
The Problem: When 50,000 Fans Hit the Gates at Once
Stadium bottlenecks aren't just annoying—they're dangerous. Static gate assignments fail when crowd dynamics shift. For PromptWar 2026, I wanted to solve this with code that actually thinks.
The Build: PromptWar Crowd Orchestration
Instead of rigid assignments, I built a 4-tier Human-Sensor Network that treats crowd management as a living system:
| Tier | Role |
|---|---|
| Host | Strategic oversight & emergency override |
| Volunteer | Ground-level sensors & mission execution |
| Attendee | Passive data source (location, velocity) |
| Service Provider | Resource allocation & logistics |
Technical Architecture
ElasticEntry Algorithm
The core routing engine calculates real-time "Friction Scores" for every entry point based on:
- Surge density (people/minute)
- Fan transit velocity
- Historical congestion patterns
Stack
- Backend: FastAPI + WebSockets for sub-second perimeter updates
- AI Layer: Gemini for predictive bottleneck detection (identifies trouble 10-15 min before it happens)
- Infra: Google Cloud Run—scales to zero, bursts to thousands
Live Demo
🔗 Try it on mobile
📂 GitHub repo
What I Learned
Combining real-time WebSocket state management with Gemini's predictive calls taught me where AI adds value vs. where deterministic logic wins. The sweet spot: AI for forecasting, traditional algorithms for immediate routing decisions.
Built for #PromptWar2026 with #GoogleCloud. Feedback welcome—how would you handle the load balancing differently?
United States
NORTH AMERICA
Related News
Amazon Employees Are 'Tokenmaxxing' Due To Pressure To Use AI Tools
20h ago
UCP Variant Data: The #1 Reason Agent Checkouts Fail
6h ago

Décryptage technique : Comment builder un téléchargeur de vidéos Reddit performant (DASH, HLS & WebAssembly)
16h ago
How Braze’s CTO is rethinking engineering for the agentic area
10h ago
Encryption Protocols for Secure AI Systems: A Practical Guide
20h ago



