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EchoAgri is an advanced agricultural platform designed to harness the power of technology to improve farming practices. This project integrates IoT devices and machine learning algorithms to monitor and manage various agricultural processes, providing farmers with actionable insights.

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EchoAgri

EchoAgri is an advanced agricultural platform designed to harness the power of technology to improve farming practices. This project integrates IoT devices and machine learning algorithms to monitor and manage various agricultural processes, providing farmers with actionable insights to optimize crop yield and resource management.

Features

  • Real-Time Monitoring: Use IoT devices to collect data on soil moisture, temperature, humidity, and other environmental factors.
  • Data Analytics: Analyze collected data to provide insights and recommendations for crop management.
  • Predictive Modeling: Utilize machine learning models to predict crop yields and identify potential issues before they become problems.
  • Resource Management: Optimize the use of water, fertilizers, and other inputs based on real-time data.
  • Remote Access: Access and monitor farm data remotely through a user-friendly dashboard.
  • Alerts and Notifications: Receive alerts and notifications for critical events and recommended actions.

Technologies Used

  • Backend: Python, Django
  • Frontend: HTML, CSS, JavaScript
  • Database: SQLite3
  • IoT Integration: Various sensors and IoT devices for data collection
  • Machine Learning: Scikit-learn for predictive analytics
  • Real-Time Data: WebSockets for real-time data transmission

Installation and Setup

Prerequisites

  • Python 3.x
  • pip (Python Package Installer)
  • IoT devices (temperature sensors, soil moisture sensors, humidity sensors, etc.)

Steps

  1. Clone the Repository

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    git clone https://github.com/NagiPragalathan/EchoAgri.git cd EchoAgri

  2. Install Dependencies

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    pip install -r requirements.txt

  3. Configure IoT Devices

    Ensure that your IoT devices are properly configured and connected to the system. Follow the device-specific instructions to set up data transmission to the EchoAgri platform.

  4. Run Migrations

    bash

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    python manage.py migrate

  5. Start the Development Server

    bash

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    python manage.py runserver

  6. Open the Platform

    Open your browser and navigate to http://localhost:8000 to access EchoAgri.

Project Structure

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EchoAgri/ ├── assets/ │ ├── images/ │ └── sounds/ ├── css/ │ └── style.css ├── js/ │ └── main.js ├── templates/ │ ├── base.html │ ├── dashboard.html │ ├── login.html │ ├── register.html │ ├── monitor.html │ └── analytics.html ├── echoagri/ │ ├── __init__.py │ ├── settings.py │ ├── urls.py │ ├── wsgi.py │ └── asgi.py ├── manage.py ├── requirements.txt └── README.md

Usage

  • Dashboard: View a summary of farm conditions and upcoming tasks.
  • Real-Time Monitoring: Access real-time data from connected IoT devices.
  • Data Analytics: View detailed analysis and recommendations based on collected data.
  • Predictive Modeling: Get predictions on crop yields and potential issues.
  • Resource Management: Manage and optimize resource use based on real-time data and insights.

IoT Integration

EchoAgri integrates with various IoT devices to collect real-time agricultural data. The data is securely transmitted and displayed on the platform, allowing farmers to make informed decisions and optimize their operations.

Supported IoT Devices

  • Temperature Sensors
  • Soil Moisture Sensors
  • Humidity Sensors
  • Other compatible agricultural monitoring devices

Contribution

Contributions to the EchoAgri project are welcome! If you would like to contribute, please fork the repository and submit a pull request with your changes.

License

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

About

EchoAgri is an advanced agricultural platform designed to harness the power of technology to improve farming practices. This project integrates IoT devices and machine learning algorithms to monitor and manage various agricultural processes, providing farmers with actionable insights.

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