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An AI-powered wearable smart spectacle system for visually impaired individuals that combines real-time object detection, OCR text recognition, text-to-speech conversion, and emergency SOS alerts using Raspberry Pi and computer vision.
Complete camera module module with full implementation
Complete image processing module module with full implementation
Complete object detection module module with full implementation
Complete ocr module module with full implementation
Complete audio feedback module module with full implementation
Complete emergency sos module module with full implementation
Complete raspberry pi controller module with full implementation
Complete blynk communication module module with full implementation
Complete user interface module module with full implementation
Processor
Raspberry Pi 4 Model B
Camera
Raspberry Pi Camera Module
Audio Output
Earphones / Speaker
Input Device
Push Button (SOS)
Storage
64GB Micro SD Card
Power Supply
5V USB-C Power Adapter / Power Bank
Operating System
Raspberry Pi OS (Linux)
Programming Language
Python 3.x
Object Detection
YOLOv4-Tiny
Computer Vision
OpenCV
Speech Engine
Text-to-Speech (TTS) Engine
IoT Platform
Blynk Platform
To assist visually impaired individuals by providing real-time navigation, object detection, text reading, and emergency assistance.
YOLOv4-Tiny is used for real-time object detection.
It uses EasyOCR or Tesseract OCR to extract text from captured images.
Yes. The extracted information is converted into speech using a Text-to-Speech engine.
Yes. It is suitable for CSE, ECE, AI & ML, IT, EEE, and Biomedical Engineering students.
“As an MCA student, I needed a full-stack project. CodeSelf delivered an excellent web application with proper documentation and live demo.”
Anjali Mehta
MCA, COEP Pune
“Great support and quality projects. The Raspberry Pi project worked perfectly and the documentation was thorough. Highly recommended.”
Vikram Singh
EEE, Delhi Technological University
“The IEEE project I ordered was exactly what I needed. The team helped me understand the implementation and I scored well in my viva.”
Sneha Reddy
CSE, VIT Vellore
“Best project center for engineering students. The MERN stack project I purchased came with clean code, proper documentation, and modifications were done for free.”
Arun Kumar
IT, PSG College of Technology
“I was struggling with my IoT project until I found CodeSelf. The project was delivered instantly and the demo video made it easy to understand.”
Priya Patel
ECE, RV College of Engineering
“Excellent platform for final year projects. Got my AI/ML project with complete documentation and source code. The viva support was really helpful.”
Rahul Sharma
CSE, BMS College of Engineering
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