🌾 AI Farming App

📄 Detailed Project Report (PPT)

You can view our complete project presentation here:
🔗 Google Drive - Project PPT

It is an intelligent mobile application that leverages Machine Learning and Deep Learning to improve agricultural practices. It supports:

• Crop Recommendation
• Crop Yield Prediction
• Rainfall Prediction
• Satellite Image Classification
• Ground-to-Satellite Image Mapping

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📱 Frontend

Built using:

• React Native
• Users can input crop-related data
• Displays intelligent predictions and insights
• Firebase used for:
  • Authentication
  • Real-time database

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🔧 Tech Stack

Layer	Technology
Frontend	React Native
Backend	Flask API
Database	Firebase
Satellite Data	Google Earth Engine (Sentinel-1)
ML Models	Scikit-learn (Random Forest)
DL Models	TensorFlow/Keras (Inception v3)

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🚀 How It Works

1. User opens the mobile app and enters farm/crop-related inputs.
2. App sends data to a Flask API backend.
3. Backend runs ML/DL models for prediction/classification.
4. Satellite data is fetched via Google Earth Engine for land/crop classification.

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📸 App Screenshots

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🧱 System Overview (ML and DL models)

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📊 Datasets Used

• Dataset 1: Crop Yield in Indian States
  🔗 Kaggle Link

• Dataset 2: Sentinel-1/2 Satellite Image Pairs (Terrain Segregated)
  🔗 Kaggle Link