||Jai Sri Gurudev||
Sri Adichunchanagiri Shikshana Trust ®
SJB INSTITUTE OF TECHNOLOGY
No. 67, BGS Health & Education City, Dr. Vishnuvardhan Road, Kengeri, Bengaluru - 560 060
Approved by AICTE - New Delhi.
An Autonomous Institution, Affiliated to Visvesvaraya Technological University, Belagavi,
Accredited by NAAC A+, Accredited by NBA. Certified by ISO 9001-2015
DEPARTMENT OF COMPUTER SCIENCE & ENGINEERING
“ TECHNICAL SEMINAR – PRESENTATION ”
“Artificial Intelligence in Education”
Under The Guidance of :
Dr. Prakruthi M K
Associate Professor,
Dept. of CSE, SJBIT
Presented by:
Coordinator:
Dr ShanthaKumar H C Nischith HU
Associate Professor, [1JB21CS098]
Dept. of CSE, SJBIT
Technical Seminar
On
Seminar Title:” The Third Eye – An Assistive
Technology for the Blind”
Under The Guidance of : Presented by:
Dr. Prakruthi MK Nischith HU
Associate Professor, [1JB21CS098]
Dept. of CSE, SJBIT
ABSTRACT
This paper presents a detailed review of "The Third Eye," an assistive
technology designed for individuals with visual impairments. The study explores how
artificial vision and machine learning enhance accessibility by enabling real-time object
detection, text recognition, and navigation assistance. Using advanced image
processing techniques, the device translates visual information into auditory feedback,
empowering users in their daily activities. The research further examines the
integration of smart wearable technology, highlighting its potential to improve
independence and quality of life. While demonstrating the effectiveness of this
solution, the paper also addresses key challenges such as hardware limitations,
accuracy concerns, and user adaptability. Ultimately, the findings emphasize the need
for continuous refinement and user-centric innovation to maximize the impact of AI-
driven assistive tools for the visually impaired.
TABLE OF CONTENT
Introduction
Literature Survey
Problem Statement
Methodology
Result and Discussion
Conclusion
INTRODUCTION
Assistive technology is revolutionizing the way individuals
with disabilities interact with their surroundings, and
innovations in this field continue to evolve.
The Third Eye leverages artificial vision and machine
learning to enhance accessibility for visually impaired
users, offering real-time object detection and text
recognition.
Researchers and developers are increasingly focusing on
AI-powered wearable devices that provide auditory
feedback and navigation assistance, helping users gain
greater independence
HISTORY
OF AI
•The origins of AI date back to early attempts to create
machines that mimic human intelligence through logic
and reasoning.
•It started with mythological automatons and early
mechanical inventions, later evolving into theoretical
foundations laid by pioneers like Alan Turing and John
McCarthy.
•Since the 21st century, breakthroughs in machine
learning, neural networks, and big data have propelled
AI to unprecedented levels, reshaping industries and
daily life.
HOW DOES AI WORK?
AI operates by utilizing vast datasets, advanced algorithms, and rapid computing power to
analyze and recognize patterns in information.
It enables machines to simulate human intelligence by learning from experience, making
predictions, and performing complex tasks with minimal human intervention.
Developing AI involves replicating cognitive functions such as problem-solving, decision-
making, and perception, allowing machines to exceed human efficiency in specific domains.
LITERATURE SURVEY
LITERATURE
AUTHOR YEAR SURVEY
TITLE METHOLODOGY DRAWBACK
TAMILARASAN M 1 1 2nd Year 2024 BLIND VISION-USING AI • The system includes a Raspberry • RFID tags cost
M Tech Sri Siddhartha Pi, a Pi camera, and an • No crowd alert
Institute Of Technology, ultrasonic sensor. • Limited environmental adaptation
Tumkur, Karnataka • Object detection is performed • Communication issues
using the YOLO algorithm and
processed through Python's
OpenCV library.
Jagadish K. Mahendran1 2021 Computer Vision-based The Blind Vision system uses • Limited obstacle detection
Daniel T. Barry2 1Kutir Assistance System for the machine learning and computer • Battery life
Technologies Corporation, Visual vision techniques to assist visually • Sensor reliability
Vancouver, BC, Canada Anita impaired individuals. The system
K. Nivedha3 Suchendra M. incorporates a Raspberry Pi, a Pi
Bhandarkar4 camera, and an ultrasonic sensor for
detecting objects and obstacles.
