EcoGuard AI

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  Website interface

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  Two modes. One mission.

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  Deforestation detection

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  Deforestation detection Count tree crowns, estimate canopy coverage, and quantify forest loss. Spot clearings, logging roads, etc

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  Pollution assessment

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  Pollution assessment Identify smog plumes, oil sheens, mining tailings, algal blooms, and industrial runoff with grounded visual evidence

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  Your scans No scans yet — let's protect some forests

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  Guardians leaderboard The most active environmental guardians on EcoGuard AI.

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  How it works

Inspiration

I am Egyptian, and Egypt is not known for its forests. However, I have relatives in Brazil, and during my visit last year, I saw with my own eyes the scale of the environmental disaster happening in the Amazon rainforest. I watched large areas transform from dense forests into barren land due to illegal logging, agriculture, and mining.

That scene deeply affected me and made me think: how can we use artificial intelligence to help monitor and protect such vital forests for our planet?

That's how the idea of EcoGuard AI was born — a simple yet powerful tool that allows anyone (researcher, environmental activist, or ordinary citizen) to upload a satellite or drone image and know within seconds whether deforestation is happening in that area.

What we built

We built a complete web platform that allows users to:

• Upload satellite or drone images easily
• Analyze the image using advanced vision models
• Receive a detailed report containing tree loss percentage, estimated tree count, and environmental analysis

Technical Features

• Modern Dark Forest design
• Professional PDF report export
• Personal dashboard + analysis history
• Interactive map
• Full Arabic & English support

How we built it

• Next.js 15 + TypeScript – Frontend framework
• Supabase – Database & authentication
• Lovable AI (Gemini) – Image analysis & deforestation detection
• Tailwind CSS + Shadcn/ui – Styling & components
• Leaflet Maps – Interactive mapping
• jsPDF – PDF report generation

Challenges we faced

• Making the analysis as accurate as possible on satellite imagery
• Building an easy-to-use interface for non-technical people
• Completing the project in a short time

What we learned

Using AI models for aerial image analysis, integrating interactive maps with analysis data, and the importance of building a user experience that works for everyone regardless of their technical background.

The story behind EcoGuard AI

EcoGuard AI started from a personal experience in the Amazon, and our goal is to help protect the world's most important forests using artificial intelligence.

Built With

• gemini-ai
• lovabl
• next.js
• supabase
• tailwind-css