Final year presentation for FYP Engineering Electrical

1. Rachna College of Engineering and Technology
(A CONSTITUENT COLLEGE OF UET)
SUPERVISOR:
ENGR. IRZAM SHAHID
GROUP MEMBERS:
2021-EE-509
2021-EE-520
2021-EE-526

2. “Innovations in IoT-Driven Assistive Technology: Development of a Smart Stick for Enhanced Navigation and Intelligent
Obstacle Detection for the Visually Impaired”
TITLE:
“INNOVATIONS IN AI-DRIVEN ASSISTIVE TECHNOLOGY:
DEVELOPMENT OF A SMART STICK FOR ENHANCED NAVIGATION AND
INTELLIGENT OBSTACLE DETECTION FOR THE VISUALLY IMPAIRED”

3. Design, develop, and test an AI-powered smart stick for visually impaired individuals to enhance navigation,
safety, and independence. The device will include the following features:
•Advanced Obstacle Detection: Utilize ultrasonic sensors to detect obstacles, including overhead hazards, to
ensure safe movement.
•Water Hazard Detection: Integrate a water sensor (LM393) to detect puddles or water bodies, providing alerts
to the user.
•Real-time Object Recognition: Leverage a Pi Camera and YOLO v8 object detection for real-time recognition
of objects and location tracking.
•Voice Assistance: Offer voice-based navigation and alerts to guide users and notify them of any hazards or
changes in the environment.
•Emergency Assistance: Incorporate AI-driven emergency assistance features for quick alerts in case of danger
or disorientation.
•User-friendly Design: Ensure the device is portable, lightweight, and intuitive to operate, improving
independence and mobility for users in outdoor environments.
Objectives

4. “Innovations in IoT-Driven Assistive Technology: Development of a Smart Stick for Enhanced Navigation and Intelligent
Obstacle Detection for the Visually Impaired”
PROGRESS
Hardware Components
• Ultrasonic Sensors (x3):
• Detects objects and obstacles from multiple directions, including overhead hazards.
• Pi Camera:
• Captures real-time images for YOLO v8 processing to recognize objects and assist in navigation.
• Water Sensor (LM393):
• Detects water presence on surfaces and alerts users to avoid potential hazards.
• Microcontroller (Raspberry Pi):
• Processes data from all sensors and the camera for real-time voice alerts and object recognition.
Prototype Development
• Environment-specific measurements collected to optimize functionality.
• Lightweight and portable design to improve mobility and independence for visually impaired users.

5. Features:
• Obstacle Detection: Ultrasonic sensors & water sensor.
• Object Recognition: HD camera with machine learning.
• Speech Recognition
• Dual Modes:
i. Vibration feedback for obstacle detection.
ii. Voice feedback for object recognition.
• IoT-Connectivity: GPS/GSM for live tracking on IoT dashboard.
• Emergency: AI based alert send location via SMS.
• Design: Lightweight, waterproof, adjustable, long battery life, portable.

6. Working Principle
1. Ultrasonic Sensors: Emit sound waves and measure reflection time to
detect object distance.

7. Working Principle
2. Pi Camera with YOLO v8: Captures and processes images for object
classification
• YOLO (You Only Look Once)
v8 is an advanced real-time object
detection algorithm using deep
learning.
• It processes images in a single
pass, making it highly efficient
and fast.

8. Working Principle
3. Water Sensor: Detects water presence using conductivity
• (LM393 Water Sensor) works by
sensing the when water is
detected.
• Adjustable Sensitivity
• Low Power Consumption

9. Working Principle
4. Microcontroller: Integrates all data and triggers alerts accordingly

10. Development Methodology
GPS (TRACK
LOACTION)
GSM(Send alert
message)

11. Project Timeline
Project Proposal and
Approval
Planning and Requirements
Analysis
Research and Design
Prototype
Development
Advanced Feature
Integration
Software Development and
Testing
Refinement and
Optimization
Documentation and
Deployment
Presentation
Preparation Project Presentation
Project Review and
Evaluation
10/9/
24 to
20/9/
24
20/9/
24 to
1/10/
24
1/10/
24 to
15/10
/24
30/10
/24 to
15/11
/24
15/11
/24 to
30/11
/24
1/1/2
5 to
15/1/
25
29/2/
25 to
15/3/
25
15/3/
25 to
25/3/
25
25/3
/25
to
30/3
/25
15/1
0/24
to
30/1
0/24
15/2
/24
to
29/2
/25

12. Thank You!