What If Your Daily Habits Had a Carbon Score? I Built EcoTrack AI 🌱

This is a submission for Weekend Challenge: Earth Day Edition

What I Built

EcoTrack AI is a frontend-based, AI-inspired web application that helps users understand and reduce their daily carbon footprint through simple lifestyle inputs.

While awareness around climate change is growing, most people don’t feel how their everyday actions contribute to it. EcoTrack AI bridges this gap by transforming abstract environmental impact into clear, immediate feedback.

Users input their daily habits—transport, diet, and energy usage—and the system simulates an AI-powered analysis to:

• Estimate their carbon footprint
• Compare it against an average baseline
• Generate personalized, behavior-focused recommendations

The goal is not just to measure impact, but to influence everyday decisions through visible feedback.

Demo

Below is a short walkthrough of the product experience: [https://youtu.be/nS_LYPiwkMo]

How I Built It

I designed EcoTrack AI as a frontend-first simulation of an intelligent system, focusing on clarity, responsiveness, and real-world usability.

The application is built using React with a modular, component-driven architecture:

• Component Design: Each stage of the user journey (input → analysis → insights) is handled by dedicated components, ensuring clean separation and scalability
• Centralized State Management: User inputs, loading states, and results are managed in a single source of truth for predictable data flow
• Carbon Logic Engine: A rule-based system estimates emissions using realistic factors across transport, diet, and energy usage
• AI Simulation Layer: A timed loading state mimics real-world AI processing, creating a sense of analysis and responsiveness
• Dynamic Recommendation System: Suggestions adapt based on user inputs, making the experience personalized rather than static
• Data Visualization: Charts provide intuitive feedback on trends and comparisons

The system is intentionally structured so that the simulated recommendation engine can be replaced with a real LLM integration using Google Gemini for live, context-aware insights.

Additional Notes

• “AI-powered insights” are simulated using frontend logic for demonstration purposes
• The architecture is designed to support real AI integration with minimal changes

EcoTrack AI is not just a calculator—it’s a behavioral feedback system.

If users can clearly see their impact, they’re far more likely to change it.

Small visibility → small actions → meaningful collective impact.