NammaLakes Documentation

This repository contains the Docusaurus-powered documentation for the NammaLakes project, an IoT-based lake monitoring system.

Table of Contents

• Introduction
• Getting Started
• Project Structure
• System Architecture
• System Design

Introduction

NammaLakes is an IoT-based lake monitoring system that tracks water quality, pollution levels, and environmental changes in real time. The system integrates IoT sensors, cloud storage, and a web-based dashboard to help authorities monitor water bodies effectively.

This documentation provides an overview of the architecture, implementation, and deployment of the system.

Getting Started

Follow these steps to set up and run NammaLakes locally.
Start the Development Server
Navigate to the project directory and run:

npm i
npm run start      

This will start a local development server at http://localhost:3000/.

Useful Commands:
Clone the repository:

git clone https://github.com/NammaLakes/NammaLakes.git  

Navigate into the project directory:

cd NammaLakes  

Install dependencies:

npm install 

Project Structure

The NammaLakes repository is structured as follows:

/NammaLakes  
│── docs/                    # Documentation files (Markdown)  
│── src/                     # Custom components  
│── static/                  # Static assets  
│── docusaurus.config.ts      # Docusaurus configuration  
│── sidebars.ts               # Sidebar structure  
│── package.json              # Project dependencies  
│── README.md                 # Documentation overview  

System Architecture

The NammaLakes system consists of the following key components:
Frontend: React+Vite (Dashboard), Docusaurus (Documentation) Backend: FastAPI
Database: PostgreSQL IoT Devices: ESP8266 (NodeMCU) / Raspberry Pi
Deployment: Docker, AWS/GCP

Key Features:

• Real-time data collection from multiple sensors.
• Alerts & notifications for abnormal conditions.
• Map integration for sensor locations.
• REST API & MQTT for seamless integration.

System Design

The system consists of multiple IoT sensors deployed across lakes, communicating with a centralized backend that processes and visualizes the data.
IoT Sensors: Measure parameters like pH, turbidity, temperature.
Edge Processing: Data is filtered before transmission.
Cloud Backend: Stores and processes sensor data.
Dashboard: Interactive web UI for visualization.