Inspiration
Roads are the backbone of modern cities, yet most road management systems still react after problems occur after accidents cause congestion, after damage becomes expensive, after delays impact thousands of people.
I was inspired by a simple question: What if road operators could make decisions before problems escalate?
InfraPulse was born from the need to help cities and highway operators move from reactive monitoring to real-time and predictive decision-making, improving safety, efficiency and sustainability.
What it does
InfraPulse is an intelligent road decision platform that helps cities and highway operators: Detect road incidents (accidents, obstructions, breakdowns) in real time Predict infrastructure risks before failures occur Recommend clear, actionable operational decisions Visualize road conditions through a live operator dashboard Instead of just showing data, InfraPulse turns road data into decisions helping operators respond faster today and plan smarter for tomorrow.
How I built it
InfraPulse was built as an API-first web system with a clear separation of concerns:
Frontend (HTML, CSS, JavaScript): A live operator dashboard showing road maps, incident alerts, risk levels, and decision summaries.
Backend (PHP): Acts as the decision engine, aggregating road data, processing events and communicating with the AI layer.
Database (MySQL): Stores road metadata, traffic events, incident reports, vibration data, weather logs and AI decisions for historical analysis.
AI (Gemini): Used for incident classification, severity scoring, predictive maintenance insights, and executive decision summaries. All AI outputs are structured JSON to ensure reliability and easy integration.
To make the system hackathon-ready, realistic simulated data is used to represent traffic flow, road stress, and incidents while keeping the architecture ready for real sensors and telecom integrations.
Challenges I ran into
Designing an AI system that produces structured, reliable decisions, not vague responses Balancing realism with hackathon constraints (simulating sensors responsibly) Ensuring the system felt enterprise-grade, not like a simple web app Keeping the scope focused enough to build fast, yet strong enough to demonstrate real-world impact Each challenge forced better system design and clearer decision logic.
Accomplishments that I'm proud of
Built a complete real-time + predictive decision system, not just a dashboard Successfully integrated AI as a decision intelligence layer, not a gimmick Designed a clean, scalable database model suitable for real deployments Created a demo-ready system that clearly shows before/after impact Aligned the solution tightly with real infrastructure stakeholders and judges Most importantly, InfraPulse feels like something that could actually be piloted.
What I learned
Judges value clarity and impact more than complex technology AI is most powerful when used to augment human decisions, not replace them Good system architecture matters even in a hackathon Simulated data can be powerful when paired with realistic logic Storytelling is as important as engineering
What's next for InfraPulse
Integration with real IoT sensors and vehicle telematics Advanced traffic and infrastructure forecasting models Direct integration with emergency services and toll systems Multi-city deployment with comparative analytics Sustainability metrics to measure emissions reduction InfraPulse is designed to grow from a hackathon prototype into a real intelligent infrastructure platform.
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