Smart Agriculture
Practical AI for agriculture: disease detection workflow built for fast field decisions.
Next.jsReactNode.jsExpressGemini APIMongoDBJWT
AI IntegrationComputer Vision WorkflowAuthenticationProduct UX
Overview
Smart Agriculture helps users upload crop images, receive AI-powered disease analysis, and track previous predictions. The product combines a simple frontend workflow with secure backend services for repeated use.
Problem
Farmers and operators often need diagnosis quickly, but expert access can be delayed and decision quality drops without a reliable first-pass signal.
Solution
I implemented a full-stack prediction pipeline with image validation, Gemini integration, and authenticated history so users can compare outcomes and make faster decisions.
Impact
- Reduced friction from image upload to prediction result in a single guided flow.
- Improved trust with authenticated history and stable API error/loading states.
- Connected AI inference to practical user actions instead of a standalone demo model.
Features
- Leaf image upload with validation and processing safeguards
- Gemini-based disease prediction service integration
- JWT-secured user accounts and protected endpoints
- Prediction history per user for comparison and follow-up
- Clear loading, empty, and failure states in the UI