Crop Recommendation System with APMC & Farmer Modules | ML Final Year Project Demo
Crop Recommendation System Using Machine Learning | Final Year Project Demo
This video demonstrates a Smart Crop Recommendation System developed using Machine Learning and Flask, designed for farmers, APMC markets, and administrators.
The system predicts the most suitable crop based on soil nutrients and climate conditions and manages crop selling through an APMC-based approval system.
🔹 Project Modules
👨💼 Admin Module
Admin Dashboard to monitor the entire system
Approve or reject APMC registrations
View farmer analytics and system statistics
Manage crop categories and subcategories
Set crop quality standards
View farmers and market details
🏪 APMC Module
Market dashboard
Manage crop categories
View farmer crop-selling requests
Approve or reject farmer requests
🌾 Farmer Module
Predict best crop using Machine Learning
Input parameters:
Nitrogen, Phosphorus, Potassium, Temperature, Humidity, pH, Rainfall
View crop recommendation results with probabilities
Send crop-selling requests to APMC
Track approval or rejection status
🧠 Machine Learning Model
Crop prediction using ML classification models
Trained on agricultural dataset
Uses ensemble techniques for better accuracy
Predicts the most suitable crop for given soil & climate conditions
🛠️ Technologies Used
Frontend: HTML, CSS, JavaScript, Bootstrap
Backend: Python Flask
Machine Learning: Scikit-learn, XGBoost
Database: SQLite
Deployment: Flask Web Application
📂 What You Will Get (After Purchase)
✔️ Complete Source Code
✔️ Trained ML Model
✔️ Project Report & PPT
✔️ Database Schema
✔️ Full Setup & Execution Support
📩 Contact to Buy This Project
📧 [email protected]
⚠️ This video is for demo purposes only. Source code and documentation are provided after purchase.
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Final Year ML Projects | AI in Agriculture | Flask Projects | Python Projects