CropCare AI is a precision diagnostics tool designed to help farmers, particularly in India and Kerala, identify plant diseases and get instant, context-aware treatment protocols. By leveraging Google's Gemini AI and real-time weather data, it provides expert-level agricultural advice to minimize crop loss and improve yields.
- AI-Powered Disease Detection: Analyze crop leaf images using Gemini 3 Flash to identify diseases, pests, and nutrient deficiencies.
- Context-Aware Advice: Integrates real-time weather data (via wttr.in) to provide localized treatment recommendations.
- Community Forum: A real-time discussion platform for farmers to share knowledge and get help from the community.
- Analysis History: Securely save and manage your crop analysis history with Firebase.
- Responsive Design: A modern, mobile-first interface with dark mode support, built with Tailwind CSS 4.
- Gemini 3 Flash (
gemini-3-flash-preview)
The Gemini 3 Flash model is the core engine of CropCare AI. When a user uploads a crop image, the model:
- Identifies the Plant: Recognizes the crop species (e.g., Coconut, Rubber, Paddy, Pepper).
- Detects Issues: Analyzes the leaf for signs of disease, pests, or nutrient stress.
- Assesses Severity: Provides a severity rating (Low, Medium, High).
- Recommends Treatment: Generates detailed organic and chemical treatment protocols, including specific products and application methods.
- Frontend: React 19, Vite 6, Tailwind CSS 4, Motion (Animations)
- Backend: Firebase (Authentication, Firestore)
- AI Integration: Google GenAI SDK (@google/genai)
- Icons: Lucide React
# Clone the repository
git clone https://github.com/nozarash1/CropCare-AI
# Go to project folder
cd cropcare-ai
# Install dependencies
npm install
# Run the development server
npm run devThis project is licensed under the Apache-2.0 License.