Nandu-hub-jpg/OptiCrop

# 🌱 OptiCrop – Smart Agricultural Production Optimization Engine ## 📌 Project Overview OptiCrop is a Machine Learning-based agricultural recommendation system that helps farmers select the most suitable crop based on soil nutrients and environmental conditions. The system analyzes soil Nitrogen (N), Phosphorus (P), Potassium (K), temperature, humidity, pH, and rainfall to recommend the best crop for cultivation. The project aims to improve agricultural productivity, reduce resource wastage, and support data-driven farming decisions. --- ## 🎯 Problem Statement Farmers often face difficulties in selecting the right crop for their land due to changing climatic conditions and varying soil characteristics. Incorrect crop selection can lead to poor yields and financial losses. OptiCrop addresses this problem by using machine learning algorithms to predict the most suitable crop based on soil and weather parameters. --- ## ✨ Features - Crop recommendation based on soil and climate conditions - Machine Learning powered prediction engine - User-friendly web interface - Real-time crop prediction - Data preprocessing and model evaluation - Model serialization using Joblib - Flask-based backend API - Responsive frontend using HTML, CSS, and JavaScript --- ## 🛠️ Technology Stack ### Frontend - HTML5 - CSS3 - JavaScript ### Backend - Flask ### Machine Learning - Scikit-Learn - Pandas - NumPy ### Data Visualization - Matplotlib - Seaborn ### Model Storage - Joblib ### Development Environment - Python 3.9+ - VS Code --- ## 📂 Repository Structure ```text opticrop/ │ ├── data/ │ └── Crop_recommendation.csv │ ├── models/ │ ├── crop_model.joblib │ └── scaler.joblib │ ├── static/ │ ├── style.css │ └── script.js │ ├── templates/ │ └── index.html │ ├── app.py ├── train.py ├── requirements.txt ├── README.md │ ├── Brainstorming & Ideation.pdf ├── Requirement Analysis.pdf ├── Project Design Phase.pdf ├── Project Planning Phase.pdf ├── Project Development Phas …