is to control wheel chair through human voice. This project is

mainly designed for physically challenged people who are dependent on wheelchairs and especially those

persons who cannot use their hand to drag their wheel chair because of some disability. In this system we have

used voice recognition module to recognize the voice of the user for controlling the direction of the wheelchair.

The prototype of the wheel chair is built using arduino, chosen for its low cost, in addition to its versatility and

performance in mathematical operations and communication with other electronic devices. The system has been

designed and implemented in a cost effective way so that if our project is commercialized the needy users in

developing countries will benefit from it. For voice recognition we have used “HM 2007 MODULE”.

We believe our project will be applicable for some useful operation and provide some advancement in

technology, and most important this may provide some help to the handicap person.



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II. HEADING

2.1 Project Design and Methodlogy

2.2 HM 2007 Module

The HM2007 Speech Recognition IC performs speech recognition or voice recognition process. Voice module

has the 3x3 metrics keypad were it can be used to trains the voice to the module. The module output is in binary

form and it is being interface with the arduino for the motor control. The module has CMOS battery to store the

program in SRAM even if the power failure is occurred. SRAM is also being used in the module to store the

program. The chip provides the options of recognizing either forty .96 second words or twenty 1.92 second

words. This circuit allows the user to choose either the .96 second word length (40 word vocabulary) or the 1.92

second word length (20 word vocabulary). For memory the circuit uses an 8K X 8 static RAM [2].

The 8-bit output data of the module is given to the Arduino board. The arduino will process the 2-bit data (i.e.

two number of pins are used) which is being given by the module and will control the movements of the wheel

chair. Only 2-bits of output data are being used because of the direction of the motor control in four direction.

The program is coded in assembly language in arduino. Addition to this the speed of the wheel chair is also

being controlled by varying the potentiometer and also obstacle detection using IR Sensor. We have also used

display unit to display in which direction the wheel chair is moving (left, right, front and backward).The chip

has two operational modes; manual mode and CPU mode. The CPU mode is designed to allow the chip to work

under a host computer.



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Fig: (1) Diagram of HM 2007 Module.

2.3 Block Diagram

2.4 Block Diagram Description

Using micro phone human voice is converted into electrical signal. The audio signal which is converted to

electrical signal goes to the HM 2007 module to recognize the voice signal which has been train to the module.

The human voice should be train to the voice module at the beginning before we give some command to the

module. When the voice is train to the voice module the voice command is being train with the BCD input from

the matrices keypad of the module, so later when we give some command to the voice module the LCD will

display the appropriate BCD binary input which has been train. HM 2007 Module will produce the binary

output. The output of the module is being interface with the arduino where the arduino will process the output of

the module for the motor direction control. An Infrared (IR) sensor is used to detect obstacles in front of the

wheel chair. IR sensor works by using a specific light sensor to detect a light wavelength in the Infrared

spectrum which is coming back when the obstacles is detected. When the object is close to the sensor, the

transmitter light will bounce back to the receiver sensor, and the object is detected. When the obstacles is

detected the motor will stop. Arduino cannot be directly connected because it cannot give sufficient current to

drive the DC motors. Motor driver is a current enhancing device, it can also be act as switching device. Thus

L239D IC motor driver is inserted between the arduino and the motor. Motor driver take the input signal from

the arduino and generate corresponding output for motor. This motor driver IC can drive two motor

simultaneously.



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2.5 Flowchart

III. IDENTATION AND EQUATION

3.1 Speech Processing Technique

A speech capturing Device: It consists of a microphone, which converts the sound wave signals to electrical

signals and an Analog to Digital Converter which samples and digitizes the analog signals to obtain the discrete

data that the computer can understand.

A Digital Signal Module or a Processor: It performs processing on the raw speech signal like frequency domain

conversion, restoring only the required information etc.

Preprocessed signal storage: The preprocessed speech is stored in the memory to carry out further task of speech

recognition.



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Reference Speech patterns: The computer or the system consists of predefined speech patterns or templates

already stored in the memory, to be used as the reference for matching.

Pattern matching algorithm: The unknown speech signal is compared with the reference speech pattern to

determine the actual words or the pattern of words

3.2 Simulation Process

Arduino Programming

Arduino takes the BCD output from HM2007 module and control the motor movement. Arduino takes two bit

output form HM2007 module and the output coding process is shown below in table (4.1).

Figure (2): Motor Direction Control Program Figure (3): Final Program

IV. FIGURES AND TABLES

4.1 Arduino Coding Concept

DIRECTION

ARDUINO

INPUT (TWO

INPUT)

MOTOR 1 (M1)

(TWO WIRES)

MOTOR 2 (M2)

(TWO WIRES)

DIRECTION OF MOTOR

LEFT 0 0 H L L H M1(Back) & M2(Front)

FRONT 0 1 L H L H M1(Front) & M2(Front)

BACK 1 0 H L H L M1(Back) & M2(Back)

RIGHT 1 1 L H H L M1(Front) & M2(Back)



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4.2 Model Figures

Figure (4): Side View of the Model Figure (5): Back View of the Model

Fig 6: Front View of the Model

V. CONCLUSION

5.1 Advantages

5.1.1 It reduces human efforts.

5.1.2This is helpful to physically handicapped people who could not able to operate home appliances with their

hand.

