Getting Started

Welcome to JalRakshak.AI

Real-time water quality monitoring powered by LoRaWAN, AI predictions, and IoT sensors. Monitor pH, TDS, temperature, turbidity, and conductivity with intelligent safety analysis.

LoRaWAN
The Things Network
Real-time Monitoring
Next.js 16
ESP32
AI Predictions

What is JalRakshak.AI?

JalRakshak.AI is an advanced IoT-based water quality monitoring system that combines hardware sensors with AI-powered predictions to provide real-time insights into water safety. The system uses LoRaWAN for long-range, low-power communication, making it ideal for remote water sources.

Hardware Components

  • ESP32 microcontroller (30-pin dev board)
  • LoRa SX1276 radio module (868 MHz)
  • pH sensor with analog probe
  • TDS (Total Dissolved Solids) sensor
  • DS18B20 waterproof temperature probe
  • OLED display (128×64 SSD1306)

Software Stack

  • Next.js 16 with App Router
  • MongoDB with Prisma ORM
  • The Things Network (TTN) integration
  • Python FastAPI for AI predictions
  • TypeScript fallback prediction engine
  • Real-time dashboard with Recharts

Key Features

Real-time Monitoring

Monitor water quality parameters in real-time with 60-second intervals. View live data, historical trends, and instant alerts on unsafe conditions.

AI-Powered Predictions

Random Forest Classifier trained on 3,276+ samples provides safety scores, risk analysis, root cause detection, and actionable recommendations.

LoRaWAN Connectivity

Long-range (up to 15 km), low-power communication via The Things Network. Perfect for remote water sources with extended battery life.

Analytics Dashboard

Beautiful, responsive dashboard with device cards, sensor history charts, live stats, and interactive AI model simulator.

Quick Start Guide

1

Installation & Setup

Install Arduino IDE, ESP32 board package, and required libraries (MCCI LoRaWAN LMIC, DallasTemperature, Adafruit SSD1306).

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2

Hardware Assembly

Connect LoRa module, sensors (pH, TDS, DS18B20), and OLED display to ESP32 following the pin diagram.

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3

TTN Configuration

Create TTN account, register application, add end device with OTAA, and configure uplink decoder.

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4

Code Generation & Upload

Use the Arduino code generator to create custom firmware with your TTN credentials, then flash to ESP32.

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5

Deploy & Monitor

Deploy your sensor node, verify webhook integration, and start monitoring water quality on the dashboard.

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System Requirements

Development Environment

Arduino IDE
v2.0+
ESP32 Board Package
v2.0+
Node.js
v18+
MongoDB
v5.0+

Hardware Requirements

Microcontroller
ESP32
LoRa Module
SX1276/78
Power Supply
3.7V LiPo
TTN Gateway Coverage
Required

Ready to Get Started?

Follow the installation guide to set up your first water quality monitoring node.