Building ArenaIQ: A Real-Time Stadium Fan Experience Powered by AI

Sumanth Gadiparthi — Mon, 20 Apr 2026 12:57:38 +0000

We’ve all been there. You pay top dollar for a concert or a sports game, only to miss the most exciting moment because you were stuck in a concession line for twenty minutes, or trapped outside at the most crowded entrance gate.

Stadiums are massive, unpredictable ecosystems. But what if we could give every fan a real-time, personalized guide to navigate the venue?

That was the inspiration behind ArenaIQ—a real-time fan experience dashboard built for the PromptWars by Google hackathon. Here is a look at how I built it, the architecture behind it, and how Prompt Engineering drives the entire experience.

🎯 The Problem
Large venues suffer from three massive crowd-control issues:

Gate Bottlenecks: Thousands of people flock to the main entrance, leaving side gates completely empty.
Concession Wait Times: Fans guess which food stand is fastest, often guessing wrong.
Dangerous Density: Sections get dangerously crowded without warning.
I wanted to build an application that solves all three of these problems natively on a fan's mobile device, all without relying on expensive backend infrastructure or paid APIs.

💡 The Solution: ArenaIQ
ArenaIQ is a premium, mobile-responsive dashboard designed to feel like a live, high-end tech product. It features three core modules:

Smart Gate Recommender: Highlights the absolute fastest gate to enter through based on live capacity.
Concession Wait Time Tracker: Ranks food stalls and displays wait-time trends so you know exactly when to grab a bite.
Flash Crowd Alerts: A live heatmap that pushes an alert directly to your phone if your current stadium section exceeds 85% capacity.
🏗️ Technical Architecture
To meet the strict hackathon constraints (specifically keeping the entire repository under 10MB), I had to be incredibly efficient with the architecture.

Frontend Framework: Next.js 14 (App Router) using React.
Styling & UI: Tailwind CSS. I completely avoided heavy external component libraries (like Material UI or Chakra) and instead built a custom Glassmorphic dark-mode design system. This kept the bundle size incredibly small while looking exceptionally premium.
State & Simulation: Because I couldn't use a paid live-data API, I built a custom React hook called useStadiumLive. This acts as a localized Simulation Engine, generating "Random Walks" and jittering the stadium data every 5 seconds to mimic thousands of moving fans.
🤖 The "Secret Sauce": The AI Logic Bridge
Because this project was for PromptWars, the judges aren't just looking at the code—they want to see how Prompt Engineering is utilized.

To showcase this, I built the AI Logic Bridge.

Instead of hiding the AI logic in the backend, I built a live, typewriter-animated terminal directly into the dashboard. Every 5 seconds, as the stadium data changes, the UI generates the exact System Prompt that the AI uses to calculate its recommendations. It dynamically feeds the AI the live gate occupancies, crowd thresholds, and concession wait times, and outputs the final recommendation.

It makes the prompt engineering 100% transparent and proves that the app's routing is driven by dynamic context, not just hardcoded if/else statements.

🚀 Accelerating Development with Antigravity
Building a beautiful, dynamic, and state-heavy dashboard in a short amount of time is difficult. To speed up my workflow, I heavily leveraged Google's Antigravity AI assistant.

Using Antigravity allowed me to:

Rapidly scaffold the useStadiumLive simulation engine.
Iterate on the Tailwind CSS glassmorphism design system without getting bogged down in CSS syntax.
Wire up complex Next.js state management across multiple components seamlessly.
🏁 Conclusion
ArenaIQ proves that you don't need massive databases, paid API keys, or heavy backend infrastructure to build a product that feels "live." By combining Next.js, highly optimized vanilla Tailwind, and smart Prompt Engineering, you can build dynamic, real-time dashboards that solve real-world problems.

The codebase is currently completely open-source and comes in at a remarkably small 0.08 MB.

Check out the code on GitHub here: https://github.com/wonderful809/arenaiq
What are your thoughts on using Client-Side AI simulations for live events? Let me know in the comments below!

DEV Community: Sumanth Gadiparthi

Building ArenaIQ: A Real-Time Stadium Fan Experience Powered by AI