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Smart Irrigation and Crops Monitoring System

Project Overview

The Smart Irrigation and Crops Monitoring System is an innovative IoT-based solution designed to empower farmers by automating farm monitoring, irrigation, and data management. This system not only tracks environmental parameters such as temperature, humidity, and soil moisture but also enables efficient irrigation control, plant health diagnosis, and agricultural tracking. The system is designed to help farmers optimize water usage, improve crop yield, and manage farming expenses effectively.


Features

1. Smart Irrigation

Automate, schedule, or manually control motor pumps using IoT for efficient water management, ensuring water is used only when necessary and at optimal times.

2. Real-Time Monitoring

Monitor soil fertility, moisture, and weather data via a Flutter app. This enables farmers to keep track of key factors that influence crop health and growth.

3. Precision Land Leveling

Use laser-guided systems to efficiently prepare the land for planting, ensuring uniformity and improved productivity.

4. Plant Health Diagnosis

Utilize advanced technology to detect plant diseases or conditions by analyzing the leaves, enabling timely intervention and treatment.

5. News and Updates

Receive timely national and international agricultural news and updates directly within the app to stay informed about the latest trends and technologies in agriculture.

6. Agricultural Tracking

Monitor and store data on farming expenses, fertilizers, crops, and other agricultural activities, providing clarity on investments and helping farmers make informed decisions.


Technologies Used

Hardware

  • ESP32: A powerful microcontroller for IoT integration.
  • DHT22: Temperature and humidity sensor.
  • LDR: Light-dependent resistor for measuring light intensity.
  • LED Bulb: For visual indicators of system status.
  • pH Sensor: To measure the soil pH level.
  • Pump Motor: For irrigation control.
  • IR Sensor: To detect presence or proximity of objects.
  • Soil Moisture Sensor: To monitor soil moisture levels.

Software

  • Arduino IDE: For programming the ESP32.
  • Python: For model developing and data management.
  • Node.js: For backend processing and building web-based APIs.
  • MongoDB: For storing sensor data and farming information.
  • Flutter: For building the mobile application for real-time monitoring.

Prerequisites

  • ESP32 development board.
  • DHT22, LDR, pH sensor, soil moisture sensor, and IR sensor.
  • Pump motor and relay for irrigation.
  • Raspberry Pi or similar for backend.
  • MongoDB instance set up for data storage.
  • Flutter development environment for the app.
  • Arduino IDE for ESP32 programming.

Team Members

  • Sanjib Shah: AI Developer
  • Sunil Nath: Backend Developer
  • Manish Paudel: IoT
  • Aman Sheikh: Flutter Developer

Installation

  1. Clone the repository:
    git clone https://github.com/IntelligentBeaver/Aahar-IOT-and-AI-based-Smart-Farming-System.git
    cd Aahar-IOT-and-AI-based-Smart-Farming-System

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