EcoTwin: An AI Climate Coach for Real-World Emissions Cuts

What I Built
EcoTwin is a personalized climate action coach that turns a few everyday inputs, like commute habits, food choices, home energy use, and travel frequency, into a practical action plan with estimated annual CO2e savings.

The goal was to build something useful immediately. Instead of giving users a generic sustainability lecture, EcoTwin acts like a climate twin: it estimates a baseline footprint, then recommends the highest-impact changes first.

Users get:

• A baseline annual footprint estimate
• A personalized set of top climate actions
• Projected annual CO2e savings
• A concise AI coaching summary powered by Gemini (with fallback if key is unavailable)

Demo
Live demo: https://ready-lamps-poke.loca.lt

Quick walkthrough:

1. Open the app
2. Enter a city and lifestyle inputs
3. Click Generate My Climate Plan
4. Review before/after footprint and recommended actions
5. Read the AI coach summary

Code
Source code is in the project folder:

• Backend: Flask API for scoring, recommendations, and AI summary
• Frontend: HTML/CSS/JS dashboard with interactive results
• Data: Curated action library with estimated CO2e savings

Core implementation highlights:

1. Transparent footprint estimation model
2. Rule-based personalization of actions by user profile
3. Gemini API integration for natural-language coaching
4. Stable local fallback summary for reliability

How I Built It
I built EcoTwin as a focused full-stack Flask app to keep the product easy to run, easy to demo, and easy to judge.

Architecture flow:

1. Frontend collects a lightweight user profile
2. Backend computes annual baseline emissions
3. Action library is filtered by relevance and sorted by impact
4. App calculates projected reductions and renders before/after metrics
5. Gemini generates a short personalized coaching summary

Design decisions:

• Kept input friction low so users can get value in seconds
• Prioritized practical behavior-change suggestions over abstract climate theory
• Added clear before/after visuals to make impact tangible during a live demo

Prize Categories
This submission is for:

• Best use of Google Gemini
• Best use of GitHub Copilot

Team
Solo submission.