CropifyAI is a smart farming web application that empowers farmers with AI-driven crop recommendations, disease detection, financial tracking, and real-time advisories. The app is designed to work both online and offline, ensuring reliability in rural areas with poor internet connectivity.
- Landing Page
App working video & UI : Google Drive link.
- AI-powered Crop Recommendation: Suggests best crops based on soil, weather, and market data.
- Image-based Disease Detection with treatment suggestions
- Financial Tracking (expenses, income, profit calculation)
- Market Advisory with nearby prices and alerts
- Real-time Weather Dashboard with notifications
- Offline Support (queued actions + background sync)
- Multilingual Support (local language advisories)
- User Authentication & Multiple Farm Profiles
Frontend
- Next.js, React.js, TypeScript, Tailwind CSS
- React Hook Form
Backend
- Next.js API Routes
- Firebase Authentication
AI Components
- Genkit (Google Gemini)
- Custom ML models trained on crop, soil, and weather datasets
Database & Storage
- Firebase Firestore
- Firebase Cloud Storage
- LocalStorage + Service Worker
Deployment
- Vercel
- Farmer logs in via Firebase Auth.
- Inputs soil details + uploads crop image.
- Backend fetches soil, weather, and market data.
- AI Engine:
- Recommends best crops with yield & profit.
- Detects diseases from uploaded images.
- Advisory system translates results into local languages.
- Farmer receives results + treatment + market insights.
- Notifications alert about rainfall, pest outbreaks, or price changes.
- Offline support queues disease analysis & financial transactions in localStorage, syncing them when internet returns.
- Queued Actions in LocalStorage: Disease analysis & financial transactions stored locally when offline.
- Auto-Sync on Reconnect: Actions automatically synced with Firebase when internet returns.
- Service Worker: Handles caching & background sync for offline reliability.
- Kaggle – Crop & disease datasets
- ICAR – Indian Council of Agricultural Research
- FAO – Food and Agriculture Organization
Usage:
Datasets are used for AI model training (crop recommendation & disease detection). Market and weather data are fetched in real-time via APIs.
- Offline support with background sync
- AI-driven disease detection from images
- Integrated financial tracking & profit calculation
- Localized language advisory system
- Real-time weather + market alerts
| Challenge | Strategy |
|---|---|
| Poor internet connectivity | Offline support + background sync |
| Limited farmer digital literacy | Simple UI + multilingual support |
| Data accuracy for AI models | Continuous training with ICAR, FAO, Kaggle datasets |
| Trust & adoption | Localized advisory + transparent recommendations |
- Farmer logs in.
- Inputs soil data and uploads a crop image.
- AI engine processes and provides:
- Best crops + profit estimate.
- Detected disease with treatment.
- Results are displayed in farmer’s local language.
- Farmer tracks expenses & profits.
- Alerts sent for weather, pests, and market price changes.
- Node.js (v18 or above)
- npm or yarn
- Firebase account & project setup
- Clone the repository:
git clone https://github.com/your-username/cropifyai.git cd cropifyai - Install dependencies:
npm install
- Create a .env.local file in the root folder and add Firebase + API keys:
NEXT_PUBLIC_FIREBASE_API_KEY=your_api_key NEXT_PUBLIC_FIREBASE_AUTH_DOMAIN=your_auth_domain NEXT_PUBLIC_FIREBASE_PROJECT_ID=your_project_id NEXT_PUBLIC_FIREBASE_STORAGE_BUCKET=your_storage_bucket NEXT_PUBLIC_FIREBASE_MESSAGING_SENDER_ID=your_sender_id NEXT_PUBLIC_FIREBASE_APP_ID=your_app_id WEATHER_API_KEY=your_weather_api_key MARKET_API_KEY=your_market_api_key
- Run the development server:
npm run dev
- Open in browser:
http://localhost:3000
- Build for production:
npm run build npm start