Blue Carbon MRV System

A digital platform that verifies mangrove and seagrass restoration using AI image analysis, geo-tagged field data, and multi-level NGO & government approvals. Blue carbon is 10x powerful than forest.

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🌿 About the Project – Blue Carbon MRV System

🌱 Inspiration

Coastal ecosystems like mangroves and seagrass capture carbon up to 10×

more efficiently than terrestrial forests.

Yet, despite their importance, communities restoring these ecosystems have no transparent system to prove their work or earn from it. Most fishermen plant mangroves for protection, but their contribution to carbon removal is never recorded, verified, or rewarded.

Our inspiration came from this gap:

How can we use technology to verify real environmental impact and empower the coastal communities who protect these ecosystems?

This question led us to develop a digital MRV (Monitoring, Reporting, Verification) system that uses AI, geo-tagging, and transparent workflows.

🧠 What We Learned

Through this project, we learned:

How blue carbon ecosystems act as natural carbon sinks

The importance of MRV (Monitoring, Reporting, Verification) in climate projects

Building end-to-end full-stack systems (frontend + backend + database)

Using AI models for vegetation detection

Integrating geo-location for field-level verification

Designing role-based dashboards for NGOs, Admins, and Corporates

How carbon credits are estimated and issued

Understanding the challenges behind carbon markets and fraud prevention

We gained both technical knowledge and real environmental understanding.

🏗️ How We Built the Project

We followed a structured workflow:

  1. Research & Understanding

We first understood how blue carbon credits are generated, restored, measured, and verified. We studied MRV frameworks and simplified them into a digital flow.

  1. System Architecture Design

We created a workflow that supports four user roles:

Fisherman

NGO Verifier

Admin / Government Authority

Corporate Buyer

  1. Core Components Built

Geo-tagged image upload system

AI verification module using image analysis to detect vegetation

NGO dashboard for human verification & comments

Admin dashboard for final approval & audit logs

Carbon credit simulation module

Corporate marketplace for viewing and buying credits

Translation support for multi-language interface

Google Maps integration for precise ecosystem location

  1. Technology Stack

Frontend: React.js, Typescript , HTML, CSS , JS

Backend: Node.js

Database: PostgreSQL, Supabase

AI: Gemini API

Mapping: Google Maps

🚧 Challenges We Faced

  1. AI Verification Accuracy

Making AI detect mangrove/seagrass vegetation was challenging because:

Image quality varies

Lighting and angle can affect results

We solved this by:

Preprocessing images

Using confidence thresholds

Allowing NGO overrides

  1. GPS & Geo-Tag Validation

Ensuring GPS accuracy in low-signal coastal zones was difficult. We added multiple validation layers:

Browser geolocation

Metadata extraction

Map-based NGO review

  1. Designing Multi-role Workflows

Creating separate dashboards with different permissions required:

Clean API design

Strong authentication

Clear separation of user flows

  1. Carbon Credit Simulation

Carbon credit calculation is scientifically complex. We built a simplified formula for demonstration:

Credits

𝛼 ⋅ Verified Area Credits=α⋅Verified Area

where 𝛼 α is a constant for MVP demonstration.

  1. Time Constraints

We prioritized the most impactful features first and built a clean, working MVP.

Built With

  • css
  • gemini
  • gemini-api
  • google-ai-studio
  • html
  • javascript)-for-frontend
  • node.js-for-backend
  • supabase-with-postgresql-for-database
  • tech-stack:-react.js-(typescript
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