🌊 OceanGuard

AI-Powered Marine Risk & Fisheries Intelligence System
Empowering fishermen and marine operators with real-time risk prediction, weather intelligence, and profit analytics.

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📖 Overview

OceanGuard is a full-stack SaaS platform that leverages machine learning and real-time weather data to help fishermen and marine operators make safer, smarter decisions at sea.

By combining a Random Forest ML model, live OpenWeather API data, and a rule-based hybrid system, OceanGuard delivers accurate marine risk predictions, profit estimations, and actionable analytics — all through a clean, responsive dark-mode interface.

Built for fisheries communities to reduce risk, maximize profit, and navigate with confidence. 🐟⚓

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✨ Features

Feature	Description
🤖 ML Risk Prediction	Random Forest model predicts marine risk levels based on real-time conditions
🌦️ Weather Integration	Live wind speed, wave height, and conditions via OpenWeather API
🔀 Hybrid Prediction	Rule-based fallback system combined with ML for higher accuracy
💰 Profit Calculator	Deterministic profit calculation module for fisheries planning
📊 Analytics Dashboard	Risk trends, historical insights, and decision support
🔐 Secure Auth	JWT-based authentication with OTP email verification
💳 Subscription Access	Free, Pro, and Enterprise tier access control
🌙 Dark Mode UI	Fully responsive interface with dark mode support

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🛠️ Tech Stack

Frontend

• ⚛️ React — Component-based UI
• 🎨 Tailwind CSS — Utility-first styling
• 🔷 TypeScript — Type-safe development

Backend

• 🟢 Node.js — Runtime environment
• 🚂 Express.js — REST API framework
• 🔑 JWT + OTP — Authentication & verification
• 📧 Gmail OAuth2 — Email service

ML Microservice

• 🐍 Python — ML development
• ⚡ FastAPI — High-performance ML API
• 🌲 scikit-learn — Random Forest model

Database & APIs

• 🍃 MongoDB Atlas — Cloud database
• 🌤️ OpenWeather API — Real-time weather data

Deployment

• 🔺 Vercel — Frontend hosting
• 🎯 Render — Backend & ML hosting

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🏗️ Architecture

User Request
     │
     ▼
┌─────────────┐
│   Frontend  │  React + Tailwind (Vercel)
│  (React)    │
└──────┬──────┘
       │ HTTP/REST
       ▼
┌─────────────┐
│   Backend   │  Node.js + Express (Render)
│  (Node.js)  │──────────────────────────────┐
└──────┬──────┘                              │
       │                                     ▼
       │                           ┌──────────────────┐
       ├──► OpenWeather API        │   MongoDB Atlas   │
       │    (Weather Data)         │   (Users, OTPs,   │
       │                           │    Risk Logs)     │
       ▼                           └──────────────────┘
┌─────────────┐
│ ML Service  │  Python + FastAPI (Render)
│  (FastAPI)  │  Random Forest Model
└─────────────┘
       │
       ▼
  Risk Prediction
  (safe / moderate / dangerous)

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📁 Folder Structure

oceanguard
├── backend
│   ├── src
│   │   ├── config
│   │   │   └── db.js
│   │   ├── controllers
│   │   │   ├── authController.js
│   │   │   ├── contactController.js
│   │   │   ├── dashboardController.js
│   │   │   ├── profitController.js
│   │   │   ├── riskController.js
│   │   │   └── subscriptionController.js
│   │   ├── middleware
│   │   │   ├── auth.js
│   │   │   └── subscription.js
│   │   ├── models
│   │   │   ├── Contact.js
│   │   │   ├── OTP.js
│   │   │   ├── Profit.js
│   │   │   ├── Risk.js
│   │   │   └── User.js
│   │   ├── routes
│   │   │   ├── authRoutes.js
│   │   │   ├── contactRoutes.js
│   │   │   ├── dashboardRoutes.js
│   │   │   ├── profitRoutes.js
│   │   │   ├── riskRoutes.js
│   │   │   └── subscriptionRoutes.js
│   │   ├── services
│   │   │   ├── mlService.js
│   │   │   └── weatherService.js
│   │   ├── utils
│   │   │   ├── apiResponse.js
│   │   │   ├── generateOTP.js
│   │   │   └── sendEmail.js
│   │   └── app.js
│   ├── .gitignore
│   ├── package-lock.json
│   ├── package.json
│   └── server.js
├── frontend
│   ├── public
│   │   ├── favicon.png
│   │   └── favicon.svg
│   ├── src
│   │   ├── assets
│   │   │   └── hero-bg.jpg
│   │   ├── components
│   │   │   ├── dashboard
│   │   │   │   └── DashboardLayout.tsx
│   │   │   ├── landing
│   │   │   │   ├── Footer.tsx
│   │   │   │   └── LandingNavbar.tsx
│   │   │   ├── ui
│   │   │   │   ├── sonner.tsx
│   │   │   │   ├── toast.tsx
│   │   │   │   ├── toaster.tsx
│   │   │   │   └── tooltip.tsx
│   │   │   ├── NavLink.tsx
│   │   │   └── OceanGuardLogo.tsx
│   │   ├── hooks
│   │   │   ├── use-mobile.tsx
│   │   │   ├── use-toast.ts
│   │   │   └── useTheme.tsx
│   │   ├── lib
│   │   │   ├── api.ts
│   │   │   └── utils.ts
│   │   ├── pages
│   │   │   ├── dashboard
│   │   │   │   ├── AnalyticsPage.tsx
│   │   │   │   ├── OverviewPage.tsx
│   │   │   │   ├── ProfitCalculatorPage.tsx
│   │   │   │   ├── RiskHistoryPage.tsx
│   │   │   │   ├── RiskPredictionPage.tsx
│   │   │   │   ├── SettingsPage.tsx
│   │   │   │   └── SubscriptionPage.tsx
│   │   │   ├── AboutPage.tsx
│   │   │   ├── ContactPage.tsx
│   │   │   ├── ForgotPasswordPage.tsx
│   │   │   ├── HomePage.tsx
│   │   │   ├── LoginPage.tsx
│   │   │   ├── NotFound.tsx
│   │   │   ├── ResetPasswordPage.tsx
│   │   │   ├── ServicesPage.tsx
│   │   │   └── SignupPage.tsx
│   │   ├── App.tsx
│   │   ├── index.css
│   │   ├── main.tsx
│   │   └── vite-env.d.ts
│   ├── .gitignore
│   ├── index.html
│   ├── package-lock.json
│   ├── package.json
│   ├── postcss.config.js
│   ├── tailwind.config.ts
│   ├── tsconfig.app.json
│   ├── tsconfig.app.tsbuildinfo
│   ├── tsconfig.json
│   ├── tsconfig.node.json
│   ├── tsconfig.node.tsbuildinfo
│   ├── vercel.json
│   └── vite.config.ts
└── ml_service
    ├── Procfile
    ├── main.py
    ├── model.pkl
    ├── model.py
    ├── requirements.txt
    └── scaler.pkl

