Christo Ananth, Stalin Jacob, Jenifer Darling Rosita, MS Muthuraman, T Ananth Kumar, “Low Cost Visual Support System for Challenged People”, 2022 International Conference on Smart Technologies and Systems for Next Generation Computing (ICSTSN), 978-1-6654-2111-9/22, IEEE, 10.1109/ICSTSN53084.2022.9761312, March 2022,pp. 1-4. Description: Christo Ananth et al. emphasized that people who are visually impaired have a hard time navigating their surroundings, recognizing objects, and avoiding hazards on their own since they do not know what is going on in their immediate surroundings. We have devised a new method of delivering assistance to people who are blind in their quest to improve their vision. An affordable, compact, and easy-to-use Raspberry Pi 3 Model B+ was chosen to demonstrate how the proposed prototype works. All of this is made possible by a camera and sensors and the most modern image processing algorithmic methods available. A camera and ultrasonic sensors are utilized to measure the distance between the user and the object. Using a global positioning system (GPS), it is also possible to track down people who are blind or have impaired vision (GPS). Consider the possibility of making this a for-profit product. Small and light, it may be fitted to a regular pair of spectacles without incurring additional fees or posing any further difficulties.

1. Low Cost Visual Support System for Challenged
People
Christo Ananth
Department of Natural and Exact
Sciences, Samarkand State University,
Uzbekistan
dr.christoananth@gmail.com
M.S.Muthuraman
Professor
Department of Mathematics,
PSNA College of Engineering and
Technology, India
muthu.raman95@gmail.com
Stalin Jacob
Senior Lecturer,
Botho University,
Botswana
stalin.jacob@gmail.com
T. Ananth kumar
Assistant Professor
Computer Science and Engineering
IFET College of Engineering
India
ananth.eec@gmail.com
Jenifer Darling Rosita
Senior Lecturer,
New Era College,
Botswana
jeni.balan@gmail.com
Abstract—People who are visually impaired have a hard
time navigating their surroundings, recognizing objects, and
avoiding hazards on their own since they do not know what is
going on in their immediate surroundings. We have devised a
new method of delivering assistance to people who are blind in
their quest to improve their vision. An affordable, compact,
and easy-to-use Raspberry Pi 3 Model B+ was chosen to
demonstrate how the proposed prototype works. All of this is
made possible by a camera and sensors and the most modern
image processing algorithmic methods available. A camera and
ultrasonic sensors are utilized to measure the distance between
the user and the object. Using a global positioning system
(GPS), it is also possible to track down people who are blind or
have impaired vision (GPS). Consider the possibility of making
this a for-profit product. Small and light, it may be fitted to a
regular pair of spectacles without incurring additional fees or
posing any further difficulties.
Keywords—Artificial Intelligence, GPS, Internet of Things,
Raspberry Pi 3 Model B+
I. INTRODUCTION
Embedded microprocessor systems are nothing more
than computer chips integrated into various products such as
lighting systems, home appliances, industrial equipment, and
other similar items[1]. Microprocessors are embedded in
security devices such as anti-lock braking systems, widely
used in automobiles, and considered real-time systems[2]. A
few examples of its significance are:
• handling a large number of functions, such as
calculations and word processing, at higher speeds.
• operations for repetitive, continuous, progressive,
and sequential functions without requiring human labour.
• handling many other functions.
Using the internet, telephones, and other interfacing
devices to communicate with others. The microprocessor has
a limit on the amount of data it can handle. The vast majority
of microprocessors are incapable of performing floating-
point operations[3]. The most significant disadvantage is that
it overheats physically. Neither it nor the other external
devices should be able to communicate with each other. To
support its operations, the microprocessor does not have any
internal peripherals, such as ROM, RAM, or other I/O
devices.
