Processing & Properties of Floor and Wall Tiles.pptx
Project PPT BLINDMAN FINAL.pptx
1. NATIONAL INSTITUTE OF TECHNOLOGY, AGARTALA
ELECTRONICS AND COMMUNICATION ENGINEERING
16 NOV, 2022
Project Presentation on
BLINDMAN OBSTACLE DETECTOR
Presented By-
1. Apangshu Debnath(19UEC014)
2. Arijit Pal(19UEC039)
3. Juliyas Reang(19UEC085)
Under the guidance of-
Dr. Tamasi Moyra Panua
(Assistant Professor &
H.O.D, ECE)
2. CONTENTS
• INTRODUCTION
• PROPOSED SOLUTION
• COMPONENT'S
I. ARDUINO NANO
II. ULTRASONIC SENSOR
III. BUZZER
IV. JUMPER WIRES
V. BATTERY
• CIRCUIT DIAGRAM
• PROCEDURE
• FLOWCHART
• CODE
• RESULTS AND DISCUSSION
• FUTURE SCOPE OF STUDY
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3. Introduction
• Vision is the most important part of human physiology as
83% of information human being gets from the
environment is via sight.
• From the statistical survey of WHO, millions of people are
blind in this world so it’s quite unfortunate situation for
them.
• Visually impaired people find difficulties in their daily life
by facing obstacles in front of them. For example- Walking
in the street, crossing the road etc.
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4. Proposed Solution
• Now to overcome this problem, we have proposed a solution to use a smart blind stick with cheaper and
more effective obstacle detection within a given range.
• We have used Arduino nano along with Arduino IDE software.
• Here the use of ultrasonic sensor plays a vital role in object detection within a certain range.
• As soon as an object is detected a buzzer sound is given to the user as an indication and hence they can
know an obstacle in front of them.
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6. Arduino Nano
• The Arduino Nano is a small, complete, and breadboard-friendly board based on the ATmega328P released in 2008. It
offers the same connectivity and specs of the Arduino Uno board in a smaller form factor.
• The Arduino Nano is equipped with 30 male I/O headers, in a DIP-30-like configuration, which can be programmed using
the Arduino Software integrated development environment (IDE), which is common to all Arduino boards and running
both online and offline. The board can be powered through a type-B mini-USB cable or from a 9 V battery.
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FIG:- Arduino Nano
7. Ultrasonic Sensor
• An ultrasonic sensor is an electronic device that measures the distance of a target object by emitting ultrasonic sound waves, and
converts the reflected sound into an electrical signal. Ultrasonic waves travel faster than the speed of audible sound (i.e. the
sound that humans can hear).
• Ultrasonic sensors have two main components: the transmitter (which emits the sound using piezoelectric crystals) and the
receiver (which encounters the sound after it has travelled to and from the target).
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Fig.: Ultrasonic sensor
8. Buzzer
• A small buzzer is a common feature in electronic products and can provide an effective way of interacting with users or
raising an alarm.
• Depending on the type and strength of the signals available to drive the buzzer, the physical space available, and the
required audio sound pressure level (spl), a magnetic or piezoelectric type will be the most common options for an
application.
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Fig.: Buzzer
9. Jumper Wires
• A jump wire (also known as jumper, jumper wire, DuPont wire) is an electrical wire, or group of them in a cable, with a
connector or pin at each end (or sometimes without them – simply "tinned"), which is normally used to interconnect the
components of a breadboard or other prototype or test circuit, internally or with other equipment or components,
without soldering.
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Fig.: Jumper wires
10. Battery
• The nine-volt battery, or 9-volt battery, is an electric battery that supplies a nominal voltage of 9 volts. Actual voltage
measures 7.2 to 9.6 volts, depending on battery chemistry. Batteries of various sizes and capacities are manufactured; a
very common size is known as PP3, introduced for early transistor radios.
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Fig.: A 9V battery with a battery clip
12. Procedure
1. Take the ultrasonic sensor and the Arduino nano and make the following connections with the help of jumper wires-
i. Connect the Vcc of the ultrasonic sensor with the 5V supply of the Arduino nano.
ii. Connect the trigger pin with the D3 of the Arduino.
iii. Connect the echo pin with the D2 of the Arduino.
iv. Connect the ground pin of the sensor with the ground of Arduino.
2. Take the positive terminal of the 9V battery and connect it to the Vin of the Arduino.
3. Take the negative terminal of the 9V battery and connect it to the other ground of arduino.
4. Take the positive of the Buzzer and connect it to the D5 of arduino.
5. Take the negative of the buzzer and connect it to the ground of Arduino nano. Since there are only two grounds and both of
them are already connected. Take the ground pin of the ultrasonic sensor, the negative of buzzer and a jumper wire and apply
wielding. After that connect the other end of the jumper wire with the ground of the Arduino.
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15. Results and discussion
• For obstacle detection, the system was experimented on in our home and also on the roadside. The project was made with
the working hardware model, detecting the obstacles if come across any obstacles.
• The blind stick proposed model can aid the virtually impaired user by helping him/her navigate through different terrains
and obstacles. The advantages are that it is low cost, has fast response, low power consumption, is lightweight, and ability
to receive feedback through buzzer audio.
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16. Results and discussion
• Detecting the obstacle with the help of Ultrasonic sensors can provide notification to the user holding it in the sound
form via Arduino buzzer and facilitate easier communication in case of emergency.
• The result was found that ultrasonic sensors were able to detect obstacles accurately, and the measured distance to the
obstacles was also approximately correct.
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D in cm (distance) S (alert signal)
0 Buzzer off
70 Buzzer on
70 and above Buzzer off
17. FUTURE SCOPE OF STUDY
• There is some future scope to fulfill the requirement of the smart stick.
• The obstacle detection capability of this project can be increased by introducing the ultrasonic sensor which has better
accuracy and precision angle width.
• We can introduce a GPS to find the exact location of the person.
• By implementing a voice recognition system we can improve the accuracy of the project and alert the person about the
obstacle.
• We can also use AI and ML with Rasberry Pi to detect the object and alert the person accordingly
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