Project Milestones
A comprehensive timeline showcasing our journey from initial research to final deployment — 12 months of innovation, development, and refinement.
Development Timeline
From conception to completion, every milestone achieved
Phase 1: Research & Planning
Months 1-2
- Literature review and competitive analysis
- User research and requirements gathering
- Technology stack selection (Python, Java, OpenCV, TensorFlow)
- Project planning and resource allocation
Phase 2: Prototype Development
Months 3-5
- Hardware integration and setup (cameras, sensors)
- Core vision module development with OpenCV
- AI model training (InsightFace, YOLO, EasyOCR)
- Initial prototype assembly and testing
Phase 3: Feature Implementation
Months 6-8
- Face recognition system (Port 5000)
- Obstacle detection with ultrasonic sensors (Port 5001)
- OCR and text reading module (Port 5002)
- Voice command interface and haptic feedback
Phase 4: Testing & Refinement
Months 9-10
- User acceptance testing with visually impaired users
- Performance optimization and edge computing
- Bug fixes and system refinements
- Accessibility compliance verification
Phase 5: Deployment & Documentation
Months 11-12
- Final prototype finalization and packaging
- Comprehensive technical documentation
- User manual and setup guides creation
- Project presentation and commercialization planning
Key Deliverables
Six major outcomes from our development journey
Working Prototype
Fully functional smart glasses with all features integrated and tested
AI Models
Trained and optimized ML models for face recognition, OCR, and object detection
Mobile App
Android application with voice commands, sensor control, and real-time feedback
Server Backend
Three Flask services running on ports 5000, 5001, and 5002 for AI processing
Documentation
Comprehensive technical documentation, user guides, and API references
Presentation
Project presentation materials and detailed commercialization strategy
Technology Integration Timeline
How we built and deployed our tech stack
Phase 1-2: Foundation
Setup Python environment, Android SDK, hardware integration with Raspberry Pi and camera modules
Phase 3: Core Services
Deploy Face Recognition (Port 5000), Ultrasonic Sensor (Port 5001), OCR Service (Port 5002) with Flask servers
Phase 4-5: Optimization
Performance tuning, edge computing optimization, user testing, and final production deployment
Project Successfully Completed
All milestones achieved on schedule. The Blind Assistant platform is now ready for deployment and real-world testing.