AI-Powered-Government-Bank-Queue-Management

AI-Powered Bank Queue: Skip the Wait, Not the Service.

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Inspiration

Long queues at SBI/Punjab National Bank branches. Saw people wasting 2-3 hours for basic services like passbook updates. Wanted to bring digital transformation to government banking.

What it does

  • Reduces wait time by 40-60% using AI predictions
  • Real-time queue management with token system
  • OTP-based secure authentication
  • Smart appointment scheduling
  • Live wait time updates

How we built it

  • Backend:Flask + SQLite + Python
  • Frontend:Bootstrap + Vanilla JS
  • AI: Custom algorithm simulating IBM Granite models
  • Auth: OTP-based mobile verification
  • Database: SQLite with appointments, users, banks tables

Challenges we ran into

  • Date format errors between frontend-backend
  • Dynamic element click events not working
  • OTP verification timing issues
  • Database schema design for appointment conflicts
  • Realistic wait time prediction algorithm

Accomplishments we're proud of

  • 5-step booking workflow that actually works
  • Functional AI recommendations without real API
  • Clean responsive UI that works on mobile
  • Complete OTP authentication system
  • Admin dashboard with real analytics

What we learned

  • Queue theory mathematics (Little's Law)
  • Time-series prediction models
  • Frontend-backend integration challenges
  • SQLite database optimization
  • User experience design for non-tech users

What's next

  • Integrate actual IBM Watsonx AI APIs
  • Mobile app with push notifications
  • Live branch crowd tracking via GPS
  • Blockchain for transparent queue management
  • Multi-language support (Hindi + Regional)
  • Integration with existing bank systems
  • Voice assistant for elderly users
  • Predictive staff allocation analytics
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