Alexandru Lavric 1 , Cătălin 2024 Acomprehensive Survey • VLCtechnology enhancement for A white cane is extensively used by
Beguni 1,2 and Sebastian- on Emerging Assistive personal assistance VIPs as a detection tool due to
Andrei Avătămănit ,ei 2,3 , Technologies for Visually • AI enhancement for VLC data its affordability, but has its drawbacks
Eduard Zadobrischi 1,2 1 , Impaired Persons communication optimization on sand or snow.
Alin-Mihai Căilean 1,2, • AI for diagnostic systems that
ultimately preserve vision.
Towards a Smart Bionic Eye: 2022 Sanchez-Garcia, Melani • Most visual prostheses are • AI-powered vision systems could
AI-Powered Artificial Vision Beyeler, Michael equipped with an external video misclassify objects or fail in critical
for the Treatment of Incurable processing unit . moments.
Blindness • Classical method relies on • A major challenge is converting
sighted subjects wearing a VR electrode stimulation into a code
head-mounted display (HMD) that the brain can understand.
4
PROBLEM STATEMENT
•Visually impaired individuals struggle with navigation and accessing textual
information.
•Existing assistive technologies are often limited, expensive, or difficult to use.
•A real-time AI-based solution is needed for enhanced accessibility and
independence.
•"The Third Eye" utilizes AI and machine learning for object detection
and text recognition.
•The device provides auditory feedback to assist users in interacting
with their surroundings.
METHODOLOGY
•Data Collection: Gather real-world datasets for object detection, text
recognition, and environmental analysis relevant to visually impaired users.
•Hardware Selection: Utilize sensors, cameras, and microcontrollers to
capture real-time visual data.
•AI Model Development: Implement machine learning models for object
detection, OCR (Optical Character Recognition), and speech synthesis.
•System Integration: Combine AI models with hardware components to
create a seamless, real-time assistive system.
•Testing & Validation: Conduct rigorous testing with visually impaired
users to ensure accuracy, usability, and reliability.
•Deployment & Optimization: Optimize system performance for real-
time processing, low power consumption, and user-friendly operation.
•User Feedback & Iteration: Gather feedback from end users to
improve functionality, accessibility, and overall user experience.
RESULT & DISCUSSION
Title :The Third Eye – An Assistive Technology for the Blind
Abstract Results and discussion
This study explores the integration of artificial The results indicate that AI techniques have
intelligence (AI) in assistive technologies for been widely utilized in the development of
visually impaired individuals. By leveraging smart learning environments. These techniques
primarily focus on algorithms such as
computer vision, natural language processing,
classification, matching, recommendation, and
and deep learning, the system aims to provide deep learning, which are designed to enhance
real-time object detection, text recognition, and teaching and learning processes. Additionally, AI
environmental awareness. The research focuses has been applied in educational settings to
on developing an AI-powered wearable or provide students with personalized feedback,
handheld device that enhances mobility, reasoning, and adaptive learning experiences.
independence, and accessibility for users. Among the reviewed studies, 35 explored the
Testing and validation are conducted to assess implementation of AI techniques for extracting
the accuracy, usability, and effectiveness of the and analyzing student data to improve learning
outcomes.
solution.
CONCLUSION
•AI enhances learning experiences and improves student performance.
•It reduces the burden on educators by automating tasks and providing insights.
•Personalized learning adapts to individual student needs for better engagement.
•AI-powered student analytics help track progress and identify areas for
improvement.
•Intelligent tutoring systems and adaptive learning platforms improve education
quality.
•AI enables real-time feedback, reasoning, and adaptive learning techniques.
REFERENCE
• [1] TAMILARASAN M 1 1 2nd Year M Tech Sri Siddhartha Institute Of Technology, Tumkur, Karnataka “BLIND VISION-
USING AI”
• [2] Jagadish K. Mahendran1 Daniel T. Barry2 1Kutir Technologies Corporation, Vancouver, BC, Canada Anita K. Nivedha3
Suchendra M. Bhandarkar4 “Computer Vision-based Assistance System for the Visuall”
• [3] Alexandru Lavric 1 , Cătălin Beguni 1,2 and Sebastian-Andrei Avătămănit ,ei 2,3 , Eduard Zadobrischi 1,2 1 , Alin-Mihai
Căilean 1,2, “AComprehensive Survey on Emerging Assistive Technologies for Visually Impaired Persons”
• [4] Towards a Smart Bionic Eye: AI-Powered Artificial Vision for the Treatment of Incurable Blindness “Sanchez-Garcia,
Melani Beyeler, Michael”
THANK YOU
