AgriScan 🌾

AI-powered mobile crop-health scanner for smallholder farmers.
Detect diseases, get treatment recommendations, and track farm health in real-time.

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🚀 Mission

Empower farmers with affordable, instant crop diagnostics – using only a smartphone camera.

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🛠️ Tech Stack (Target Architecture)

• Flutter – Mobile App
• FastAPI / Python – Backend (AI API)
• Supabase / PostgreSQL – Database + Auth
• TensorFlow / PyTorch – Model Training
• Docker & CI/CD – Production pipeline

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📌 Core Features (MVP: 90 Days)

• Scan leaf → AI disease detection
• Treatment recommendations
• Farm logbook + image history
• SMS/Offline support (for rural areas)
• Admin dashboard (later phase)

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🌱 Public Roadmap (Build in Public)

• Q1 – Research + UI + Data Collection
• Q2 – AI Inference + MVP App
• Q3 – Pilot with Kenyan Farmers
• Q4 – Monetize (B2B + Co-ops)

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📍 Status

Current Version: v0.1 MVP

✅ Completed:

• TensorFlow Lite model integration for cassava leaf disease classification
• FastAPI backend with /api/v1/predict endpoint
• Flutter mobile app with camera integration
• Hive database for offline history and queueing
• Material 3 UI with clean, modern design
• CI/CD pipeline with GitHub Actions
• Automated tests for API and Flutter app

🚧 In Progress:

• Treatment recommendations
• SMS integration
• Admin dashboard

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🚀 Demo

Screenshots

Screen	Description
Scan Screen	Camera interface for capturing leaf images
History Screen	View all past scans with sync status

📸 Screenshots coming soon! Add them to /docs/ folder.

Quick Start

Backend:

cd api
pip install -r requirements.txt
python models/convert_to_tflite.py  # If needed
uvicorn app.main:app --reload

Mobile App:

cd app
flutter pub get
flutter packages pub run build_runner build  # Generate Hive adapters
flutter run

Run Tests:

# API tests
cd api
pytest tests/ -v

# Flutter tests
cd app
flutter test

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📄 License

MIT