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GreenGo 🌱

  • AI-powered community platform for biodiversity tracking and sustainability.

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Problem

  • Communities are disconnected and climate change feels out of individual control.

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Solution

  • GreenGo enables local action using AI, maps, and community participation.

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Key Features

  • • Satellite NDMI Analysis
  • • Image-based plant recognition
  • • Community engagement
  • • Interactive maps

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How It Works

  • 1. Analyze satellite data
  • 2. Users upload images
  • 3. AI labels biodiversity
  • 4. Data shown on maps

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Tech Stack

  • Frontend: React + Vite
  • Backend: Django
  • Cloud: AWS
  • Maps: Google Maps / Leaflet
  • AI: Computer Vision

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Architecture

  • User → React App → Django API → AI Model → Database → Map Visualization

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Users Workflow

Exploring map , uploading flowers , creating events with sequence diagrams

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Feature Deep Dive

NDVI calculation , AWS rekognition integration, community comparison stats

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UI (user interface)

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UI (user Interface)

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UI (user interface)

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Business Value

  • • Drives sustainability
  • • Enables local climate action
  • • Scalable for cities & governments

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Future Plans

  • • Map pins for biodiversity
  • • Advanced AI models
  • • Mobile app
  • • Community events system

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Conclusion

  • GreenGo empowers communities to take action for a greener future 🌍