🚀 FlowSync AI — Real-Time Crowd Intelligence Platform

FlowSync AI is a real-time crowd intelligence system designed for large-scale venues like stadiums, concerts, and public events.

It enables density-aware routing, queue prediction, and operational decision-making using live or simulated crowd data—helping organizers manage 100,000+ attendees efficiently in real time.

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🧠 Problem

Large events face:

• Unpredictable crowd congestion
• Long queues at food/restrooms
• Unsafe bottlenecks during peak moments
• Lack of real-time visibility for operators

Most systems today are reactive, not predictive.

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⚡ Solution

FlowSync AI is predictive + adaptive.

It continuously:

• Monitors crowd density
• Predicts congestion hotspots
• Suggests optimal routes
• Recommends operator interventions

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🎯 Key Features

📍 Real-Time Crowd Intelligence

• Zone-based density heatmaps
• Live crowd simulation / ingestion
• Hotspot detection

🧭 Smart Routing Engine

• Density-weighted pathfinding
• Avoids congested zones dynamically
• Phase-aware navigation (entry / halftime / exit)

⏱ Queue Intelligence

• Predict wait times for stalls/restrooms
• Suggest faster alternatives

🧑‍💼 Operator Dashboard

• High-risk zones detection
• Actionable interventions
• Real-time alerts system

🎮 Demo Scenarios (Hackathon Ready)

• Surge simulation
• Food rush spike
• Emergency evacuation mode
• AI optimization mode

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🏟 Real-World Context

Tested using Narendra Modi Stadium (Ahmedabad) layout:

• Real geographic structure
• Gate-based entry/exit logic
• Zone-mapped crowd simulation

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📍 Supported Locations

🏟 Stadiums

• Narendra Modi Stadium
• Wembley Stadium
• MetLife Stadium
• Melbourne Cricket Ground
• Camp Nou

🗺 Places / Landmarks

• Times Square
• Burj Khalifa
• Eiffel Tower
• Tirupati Temple
• Kumbh Mela Grounds

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🧱 Tech Stack

Layer	Tech
Frontend	React + TypeScript + Vite
Backend	FastAPI (Python)
Deployment	Google Cloud Run
Maps	Google Maps Platform
Algorithms	Grid-based pathfinding + density cost weighting
Data Mode	Hybrid (Simulated + Live Ingest API)

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🌐 Live Deployment

• 🔗 Frontend: https://flowsync-frontend-796656775802.asia-south1.run.app
• 🔗 Backend API: https://flowsync-backend-796656775802.asia-south1.run.app
• 📘 API Docs: https://flowsync-backend-796656775802.asia-south1.run.app/docs

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⚙️ System Architecture

Frontend (React) -> Backend API (FastAPI) -> Crowd Simulator / Live Data Ingestion -> Routing + Prediction Engine

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🚀 Getting Started (Local)

Backend

cd backend
pip install -r requirements.txt
uvicorn app.main:app --reload --port 8000

Frontend

cd frontend
npm install
npm run dev

Access

• Frontend → http://localhost:5173
• Backend Docs → http://localhost:8000/docs

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🔌 API Highlights

Endpoint	Description
/snapshot	Current crowd + queue state
/heatmap	Zone density map
/journey	Smart route planning
/venue-map	Venue structure
/staff-actions	AI operator suggestions
/alerts	Real-time alerts
/demo-control	Trigger simulation scenarios
/ingest/live-snapshot	Push real telemetry
/data-source	Live vs simulated data status

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📡 Live Data Ingestion Example

{
  "generated_at": "2026-04-15T12:30:00Z",
  "zones": [
    { "zone_id": "zone-1", "density_score": 88 }
  ],
  "queues": [
    { "stall_id": "stall-1", "wait_time_minutes": 12 }
  ]
}

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🧪 Demo Scenarios

Trigger via /demo-control:

• surge-zone-1
• food-rush
• emergency-mode
• optimize-crowd

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🏆 Why This Project Stands Out

• Real-world venue simulation (not dummy/demo-only data)
• AI-driven routing and prediction logic
• Full-stack deployment on Google Cloud Run
• Covers both attendee experience + operator decision-making
• Designed to scale with real telemetry (IoT, CCTV, WiFi tracking)

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⚠️ Important Notes

• API keys (Google Maps) are restricted by domain
• Backend CORS is configured for the deployed frontend
• System works in simulated mode by default if no live data is ingested

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🔒 License

MIT License