Discover the perfect crop for your land with intelligent agricultural analysis
A joint effort by Swapna Kondapuram and Deep Das, 3rd year undergraduates at NIT Surat
CropVision is an innovative web application that leverages artificial intelligence to provide farmers and agricultural professionals with data-driven crop recommendations. By analyzing multiple environmental and soil parameters, the platform suggests the most suitable crops for specific land conditions, helping optimize agricultural productivity and sustainability.
- 🔍 Intelligent Crop Analysis - Advanced algorithm considering 7 critical parameters
- 📊 Comprehensive Dashboard - Track predictions, success rates, and field analytics
- 📈 Real-time Analytics - Visual insights into crop distribution and trends
- 👤 User Authentication - Secure login and personalized experience
- 🎨 Beautiful UI/UX - Modern, responsive design with smooth animations
- 📱 Mobile Responsive - Optimized for all device sizes
- 💾 Data Export - Download prediction data and analytics
CropVision analyzes seven crucial agricultural parameters to make accurate crop predictions:
- 🌧️ Rainfall (mm) - Monsoon patterns and water availability
- 🌡️ Temperature (°C) - Climate conditions and thermal requirements
- 💨 Humidity (%) - Atmospheric moisture levels
- ⚛️ Phosphorous (kg/ha) - Root development and flowering nutrients
- ⚡ Potassium (kg/ha) - Plant disease resistance and stress tolerance
- 🧪 Nitrogen (kg/ha) - Vegetative growth and chlorophyll production
- 🔬 pH Value (0-14) - Soil acidity/alkalinity balance
- 🌾 Rice - Optimal for high rainfall and warm climates
- 🌾 Wheat - Perfect for cool temperatures and moderate water
- 🌽 Maize - Ideal for warm conditions with good nitrogen levels
- 🌿 Cotton - Suitable for high potassium and warm weather
- 🫘 Soybean - Thrives in balanced pH and moderate conditions
- 🍅 Tomato - Requires high nutrients and controlled environment
- 🥬 Mixed Vegetables - Versatile options for diverse conditions
- Node.js (v16 or higher)
- npm or yarn package manager
- Modern web browser
-
Clone the repository
git clone https://github.com/your-username/cropvision.git cd cropvision -
Install dependencies
npm install
-
Start development server
npm run dev
-
Open in browser
http://localhost:5173
npm run build
npm run preview- React 18.3.1 - Modern UI library with hooks
- TypeScript 5.5.3 - Type-safe JavaScript development
- Vite 5.4.2 - Fast build tool and development server
- Tailwind CSS 3.4.1 - Utility-first CSS framework
- Lucide React - Beautiful icon library
- Custom CSS Animations - Smooth transitions and effects
- ESLint - Code linting and formatting
- PostCSS - CSS preprocessing
- Autoprefixer - CSS vendor prefixing
- Storytelling Interface - Each parameter input tells an agricultural story
- Real-time Feedback - Instant insights on soil conditions
- Animated Transitions - Smooth, engaging user interactions
- Progress Tracking - Visual step-by-step journey
- Prediction Confidence - AI-calculated accuracy scores
- Historical Trends - Track prediction patterns over time
- Crop Distribution - Visual breakdown of recommended crops
- Success Rate Monitoring - Performance analytics
- Secure Authentication - Email/password login system
- Profile Management - Customizable user settings
- Data Persistence - Local storage for user preferences
- Account Export - Download personal data
- Real-time Weather - Current conditions display
- Field Management - Track multiple agricultural areas
- Recent Predictions - Quick access to latest recommendations
- Performance Metrics - Success rates and statistics
Beautiful, animated landing page with crop-themed visuals and smooth transitions.
Step-by-step parameter input with real-time feedback and agricultural storytelling.
Detailed analysis results with confidence scores, growing tips, and market insights.
Comprehensive data visualization with charts, trends, and performance metrics.
We welcome contributions to CropVision! Here's how you can help:
- Fork the repository
- Create a feature branch (
git checkout -b feature/amazing-feature) - Commit your changes (
git commit -m 'Add amazing feature') - Push to the branch (
git push origin feature/amazing-feature) - Open a Pull Request
- Follow TypeScript best practices
- Use Tailwind CSS for styling
- Write meaningful commit messages
- Test on multiple browsers
- Ensure responsive design
This project is licensed under the MIT License - see the LICENSE file for details.
Swapna Kondapuram & Deep Das
3rd Year Undergraduate Students
National Institute of Technology (NIT), Surat
Bridging the gap between technology and agriculture through innovative solutions
- NIT Surat - For providing the educational foundation
- Agricultural Research Community - For crop science insights
- Open Source Community - For the amazing tools and libraries
- React & TypeScript Teams - For the robust development platform
For questions, suggestions, or collaboration opportunities:
- 📧 Email: contact@cropvision.app
- 🐙 GitHub: CropVision Repository
- 🎓 Institution: National Institute of Technology, Surat
Made with ❤️ for sustainable agriculture
CropVision - Empowering farmers with AI-driven insights
