AgriNova AI

AI-powered plant disease detection and smart farming assistant for faster, smarter crop care.

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Inspiration Agriculture plays a vital role in global food production, yet many farmers face challenges in identifying plant diseases early and getting quick expert guidance. These delays often lead to reduced crop yield and financial loss. We were inspired to build AgriNova AI to bridge this gap by using artificial intelligence to make plant disease detection and agricultural guidance more accessible, fast, and user-friendly.

What it does AgriNova AI is an AI-powered agricultural assistant that helps users in two main ways: 🌿 Plant Disease Scanner: Users can upload images of plant leaves, and the system detects possible diseases and provides suggestions for treatment. 💬 AI Plant Assistant Chatbot: Users can ask agriculture-related questions and receive instant AI-generated responses. It also includes a secure JWT-based authentication system for safe login and user management. The chatbot is powered using the Grok API from xAI.

How we built it

We built AgriNova AI using a full-stack architecture: Frontend for user interaction (chatbot interface + image upload system) Backend API for handling authentication and requests AI integration for chatbot responses Image processing workflow for disease detection JWT authentication for secure user sessions We connected the frontend with AI services and backend APIs to create a smooth real-time experience.

Challenges we ran into One of the main challenges was integrating AI responses efficiently without affecting performance or response time. Another challenge was handling image uploads and ensuring consistent results from the disease detection feature. We also faced difficulties in managing authentication flow and API communication between frontend and backend.

Accomplishments that we're proud of We are proud of successfully building a system that combines: AI chatbot assistance Image-based disease detection Secure authentication system Creating a unified platform that brings all these features together in a simple interface was a major achievement for us.

What we learned Through this project, we learned: How to integrate AI APIs into real-world applications How image-based disease detection systems work How to implement secure authentication using JWT How to build scalable full-stack applications with AI features

What's next for AgriNova AI In the future, we plan to improve AgriNova AI by: Increasing accuracy of plant disease detection models Adding more crop types and disease datasets Introducing real-time crop monitoring features Building a mobile application for wider accessibility Enhancing AI chatbot with more agricultural knowledge

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