What Inspired Us We noticed two problems: students struggle to focus during study sessions, and cryptocurrency mining often wastes idle computer time. StudyCoin solves both by rewarding focused studying with cryptocurrency mining.
What We Learned Computer Vision: YOLO object detection and MediaPipe face analysis Full-Stack Development: React frontend with Flask backend Cryptocurrency Integration: XMR mining pools and wallet management Privacy-First AI: Local processing without storing personal data
How We Built It Core Architecture Apply to app.py Key Components AI Study Detection: Real-time analysis using YOLO and MediaPipe Frontend Interface: React with TypeScript and real-time session management Backend API: Flask with Auth0 authentication and Supabase database Mining System: XMR (Monero) mining with configurable CPU usage Technical Stack Frontend: React, TypeScript, Tailwind CSS Backend: Python Flask, Supabase AI/ML: OpenCV, YOLOv8, MediaPipe Mining: XMRig integration
🚧 Challenges We Faced
- Camera Resource Management Problem: Frontend and AI system competing for camera access Solution: Implemented exclusive camera access by releasing frontend camera before AI access
- Real-time AI Performance Problem: AI analysis causing lag and poor user experience Solution: Optimized to analyze every 2 seconds with compressed frames
- Cross-Platform Compatibility Problem: Different camera backends on Windows vs other systems Solution: Implemented multiple camera backends (DirectShow + default)
- User Privacy Concerns Problem: Users concerned about video data being stored Solution: Privacy-first design with local processing and no data storage
Impact & Results Intuitive interface that guides users through study sessions Real-time feedback on focus status and mining progress Privacy-preserving computer vision implementation Educational value in cryptocurrency and AI concepts
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