EcoMind 🌍

AI-powered carbon footprint analyzer using Google Gemini

Built for the DEV Weekend Challenge: Earth Day Edition

Live Demo

🔗 https://ecomind-gamma.vercel.app

What It Does

EcoMind lets you describe your daily lifestyle in plain language and returns a personalised carbon footprint analysis powered by the Google Gemini API. No rigid forms — just describe your commute, diet, home heating, and travel habits, and get back:

• Estimated annual CO₂ in kg
• Sustainability score (1–10)
• Top 5 reduction actions ranked by impact with CO₂ savings per year
• Regional context — advice tailored to your location (Finland-aware by default)

Tech Stack

• Next.js 14 (App Router) + TypeScript
• Google Gemini API (gemini-1.5-flash) via @google/generative-ai
• Structured JSON output using Gemini's responseSchema feature
• Tailwind CSS for styling
• Vercel for deployment

Getting Started

# Clone the repo
git clone https://github.com/mzunain/ecomind.git
cd ecomind

# Install dependencies
npm install

# Add your Gemini API key
echo 'GEMINI_API_KEY=your_key_here' > .env.local

# Run development server
npm run dev

Get a free Gemini API key at https://aistudio.google.com

Key Technical Decision: Structured JSON Output

Instead of parsing free-form Gemini text responses, this project uses Gemini's responseSchema to enforce a strict JSON schema at the model level:

const model = genAI.getGenerativeModel({
  model: 'gemini-1.5-flash',
  generationConfig: {
    responseMimeType: 'application/json',
    responseSchema: ecoAnalysisSchema,
  },
});

This guarantees reliable, parseable responses without regex or prompt engineering hacks.

License

MIT