𝘼𝙄-𝘽𝙖𝙨𝙚𝙙 𝙎𝙢𝙖𝙧𝙩 𝘾𝙧𝙤𝙥 𝙍𝙚𝙘𝙤𝙢𝙢𝙚𝙣𝙙𝙖𝙩𝙞𝙤𝙣 𝙎𝙮𝙨𝙩𝙚𝙢

🌾 Overview

The AI-Based Real-Time Crop Risk Prediction System is a smart agriculture web application designed to help farmers make informed decisions using Artificial Intelligence and real-time environmental data. The system predicts crop risk levels by analyzing weather conditions, soil parameters, and historical agricultural data to reduce crop loss and improve farming productivity.

🏗️ System Architecture

This project aims to support sustainable farming practices through an easy-to-use and multilingual platform with real-time insights and guidance.

🚀 Features

✅ Real-time crop risk prediction using Machine Learning

🌦️ Live weather analysis using OpenWeather API

🌱 Soil and environmental parameter evaluation

🌐 Multilingual support (English & Tamil)

📊 Interactive dashboard with charts and notifications

🏛️ Government schemes and agricultural support information

📦 Live stock availability updates

📚 Beginner-friendly cultivation guidance

📱 Responsive and user-friendly interface

🛠️ Tech Stack

Frontend

HTML5

CSS3

JavaScript

Chart.js

Backend

Python

Flask

Machine Learning

Scikit-learn Pandas NumPy APIs & Tools OpenWeather API

⚙️ System Workflow

Farmer accesses the web application

System fetches real-time weather data

User selects crop and location

Backend processes environmental inputs

Machine Learning model predicts crop risk level

Results are displayed using charts and color indicators

Additional farming guidance and government schemes are shown

📈 Machine Learning Model

The system uses Machine Learning algorithms such as:

Random Forest Classifier

Classification-based crop risk prediction

Risk Levels

🟢 Low Risk

🟡 Medium Risk

🔴 High Risk

🎯 Project Objectives

Reduce crop loss through early risk prediction

Improve agricultural decision-making

Provide real-time farming assistance

Increase awareness of government agricultural schemes

Support beginner and small-scale farmers

📂 Project Structure

AI-Crop-Risk-Prediction/

│

├── static/ # CSS, JS, Images

├── templates/ # HTML templates

├── model/ # ML model files

├── dataset/ # Training datasets

├── app.py # Flask application

├── requirements.txt # Dependencies

├── README.md

└── .gitignore

▶️ Installation & Setup

1️⃣ Clone the Repository

git clone https://github.com/your-username/AI-Crop-Risk-Prediction.git

cd AI-Crop-Risk-Prediction

2️⃣ Create Virtual Environment

python -m venv venv 3️⃣ Activate Virtual Environment

Windows

venv\Scripts\activate

Linux / Mac

source venv/bin/activate

4️⃣ Install Dependencies

pip install -r requirements.txt

5️⃣ Run the Application

python app.py

📊 Future Enhancements

Mobile application support

AI-based fertilizer recommendation

Crop disease detection using Deep

IoT sensor integration

SMS alert system for farmers

💛Contribution

Contributions and suggestions are welcome. Feel free to fork the repository and submit pull requests.

📜 License

This project is developed for educational and research purposes.(MIT License)

👨‍💻 Author

Vishal P AI & Web Development Enthusiast | Smart Agriculture Projects | Machine Learning Developer