II. LITERATURE SURVEY
An ultrasonic walking guide in [4] uses three ultrasonic
sensors to view an obstacle from three different perspectives:
the front, the left, and the right. When the guide knows
where the obstacle is coming from, he or she is more
effective. A convolutional neural network and an additional
ultrasonic sensor are part of the system's pothole detection
capabilities (CNN)[5]. Drivers can see what is happening on
the road's surface thanks to the use of an embedded
controller. Image training on a host computer precedes real-
time classification on an embedded controller in the process
of real-time classification[6]. It also uses a CNN to make a
real-time decision on an image. For this reason, no alerts will
be triggered. For the time being, the system can only locate
and classify obstacles based on their physical location[7],
which makes it a little challenging to navigate around. One
of the components of the system described in [8] is an RGB-
D camera, processing unit, and wearable device. They
collaborate to assist people in avoiding obstacles in an
unfamiliar indoor environment. The system's most important
component is an RGB-D camera that captures color and
dense depth images of an environment[9]. Additionally, a
wearable fabric-based device can communicate navigational
information at the arm level to avoid detected obstacles, and
this device processes images and performs all the necessary
calculations for obstacle avoidance. It does not distinguish
between obstacles that are standing still and those that are
moving when using it. It was impossible to guarantee
everyone's safety as they walked due to a large number of
people]10.
People who are visually impaired already have a section
dedicated to teaching them how to use electronic devices. A
visual navigation system based on a USB camera has been
considered, as has a system that detects obstacles using
ultrasonic sensors. Both of these systems have been
considered[11]. An audible beep is used to notify the user of
obstacles that are up to 300 centimeters away from them in
the proposed system. It's also critical to record the user's field
of view with an attached USB webcam for various reasons,
including determining the properties of an obstacle and, in
2022
International
Conference
on
Smart
Technologies
and
Systems
for
Next
Generation
Computing
(ICSTSN)
|
978-1-6654-2111-9/22/$31.00
©2022
IEEE
|
DOI:
10.1109/ICSTSN53084.2022.9761312
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2. this case, locating a person[12]. Blind people are more likely
to use these devices because they are small, inexpensive, and
simple to operate. Because a blind person cannot see the
screen or the buttons that operate the device, it must be
simple to operate. System: It is used as a processing unit in
this system, the eBox 2300TM. The processors in this
embedded system make use of the ETA algorithm. This
single app is in charge of everything that assists a person in
locating their way in the world. In this instance, a low-cost
embedded computer system with an X86 processor is used,
and the eBox 2300TM is the system in question. Aside from
its small size and low price, it also has a built-in system to
function.
From the survey, It shows that the previous technologies
are uable to perform the following tasks at this time:
o Using the device and comprehending the audio
feedback takes a great deal of time and effort to master.
o It does not provide any information about the object
in front them such as the name of the object and does not
give accurate measurement.
o It is not a hands-free device we have to carry the
device so; it makes the user to feel uncomfortable.
III. PROPOSED SYSTEM
Fig. 1. Object Detection Mechanism Through RCNN Algorithm
The Raspberry Pi 3Model B+ is connected to the rest of
the system through various interfaces. There are two
methods for obtaining information. In this experiment, the
Raspberry Pi camera module V2 collected a large amount of
data in the colors red, green, and blue (RGB). This module is
equipped with an 8-megapixel Sony IMX219 sensor of
exceptional quality. A company has created the camera
sensor, which has a fixed-focus lens and is used in the
device. The following pieces of hardware are required: a
Raspberry Pi 3Model B+ and a module that contains a
camera and ultrasonic sensors. The Raspberry Pi was
specifically designed to fit on it. Static images can be
captured at a resolution of 3280 pixels by 2464 pixels using a
digital camera. It can also record videos in various
resolutions, including 1080p, 720p, and 640 pixels by 480
pixels. It is connected to the Pi module through small
sockets, and it communicates with the camera via a serial
interface unique to the Pi module. We use a computer
program that can get the RGB data in real-time and figure
out what is in every video frame that the system is already
aware of by analyzing the data.
Modern CCD/CMOS sensor technology has enabled
high-sensitivity cameras with fast image acquisition and
exceptional performance. The camera also makes a research-
grade USB microscopy camera series that takes crisp images
in low light. An ultrasonic sensor measures distance using
sound waves. Transducers send and receive ultrasonic waves
where pulses tell the sensor about the nearby object. Sounds
reverberate off walls and other objects, forming unique
Ultrasonic sensors that work by emitting a high-frequency
sound wave. Infrared sensors have ultrasonic transducers.
GPS uses a satellite network to send data via radio waves.
The receivers use satellite data to locate objects on Earth.
