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📄 Reef_A_Marine_Environment_Dataset

Netlify Status Screenshot 2025-05-01 at 16 12 28

🌊 Mariana V2.5 — Intelligent Coral Reef Monitoring System

Official Release Date: May 1st, 2025
Developer: Senath Sethmika | LinkedIn | Facebook


Mariana V2.5 is a next-generation marine monitoring system designed to predict and protect coral reef health. Powered by environmental datasets and a Machine Learning model built using the Gemini API, it evaluates coral supportiveness using real-time marine parameters.

“Protecting coral reefs through data, AI, and clean design.” This dataset contains simulated marine environmental data collected from Reef_A during April 2025, recorded at 6-hour intervals.

It is designed to work with a Machine Learning model powered by the Gemini API to predict whether marine environmental conditions are supportive or threatening to coral health based on multiple oceanographic parameters.


📈 Dataset Overview

🌊 Parameter Thresholds for Coral Health

Parameter Ideal Range Caution / Warning Threatening / Dangerous
Water Temperature (°C) 24–28 28–30 > 30
Salinity (PSU) 33–36 31–33 or 36–38 < 31 or > 38
pH Level 8.0–8.3 7.8–8.0 < 7.8 (Acidification)
Dissolved Oxygen (mg/L) > 6.0 4.0–6.0 < 4.0 (Hypoxia)
Turbidity (NTU) < 1.0 1.0–3.0 > 3.0 (Light Stress)
Nitrate (mg/L) < 0.1 0.1–0.3 > 0.3 (Suffocating)

Each value includes units for realism.


🤖 ML Model Goals (Gemini API)

  • Predict coral supportiveness based on multiple features.
  • Analyze up to 5 parameters simultaneously:
    • Water Temperature
    • Salinity
    • pH Level
    • Dissolved Oxygen
    • Turbidity
    • (Optional) Nitrate
  • Coral supportiveness is not labeled — the ML model must infer it.

📊 Parameter Ranges (Typical & Stressful)

Parameter Supportive Range Stressful Range
Water Temperature 26°C – 29°C > 30°C or < 25°C
Salinity 34.5 – 35.0 PSU < 34.0 or > 35.5 PSU
pH Level 7.9 – 8.3 < 7.6 or > 8.4
Dissolved Oxygen > 5.5 mg/L < 5.0 mg/L
Turbidity < 3.0 NTU > 5.0 NTU
Nitrate < 0.10 mg/L > 0.25 mg/L

Based on published coral reef research data.


🛠️ Notes

  • No Coral_Supportive column is provided — the model must predict it.
  • Data includes natural variation and stress events.
  • Only one location (Reef_A) is included for April 2025.

📥 Future Upgrades

  • Add more reef locations (Reef_B, Reef_C…)
  • Add multi-depth sampling support
  • Seasonal datasets (June, September, etc.)

🌐 CoralSafe Deployment Guide

Steps to Deploy on Netlify

  1. Prepare Your React/Next.js Project

    • TypeScript-based (.tsx)
    • Includes: src/, components/, hooks/, lib/
  2. Create a Netlify Account

  3. Connect GitHub

    • Click New Site from Git
    • Choose repository & set:
      • Branch: main
      • Build Command: npm run build

📧 Contact


🔒 Licensing & Usage

© 2025 CoralGuard by Senath Sethmika. All rights reserved.
Data analysis for educational and scientific purposes only.
Commercial usage, resale, or integration in monetized platforms is strictly prohibited without explicit written permission from the original author, Senath Sethmika (Developer & Owner).


🌊 #CoralSafe #MarianaV2 #ReefProtection #AIForOcean

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A machine learning model to predict coral reef supportiveness based on marine environmental data.

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