🌱 EcoIntellect API

Tagline: Sustainability Intelligence Layer for Digital Platforms

🎯 Problem Statement

Digital platforms (food delivery, ride booking, e-commerce) contribute significantly to carbon emissions through transportation choices, packaging waste, and inefficient routing. Users make high-carbon decisions daily without knowing the environmental cost.

The Gap: Platforms lack a plug-and-play sustainability intelligence layer for their checkout flows.

💡 Solution

EcoIntellect is a Sustainability Decision Intelligence API that platforms integrate at checkout to:

Capability	Description
🔬 Emission Calculation	Powered by GreenPT emission factors (EPA-sourced baseline)
🔄 Alternative Comparison	Rank all 16 transport × packaging combos by Eco Score
📡 Scale Modelling	Wolfram\|One projects impact from 1,000→1,000,000 users
🎮 Gamification	Eco Scores (0–100), achievements, and ranking
🛒 Checkout Interception	Live demo showing Swiggy/Zomato-style popup at payment

🏗️ Architecture

┌──────────────────────────┐
│  Food Delivery Platform  │  (Swiggy, Zomato, etc.)
│  "User presses Pay ₹390" │
└────────────┬─────────────┘
             │ POST /api/v1/analyze-order
             ▼
┌────────────────────────────────────────────────────┐
│               EcoIntellect API                     │
│  (FastAPI · Python · Pydantic)                     │
│                                                    │
│  ┌──────────────────┐  ┌─────────────────────────┐ │
│  │  GreenPTClient   │  │     WolframClient       │ │
│  │  - Emission      │  │  - Yearly projections   │ │
│  │    factors       │  │  - 1k→1M user scenarios │ │
│  │  - Eco estimates │  │  - Tree equivalents     │ │
│  └──────────────────┘  └─────────────────────────┘ │
└────────────────────────────────────────────────────┘
             │
             ▼
┌──────────────────────────┐
│   EcoIntellect Dashboard │  (React + Vite + Recharts)
│   - Analysis charts      │
│   - Alternative rankings │
│   - Wolfram scale chart  │
│   - Mock checkout demo   │
└──────────────────────────┘

🚀 Quick Start

Prerequisites

Python 3.9+
Node.js 18+

Backend

cd backend
python -m venv venv
venv\Scripts\activate        # Windows
# source venv/bin/activate   # macOS/Linux

pip install -r requirements.txt

# Add your sponsor API keys
cp .env.example .env

uvicorn app.main:app --reload
# → http://localhost:8000
# → http://localhost:8000/docs  (Swagger UI)

Frontend

cd frontend
npm install
npm run dev
# → http://localhost:5173

🔑 Environment Variables

# backend/.env
GREENPT_API_KEY=your_greenpt_api_key_here
WOLFRAM_APP_ID=your_wolfram_app_id_here

The API root (GET /) shows live integration status:

{
  "sponsor_integrations": {
    "greenpt": true,
    "wolfram": true
  }
}

📊 API Reference

`POST /api/v1/analyze-order`

Calculate the full environmental footprint of a food delivery order.

Request:

{
  "distance_km": 5,
  "transport_mode": "car",
  "packaging_type": "plastic",
  "estimated_time_minutes": 30,
  "order_value": 350,
  "frequency_per_week": 3
}

Response:

{
  "carbon_emission_grams": 650.0,
  "eco_score": 20,
  "rating": "Poor",
  "better_alternatives": [
    {
      "transport_mode": "Bike",
      "packaging_type": "Reusable",
      "carbon_emission_grams": 5.0,
      "carbon_saved_grams": 645.0,
      "time_difference_minutes": 8,
      "eco_score": 95
    }
  ],
  "yearly_projection": {
    "total_orders_per_year": 156,
    "total_carbon_kg": 101.4,
    "trees_needed_to_offset": 5,
    "equivalent_car_km": 845.0,
    "money_spent": 54600.0,
    "scale_scenarios": [
      { "users": 1000,    "total_co2_saved_tonnes": 101.4,   "label": "1,000 users" },
      { "users": 10000,   "total_co2_saved_tonnes": 1014.0,  "label": "10,000 users" },
      { "users": 100000,  "total_co2_saved_tonnes": 10140.0, "label": "100,000 users" },
      { "users": 1000000, "total_co2_saved_tonnes": 101400.0,"label": "1,000,000 users" }
    ]
  },
  "environmental_context": "That's equivalent to driving 811 km by car."
}

`GET /api/v1/compare-alternatives?distance_km=5`

Returns all 16 transport × packaging combinations ranked by Eco Score.

`GET /api/v1/user-impact/{user_id}`

Returns gamified impact summary: Eco Score, carbon saved, achievements, Wolfram projections.

🔌 Production Integration Guide

This section explains how EcoIntellect moves from hackathon demo to production SaaS.