Because its three components work together, the GPS is
accurate and reliable. Distances to known points are used to
calculate the "Trilateration Principle." Inputs on the GPS
receiver board are RS232 for PC or embedded systems. It
includes everything from the GPS antenna to the serial data
output. A GPS Modem's output can be NMEA or Binary.
To work, a power supply needs an electric load. It can
also convert solar, mechanical, or chemical energy into
electrical energy. Uninterruptible power supply The term
usually refers to powered devices. The back of a computer
case usually has fans and a power supply. They usually
convert AC to DC and are at the back. Also called a "power
brick" or "power unit." The game requires Flash. During
software debugging, RAM memory allows rapid code
changes. Extra pins on bonded-out chips let you program the
microcontroller in real-time, control program flow, and
access on-chip registers and memory. This circuit uses AC to
DC. The line filter also has a step down transformer.
Transforms 230 VAC to 15 VAC. This AC voltage is bridge
rectified. The bridge rectifier's output is DC with small AC
ripples. Shunt capacitor 1000uF filters AC ripple. The shunt
capacitor output is pure DC because it grounds the AC signal
and blocks the DC. It can move freely because the
transformer's primary voltage affects it. And so on. A series
voltage regulator stabilises the voltage. Finally, a 10uF shunt
capacitor filters out SCR noise. This is a +5V power supply
for digital electronics. Small, low-cost wall transformers with
variable output voltage are common. To use these
transformers in a digital circuit, they must be voltage
regulated. They're easy to get. This circuit solves the
problem. So it is. +5V at 150 mA. This regulator chip is 1 A
cooled. Protection against overheating and wire/plug shorts.
Multiple object detection and identification in a single
image is still a work in progress. TensorFlow is an open
source object detection framework. TensorFlow Object
Detecti Keras. The Python API uses TensorFlow. Keras is an
API. A simple Keras neural network model. It can also run
deep learning algorithms. Making a neural network model
with code is simple. Keras has a good one. Backends for
Keras include Tensorflow, Theano, and CNTK. It is modular
and has pre-trained deep learning weights. Using Python is
easy (read/write) and fast on the Raspberry Pi. That's what
the Raspberry Pi 3B+ uses. Python 3 is good for AI, ML, and
data science. With a rich toolkit and libraries. It speaks
English and others. Linux and Windows help. "Format
synthesis" is used in eSpeak Small packages can contain
multiple languages. Larger synthesisers based on real-life
recordings produce more natural and smoother speech.
An IDE helps programmers write code. One of the most
important features of an IDE is the debugger. Only one
programming language, processor, or hardware can be
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3. supported. Most IDEs support multiple languages,
processors, etc. For embedded systems, people use gcc,
Eclipse, and Delphi. Unrestricted access to the source code
of embedded systems. App or part of a larger development
environment (e.g. IDE). Syntax highlighting and
autocomplete are two features that help speed up code
writing. These things aid coding. A compiler reads source
code and converts it to machine-readable form (object code).
It can be a programme (like a linker) or a text file that
humans can read. The compiler decodes high-level code
(e.g., assembly language or machine language). Most often,
it's to translate source code. They want to write a programme
for a computer. Their code can run on multiple platforms.
This is because the compiler is always on a different
machine.
It is a programme that combines objects created by a
compiler into one programme or library. It must combine all
object files created during compilation before creating a file
that can be loaded into the target ROM. ld is a widely used
embedded linker (GNU). A debugger is used to debug other
programmes. A debugger is a PC programme. It must be
tightly coupled to your emulator to work. To control the
emulator from a PC, you need a Debugger. When fixing code
and testing your app, be cautious. Each tool has its own
development and debugging options. It looks at emulators
and simulators. Simulators try to emulate the
microcontroller. A few simulate the entire system
(simulation of peripherals outside of the microcontroller). No
simulator exists that can show a microcontroller in real-time,
regardless of PC speed. Simulator waveforms for each
microcontroller pin take time to create "stimulus" files.
Simulating functions that rely on other components is
difficult. Simulators are ideal for testing microcontroller
algorithms. Basically, it's a piece of hardware that imitates a
microcontroller chip. It can help you diagnose computer
issues. Microcontroller "emulator" in real-time. The ROM of
a microcontroller can only be written once (OTP). So an
emulator's programme memory is static RAM. Firmware can
only be reprogrammed 100-1000 times. That is, use external
RAM instead of the micro's own RAM.
