Skip to content
Raja Varma
Smart CityArtificial IntelligenceWeb DevelopmentLive

MetroMind – Smart City Digital Twin

MetroMind is a smart-city management platform that brings traffic prediction, live analytics, and a digital-twin view of city infrastructure into one interactive dashboard.

Problem Statement

City administrators and planners often lack a unified, real-time view of urban infrastructure - traffic flow, congestion patterns, and infrastructure health are tracked in silos, making it hard to anticipate problems before they cause disruption.

Proposed Solution

MetroMind combines a digital-twin visualization of city infrastructure with AI-driven traffic prediction and live analytics dashboards, giving planners a single interactive surface to monitor and forecast urban conditions.

Main Features

  • AI-powered traffic prediction
  • Real-time analytics dashboards
  • Digital-twin visualization of city infrastructure
  • Interactive monitoring panels
  • Urban infrastructure health tracking

Technical Architecture

A React frontend renders the digital-twin visualization and dashboard panels, backed by a Node.js API layer. A machine-learning layer produces traffic predictions that the dashboard consumes and displays as live trend indicators.

Challenges & Solutions

Representing several live data streams (traffic, infrastructure status, predictions) in one coherent view without overwhelming the user.

Split the interface into a digital-twin map view plus focused dashboard panels, so each data stream has its own visual context instead of one cluttered screen.

Keeping AI-predicted traffic data understandable to non-technical viewers.

Surfaced predictions as simple trend indicators on the dashboard rather than exposing raw model output.

Results & Impact

Deployed and publicly accessible at metromind-steel.vercel.app - the flagship demonstration of combining AI/ML with full-stack dashboard engineering for smart-city use cases.

Future Improvements

  • Integrate live/open traffic data feeds instead of simulated data
  • Add historical trend comparison across the digital twin
  • Expand infrastructure monitoring to utilities beyond traffic