What I Built
I built GreenLens, an AI-powered platform that turns any location into actionable environmental intelligence.
Most tools show:
AQI
climate data
reports
👉 But they don’t answer:
“Where exactly should we plant trees?”
🌳 The Breakthrough
GreenLens doesn’t just analyze — it decides.
It tells you:
📍 where to plant trees
🌱 how many trees are needed
🌳 where dense forests are possible
🧠 what strategy to follow
🌿 Miyawaki Forest Detection (Core Feature)
Using the Miyawaki method, the system identifies:
high-impact plantation zones
small-area dense forests
fast-growing urban greening opportunities
🖼️ How It Looks (ADD YOUR SCREENSHOTS HERE)
👉 (IMPORTANT: Add these images in your Dev.to post manually)
📸 Screenshot 1: Map selection
📸 Screenshot 2: Results dashboard
📸 Screenshot 3: AI recommendations
⚡ How It Works
User selects location
↓
Fetch environmental data
↓
Calculate tree opportunity
↓
AI generates recommendations
↓
Dashboard displays results
🧠 AI Layer (What Makes It Special)
Instead of a chatbot, Google Gemini acts as a decision engine:
interprets environmental signals
generates human-readable insights
suggests real-world actions
💡 Core Idea
Data provides facts. AI provides direction.
🚀 From Analysis → Real Impact
This is not just a tool — it’s a platform vision.
🌍 Community Tree Tracking
tag planted trees
upload images
track growth
build local communities
👉 “GitHub for trees”
💰 Crowdfunding Environmental Action
launch plantation campaigns
raise funds
track execution
👉 “This area needs 500 trees → fund → plant → track”
🏗️ How I Built It
Tech Stack
Laravel + Blade
Bootstrap
Google Maps API
Google Air Quality API
Google Gemini
SQLite
Nginx
⚡ Real Engineering Challenge
The app runs under:
/earth-health/
This required:
fixing Laravel routing
handling base paths
configuring nginx
🌍 Why This Matters
Environmental tools usually fail because they:
show data
but don’t guide action
GreenLens bridges:
👉 data → decisions → action
Demo Links
🌐 Live App: http://104.207.64.25/earth-health/
🧪 Assessment: http://104.207.64.25/earth-health/assess
💻 Code: https://github.com/ahmadrabbani/earth-health
💰 Call for Collaboration
I’m looking to take this further:
🌍 environmental partners
💻 developers
💰 early supporters
Prize Categories
🥇 Best Use of Google Gemini
How it works ?
User selects location
↓
Fetch environmental data
↓
Calculate tree opportunity
↓
AI generates recommendations
↓
Dashboard displays results
Gemini is deeply integrated as:
interpretation layer
recommendation engine
decision support
Final Thoughts
AI shouldn’t just inform.
It should help us act.
Prize Categories
🥇 Best Use of Google Gemini
Gemini is deeply integrated as:
interpretation layer
recommendation engine
decision support
💬 Feedback welcome
⭐ Star the repo if you like it
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