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Harvestify is an intelligent farming assistant designed to help farmers make data-driven agricultural decisions. The system uses machine learning, weather data, and soil parameters to provide accurate predictions and actionable recommendations for improving crop yield.

Key Features

Crop Recommendation:
Suggests the best crop to cultivate based on soil nutrients (N, P, K), pH, humidity, temperature, and rainfall using ML models like Random Forest or Decision Tree.

Fertilizer Recommendation:
Analyses soil deficiencies and recommends the right type and quantity of fertilizers.

Disease Prediction:
Uses image-based classification (CNN model) to detect crop diseases from leaf images and provides remedies.

Weather Forecast Integration:
Fetches real-time weather conditions and alerts farmers about unfavorable conditions.

Farmer-Friendly UI:
Simple web or mobile interface built using Flask, Django, or React to easily input soil data and receive predictions.

Technologies Used

Machine Learning: Random Forest, KNN, Logistic Regression

Deep Learning: CNN for image-based disease detection

Frontend: HTML, CSS, JavaScript or React

Backend: Python (Flask or Django)

Database: SQLite or MySQL

APIs: OpenWeather API for weather forecasts

Outcome

Helps farmers select the most profitable crop

Reduces crop loss by predicting diseases early

Improves soil nutrient management

Supports smart and sustainable farming practices