AI-Based Precision Crop Recommendation Using Soil, Environmental, and Market Intelligence
Github Link:https://github.com/Ramseshu24221/AI-POWERE...
Description: AI-Based Crop Recommendation System
Overview
This project presents an intelligent crop recommendation system that integrates soil data, environmental conditions, and market insights using Artificial Intelligence techniques.
The system aims to assist farmers in selecting the most suitable crop to maximize productivity and profitability.
Features
Multi-source data fusion (soil, climate, market data)
Machine Learning model for crop prediction
User-friendly interface
Data-driven decision support
Scalable and adaptable architecture
Technologies Used
Python
Machine Learning (Random Forest)
Pandas, NumPy
Scikit-learn
Matplotlib / Seaborn
Dataset
The dataset includes:
Soil parameters (N, P, K, pH)
Environmental data (temperature, humidity, rainfall)
Market-related information
Project Structure
data/ – Dataset files
models/ – Trained models
src/ – Source code
notebooks/ – Jupyter notebooks
README.md – Project documentation
Installation
Clone the repository
Install dependencies using:
pip install -r requirements.txt
Run the project
Usage
Input soil and environmental parameters
The model predicts the most suitable crop
Results help in decision-making
Results
The model provides accurate crop recommendations based on integrated data sources.
It improves agricultural decision-making and supports sustainable farming practices.
Future Work
Integration with real-time IoT sensors
Mobile application development
Advanced deep learning models
Market price prediction enhancements
Contributors
Your Name
Team Members
License
This project is licensed under the MIT License. # AI-POWERED-CROP-RECOMMENDATION-BASED-ON-ENVIRONMENTAL-DATA-AND-MARKET-TRENDS