Decision Matrix: Mock vs Production

Component	Hackathon Demo	Production
Emission factors	EPA-sourced constants (in `GreenPTClient`)	Live GreenPT API calls
Yearly projections	Wolfram API (active) + math fallback	Full Wolfram\|One computational queries
User database	Statistically representative mock data	PostgreSQL / Supabase
Authentication	Open (demo)	JWT / API key middleware

Upgrading GreenPT to Production

In backend/app/services/greenpt_integration.py:

def get_emission_factor(self, category: str, item: str) -> float:
    if self.api_key:
        # ✅ Production: uncomment this block
        # response = requests.post(
        #     f"{self.base_url}/emissions/factor",
        #     headers={"Authorization": f"Bearer {self.api_key}"},
        #     json={"category": category, "item": item}
        # )
        # return response.json().get('co2_grams', 0)
        pass

    # Demo fallback: EPA-sourced baseline data
    return self.demo_transport_factors.get(item, 100)

Example: Zomato Integration

// At checkout — call EcoIntellect before showing "Place Order"
const ecoResponse = await fetch('https://api.ecointellect.io/v1/analyze-order', {
  method: 'POST',
  headers: {
    'Authorization': 'Bearer YOUR_API_KEY',
    'Content-Type': 'application/json'
  },
  body: JSON.stringify({
    distance_km: calculateDistance(restaurant, userAddress),
    transport_mode: selectedDeliveryType,   // "car" | "bike" | "electric_vehicle"
    packaging_type: restaurantPackaging,    // "plastic" | "paper" | "biodegradable"
    order_value: cartTotal,
    frequency_per_week: getUserOrderFrequency(userId)
  })
});

const eco = await ecoResponse.json();

// Show EcoIntellect intercept popup when eco_score < 60
if (eco.eco_score < 60 && eco.better_alternatives.length > 0) {
  const best = eco.better_alternatives[0];
  showEcoInterceptModal({
    carbonSaved: best.carbon_saved_grams,
    ecoOption: `${best.transport_mode} + ${best.packaging_type}`,
    discount: 10   // ₹10 eco-discount
  });
}

🌍 Environmental Impact at Scale

Using Wolfram|One modelling (computed live by the API):

User Adoption	CO₂ Saved / Year
1,000 users switch	~101 tonnes
10,000 users switch	~1,014 tonnes
100,000 users switch	~10,140 tonnes
1,000,000 users switch	~101,400 tonnes 🌳

Equivalent to planting 4.6 million trees if 1M delivery users switched to eco-options.

🎮 Demo Scenarios

Scenario	Transport	Packaging	Distance	Eco Score
High Impact	Car	Plastic	10 km	20 (Poor)
Mid Range	Motorcycle	Paper	5 km	—
Eco-Friendly	Bike	Reusable	3 km	95 (Excellent)
EV Transition	Electric Vehicle	Biodegradable	8 km	—

🛠️ Tech Stack

Layer	Technology
API	FastAPI (Python 3.9+)
Validation	Pydantic v2
Sponsor: Emissions	GreenPT API
Sponsor: Projections	Wolfram\|One
Frontend	React 19 + Vite
Styling	Tailwind CSS v4
Charts	Recharts
Icons	Lucide React

📈 Future Roadmap

Production GreenPT API live data feeds
Wolfram Alpha complex route optimization queries
PostgreSQL user history and carbon ledger
Mobile SDK (iOS / Android)
Carbon offset marketplace integration
Multi-city emission factor calibration
AI-powered delivery clustering (reduce total trips)

📝 License

MIT — see LICENSE

🏆 Built For

Hack for Humanity 2026 · hack-for-humanity-26.devpost.com

Environmental focus: Carbon emissions, waste reduction, sustainable transport

Built with 💚 for a sustainable future · Powered by GreenPT & Wolfram|One

Name		Name	Last commit message	Last commit date
Latest commit History 21 Commits
backend		backend
docs		docs
frontend		frontend
.gitignore		.gitignore
README.md		README.md
start.bat		start.bat

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Repository files navigation

🌱 EcoIntellect API

🎯 Problem Statement

💡 Solution

🏗️ Architecture

🚀 Quick Start

Prerequisites

Backend

Frontend

🔑 Environment Variables

📊 API Reference

`POST /api/v1/analyze-order`

`GET /api/v1/compare-alternatives?distance_km=5`

`GET /api/v1/user-impact/{user_id}`

🔌 Production Integration Guide

Decision Matrix: Mock vs Production

Upgrading GreenPT to Production

Example: Zomato Integration

🌍 Environmental Impact at Scale

🎮 Demo Scenarios

🛠️ Tech Stack

📈 Future Roadmap

📝 License

🏆 Built For

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🌱 EcoIntellect API

🎯 Problem Statement

💡 Solution

🏗️ Architecture

🚀 Quick Start

Prerequisites

Backend

Frontend

🔑 Environment Variables

📊 API Reference

POST /api/v1/analyze-order

GET /api/v1/compare-alternatives?distance_km=5

GET /api/v1/user-impact/{user_id}

🔌 Production Integration Guide

Decision Matrix: Mock vs Production

Upgrading GreenPT to Production

Example: Zomato Integration

🌍 Environmental Impact at Scale

🎮 Demo Scenarios

🛠️ Tech Stack

📈 Future Roadmap

📝 License

🏆 Built For

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`POST /api/v1/analyze-order`

`GET /api/v1/compare-alternatives?distance_km=5`

`GET /api/v1/user-impact/{user_id}`

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