An AI-powered, sensor-integrated wearable device for obstacle detection, text recognition, navigation, and real-time assistance—built to empower visually impaired individuals with safe, independent mobility.
GuardianEye is a multi-sensory smart eyewear system designed to assist visually impaired individuals in navigating their surroundings confidently and independently. By combining advanced AI, computer vision, and sensor fusion, the device offers:
- Real-time obstacle detection
- Currency note recognition
- Printed text reading via OCR
- Multi-language voice feedback
- Location tracking for caregivers
- Hands-free voice command control
- Emergency alert system with haptic and audio feedback
| Feature | Description |
|---|---|
| 🛣️ Real-Time Obstacle Detection | Detects and classifies static/dynamic obstacles using LiDAR + YOLO |
| 💬 Multi-Language Voice Output | NLP-based output in multiple languages for localized interaction |
| 📷 Optical Character Recognition (OCR) | Reads text from newspapers, signboards, etc., and converts to speech |
| 🎙️ Voice Command System | Microphone-powered hands-free interaction via natural language |
| 💸 Currency Note Detection | Identifies denomination using computer vision to prevent fraud |
| 🧭 GPS Location Tracking | Enables family members to track user’s location remotely |
| 🤖 Person & Object Recognition | Recognizes known individuals and frequently seen objects |
| 📳 Haptic Feedback | Vibrates for obstacle alerts, turns, or important environmental cues |
| 🚨 Emergency Beep Alert | Loud beeping sound triggers when immediate danger is detected |
- 🧠 AI Models: YOLOv8 (Object Detection), Tesseract (OCR), NLP (Speech-to-Text / Text-to-Speech)
- 🌐 Communication: Bluetooth Low Energy (BLE)
- 🔊 Audio Feedback: Bone conduction speakers
- 📷 Sensors: LiDAR, Pi camera, GPS
- 📦 Hardware Platform: Microcontroller (Raspberry Pi), Rechargeable battery, Microphone
- Navigate urban streets, stairs, and corridors
- Recognize people at work or home
- Read public signs or packaging labels
- Detect currency during monetary exchange
- Alert surroundings in case of emergencies
- Stay connected with caregivers for safety
Coming Soon: Demo Video
- ✅ Real-time object detection
- ✅ Text-to-speech conversion of printed material
- ✅ GPS tracking dashboard for caregivers
- ✅ Voice-command feature demo
- Research and literature review
- Hardware component selection
- AI module prototyping (YOLO + OCR)
- NLP-based multi-language system
- Integration & Testing
- Real-world trials with visually impaired users
- Final production and optimization
- Anirudh Garg – Computer vision(Team Lead)
- Aaradhya Sharma – Computer vision
- Abhiroop Singh – IoT
- Rajveer Singh – Speech Processing, Documentation
- Bhavneet Kaur – NLP, Speech Processing
This project is licensed under the MIT License.
Have feedback, ideas, or want to collaborate? Reach out at:
"Let’s build a world where everyone can see possibilities—even without sight." 🌍