Soil-Detector-Project

🌱 SoilGuard: AI Soil Quality Checker

📌 Overview

The SoilGuard: AI Soil Quality Checker is a Machine Learning-powered web application that predicts soil type from an uploaded image and provides:

✅ Best crops to grow
✅ Fertilizer recommendations
✅ Soil health analysis
✅ Watering tips
✅ Latest government schemes for farmers
✅ Agricultural news & weather updates

This project is designed to help farmers and agriculture enthusiasts make better decisions about soil and crop management.

🚀 Features

📷 Upload soil images to detect soil type.
🎯 ML-based prediction with confidence level.
🌾 Smart crop recommendations.
💧 Watering and fertilizer tips.
📰 Live agricultural news updates.
🌦 Weather forecast integration.
🏛 Government schemes information.

🛠️ Technologies Used

Frontend: HTML, CSS, Bootstrap, JavaScript
Backend: Python, Flask
Machine Learning: TensorFlow / Keras, Scikit-learn
Other Libraries: NumPy, Pandas, OpenCV, Matplotlib
Database (if any): MySQL
API Integrations:
- OpenWeather API (for weather updates)
- News API (for agricultural news)

📂 Project Structure

Soil-Detector-Project/ │– static/ # CSS, JS, Images │– templates/ # HTML files │– app.py # Flask backend │– model/ # Trained ML models │– dataset/ # Soil dataset (100MB) │– requirements.txt # Python dependencies │– README.md # Project documentation

⚙️ Installation & Usage

🔹 1. Clone Repository

git clone https://github.com/vaishnavibhutada/Soil-Detector-Project.git
cd Soil-Detector-Project

🔹 2. Create Virtual Environment & Install Dependencies

python -m venv venv
# Activate the virtual environment
# For Windows:
venv\Scripts\activate
# For Linux/Mac:
source venv/bin/activate

pip install -r requirements.txt