IV. SIMULATION RESULTS
It looks for a rectangular box whenever attempting to
identify an object on the screen. To meet the needs of the
user, the dimensions of the rectangular box (width w and
height h) and the coordinates of the rectangular box (x0 and
y0) can be customised. Using feature vectors to specify the
width w and height h of a bounding box results in variable
bounding box sizes depending on the camera's distance from
the object under consideration. The distance between an
object and a user is determined by the amount of light that
passes through the camera's lens.
TABLE I. DISTANCE MEASUREMENT BETWEEN OBJECT AND USER
Test
Cases Actual distance (in cm)
Ultrasonic
Sensor
distance
(in cm)
Camera
distance
(in cm)
1 30.5 30.2 31
2 15.6 15.6 17
3 23.3 23.2 23
4 43.5 43.2 42
5 0.8 1.0 1
6 12.3 12.1 12
Equation (1) shows that the distance between the camera lens
and the subject is calculated in inches with the help of the
width (w) and the height (h). Equation (2) shows that the
distance between two points is calculated in centimetres by
an ultrasonic sensor with the help of the pulse duration and
sound speed. An ultrasonic sensor can measure a moving
object and a visually impaired person at different distances
because of its real-time response time. The distance between
an object and a blind user is done with a measuring tape to
compare the relative distances between the two objects. The
camera's response time improves as a result of the increased
processing power and frames per second available to it. The
fact that ultrasonic sensors and cameras have longer
processing times slightly than conventional sensors and
cameras does not preclude the generation of this type of
feedback by both devices simultaneously. The location
tracking is achieved by GPS and the results are shown in the
IOT website URL=http://vehicleiot.in/getload.php
Fig. 2. Hardware of the proposed system
Fig. 3. Location Tracking Website
Fig. 4. Location of the User with Latitude and Longitude
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4. TABLE II. PERFORMANCE RATIO OF SINGLE WITH MULTIPLE OBJECT
DETECTION
Test
Cases
Actual Object(s) Predicted Object(s)
Failure
Case(s)
1
Person Person None
2 Mouse Mouse None
3 Person Person None
4 Notebook Notebook None
5 Cellphone Cellphone None
6
Person,Chair,Mouse Person,Chair,M
ouse
None
7
Notebook,Person Notebook,Perso
n
None
8
Cellphone,Notebook Cellphone,Note
book
Laptop
9
Pen,Mouse,Keyboard Pen,Mouse,Key
board
None
10 Bottle,Backpack Bottle,Backpack None
11
Cup,Chair,Knife Cup,Chair,Knif
e
None
12 Laptop,Bed,Cup Laptop,Bed,Cup Bed
131
Bicycle,Person,Chair Bicycle,Person,
Chair
None
4
Tree,Car,Motorbike Tree,Car,Motor
bike
None
Table II shows that the system is nearly perfect in its
ability to identify single items and has no failures, which is a
good summary. This system can distinguish between
multiple known objects in a frame even when there are
multiple known objects in the frame. If the user's location is
within 15–20 meters of the object recognition system, object
recognition accuracy can be as high as 98 percent. When
identifying objects, the camera uses the values from the
ground truth.
V. CONCLUSION
The ability to navigate, recognize objects, and avoid
obstacles are difficult tasks for blind people to complete on
their own, even though they cannot see anything around
them. This paper demonstrates how to design and build a
new visual aid system for entirely deaf or blind people from
the beginning. The Raspberry Pi 3 Model B+ has been used
to demonstrate the proposed prototype's functionality and
design to demonstrate how it works. This is because it is
inexpensive, compact, and simple to use. It is equipped with
a camera and sensors that aid in the avoidance of obstacles
and high-tech image processing algorithms that aid in the
detection and tracking of various objects. The camera and
ultrasonic sensors are used to determine how far the user is
from the object. The GPS system is also used to track down
people who are blind or have limited vision. The product, if
developed, could be light and portable and easily attached to
any regular pair of eyeglasses without adding any additional
cost or complexity, allowing it to be commercially
successful.
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