ECOSOIL - AI BASED FARMING

This repository contains the code for a crop recommendation system that uses machine learning models to predict the best crop to cultivate based on soil conditions and environmental factors. The system also provides fertilizer recommendations and cropping techniques to optimize crop yield.

Prerequisites

To run the code, you will need the following:

• Python 3.6 or later
• NumPy
• Pandas
• Scikit-learn
• Flask
• Pickle

Installation

To install the required dependencies, run the following command in your terminal:

pip install -r requirements.txt

Usage

To run the crop recommendation system, follow these steps:

1. Clone the repository to your local machine.
2. Open the app.py file in a text editor.
3. Replace the model.pkl, standscaler.pkl, minmaxscaler.pkl, and classifier.pkl file paths with the paths to the corresponding files on your local machine.
4. Save the app.py file.
5. Open a terminal window and navigate to the directory where the app.py file is located.
6. Run the following command to start the Flask application:

flask run

The crop recommendation system will now be running on localhost:5000. You can access the system by opening a web browser and navigating to http://localhost:5000.

Features

The crop recommendation system has the following features:

• Crop recommendation: The system uses a machine learning model to predict the best crop to cultivate based on soil conditions and environmental factors.
• Fertilizer recommendation: The system provides fertilizer recommendations based on the predicted crop and soil conditions.
• Cropping techniques: The system provides cropping techniques to optimize crop yield.

Screenshots & Videos

me.mp4

Conclusion

The crop recommendation system is a powerful tool that can help farmers optimize their crop yields. The system is easy to use and can be accessed from any device with an internet connection.