5.1.3This will help to save energy to some extent, since some people feels lazy to go and switch off the

appliances manually.

5.1.4 It is easy to operate for the people who are tried and does not need to operate the home appliance manually

by hands.

5.1.5 It reduces risk.

5.2. Limitation

5.2.1 It requires extra supply to operate the model.

5.2.2 Only the installed voice is recognized by the module.

5.2.3 The cost of the module is quite higher.

5.3 Application

5.3.1 Command and control of home appliances.



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5.3.2 Telephone assistance system and Data entry

5.3.3 Speech and voice recognition security system (voice password)

5.3.4 Speech controlled appliances and toys.

5.3.5 Speed assisted computers games.

5.3.6 Speech assisted virtual reality.

5.3.7 Speech to speech translation.

This technique can be extend to the efficient use of human efforts. This technique can be used in home

appliance for controlling home appliance by human voice. In further process, it can be used for controlling car

by human voice. With the voice recognition along with arduino human efforts can be eliminated and some

electrical wiring can also be eliminate. With the arduino power saving can also be done.

VI. ACKNOWLEDGEMENT

We are extremely grateful to our project guides, Mr. Nirmal Rai (Assistant Professor, E & C Dept., SMIT) for

insightful suggestions on the project work and for guiding us during the entire project with his encouragement,

support and cooperation. We are also grateful to Prof. (Dr.) R.N. Bera (HOD, E & C Dept., SMIT), Mr.

Dipanjan Bhattacharaya (Assistant Professor, Project Coordinator, E & C Dept., SMIT) for allowing us to

proceed with the project and providing us with the opportunity to embark on the subject, which has given us

invaluable knowledge and experience. We would also like to extend our heart-felt thanks to our family and

friends for their expenditure moral support, love and affection.

Providing the transforming gift of mobility to the physically disabled people.

REFERENCES

[1] Y.Usha Devi 1, II M.Tech, Wireless Home Automation System Using ZigBee, International Journal of

Scientific & Engineering. Research Volume 3, Issue 8, August-2012 ISSN 2229-5518.

[2] Dhawan S. Thakur1 and Aditi Sharma2, Eternal University, Himachal Pradesh, India. (IOSR-JECE) E-

ISSN: 2278-2834, p-ISSN: 22278-8735. Volume 6. Issue 1 (May- June. 2013), PP 65-75.

www.iosrjournals .org.

[3] “Voice Operated Intelligent Wheelchair” by Ms. S. D. Suryawanshi1, Mr. J. S. Chitode2, Ms. S. S.

Pethakar3. International Journal of Advanced Research in Computer Science and Software Engineering.

Volume 3, Issue 5, May 2013.

[4] “Voice Operated Wheel Chair”. By- Jayesh K. Kokate1 (student), A. M. Agarkar2 (Professor), Dept. of

Electronics & Telecommunication, SSGMCE, Shegaon, Maharashtra, India. EISSN: 2319-163, pISSN:

2321-7308.

[5] L.Fehr, W. Edwin Langbein and S.B. Skaar, „Adequacy of Power Wheelchair Control Interface for Person

with Severe Disabilities: A Clinical Survey, J. Rehabil. Res. Develop, 37(3), pp. 353-360, 200.

[6] Yasunari Obuchi, Multiple-Microphone Robust Speech Recognition Using Decoder-Based Channel

Selection, Advanced Research Laboratory, Japan, 2004



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[7] “Voice Operated Wheelchair”, Aakash. A. Hongunit1, Mayauri. Deulkar2, Varsha. Sable3. Prof. Dr. P. B.

Mane. University of Pune, AISSMS Institute of Information Technology. E&C Dept. Volume 4, Issue 4,

April 2014.ISSN: 2277- 128X.

[8] www.alldatasheet.com.

[9] www.alljournalsofHM2007.com.

[10] www.alldatasheetofarduino.aom.

[11] Autonomous Robots 1995, Volume 2, Issue 3, pp. 203-224.

Thanking you all a lot.

Author1: Kharka

Bahadur Rai

Department of Electronics and Communication Engineering, Sikkim Manipal Institute

of Technology, Rangpoo Majhitar, East Sikkim, India Pin no: 737136/ 737132.

Author2: Jeetendra

Thakur

Department of Electronics and Communication Engineering, Sikkim Manipal Institute

of Technology, Rangpoo Majhitar, East Sikkim, India Pin no: 737136/ 737132.

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VOICE CONTROLLED WHEEL CHAIR USING · PDF fileVOICE CONTROLLED WHEEL CHAIR USING ARDUINO ... The HM2007 Speech Recognition IC performs speech recognition or voice recognition process