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🚀 Installation & Setup

Prerequisites

• Node.js v18+
• Python 3.9+
• MongoDB Atlas account
• OpenWeather API key

1. Clone the Repository

git clone https://github.com/Mokshith08/OceanGuard.git
cd OceanGuard

2. Backend Setup

cd backend
npm install
cp .env.example .env   # Fill in your environment variables
node server.js

3. ML Service Setup

cd ml_service
pip install -r requirements.txt
uvicorn main:app --host 0.0.0.0 --port 8001 --reload

4. Frontend Setup

cd frontend
npm install
cp .env.example .env   # Fill in your environment variables
npm run dev

Frontend runs at http://localhost:5173 Backend runs at http://localhost:5000 ML Service runs at http://localhost:8001

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📡 API Endpoints

🔐 Authentication

Method	Endpoint	Description
POST	/api/auth/signup	Register new user
POST	/api/auth/login	Login & send OTP
POST	/api/auth/verify-otp	Verify OTP & get JWT

🌊 Risk Prediction

Method	Endpoint	Description
GET	/api/risk/predict/:city	Get marine risk for a city

💰 Profit Calculator

Method	Endpoint	Description
POST	/api/profit/calculate	Calculate fishing profit

📬 Contact

Method	Endpoint	Description
POST	/api/contact	Submit contact form

📊 Dashboard

Method	Endpoint	Description
GET	/api/dashboard	Get analytics & risk trends

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🤖 ML Model Details

Model: Random Forest Classifier

Property	Details
Algorithm	Random Forest
Framework	scikit-learn
API	FastAPI (Python)
Output	safe / moderate / dangerous

Input Features

features = [
    "wind_speed",       # Wind speed in m/s
    "wave_height",      # Estimated wave height
    "weather_code",     # OpenWeather condition code
    "day_of_week",      # 0 = Monday, 6 = Sunday
    "is_daytime",       # 1 = day, 0 = night
]

Hybrid Prediction Logic

If ML confidence > threshold:
    Use ML prediction
Else:
    Fallback to rule-based system
        wind_speed > 10  →  dangerous
        wind_speed > 6   →  moderate
        else             →  safe

Additional Details

• ⚖️ Class balancing applied during training to handle imbalanced risk data
• 📏 StandardScaler used for feature normalization
• 🔄 Model persistence via joblib for fast inference

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📸 Screenshots

🖥️ Dashboard

🌊 Risk Prediction

🔐 Login Page

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🔮 Future Improvements

• 🧠 Advanced ML Models — XGBoost, LSTM for time-series risk forecasting.
• 📡 Real-time IoT Integration — Live sensor data from marine buoys.
• 📱 Mobile App — React Native app for fishermen on the go.
• 🗺️ Geo-mapping — Interactive risk heatmaps using Mapbox/Leaflet.
• 🌐 Multi-language Support — Regional language support for fishermen.
• 📶 Offline Mode — PWA support for low-connectivity areas.
• 💳 Payment Integration — Payment integration for subscription.
• 🔔 Alert and notification system — Fisherman gets alert before going to sea.
• 🤖 AI chatbot - AI chatbot for OceanGuard.

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👨‍💻 Author

Mokshith GitHub

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📄 License

This project is licensed under the MIT License — see the LICENSE file for details.

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Made with ❤️ and ☕ for the fishing communities of India 🇮🇳
OceanGuard — Navigate Smarter. Fish Safer. 🌊