This project is an AI-powered plant disease prediction tool utilizing Convolutional Neural Networks (CNN). It is specialized for identifying diseases in maize, potato, tomato, and rice crops, helping farmers and agricultural professionals detect and manage crop diseases early.

The Crop Health Management and Monitoring project harnesses the power of machine learning to provide a comprehensive solution for farmers and agricultural professionals. This system offers real-time monitoring, predictive analytics, and actionable insights to help maintain optimal crop health.

🚀 A scalable Python backend for an AI chatbot built for agriculture and aquaculture. It delivers real-time insights on crops, pest detection, and fish farming. With secure APIs and modular design, it integrates seamlessly into apps, empowering farmers 🌱 and businesses to boost productivity, efficiency, and sustainability.

This repository features the development of an AgroTech Solutions system. It includes a data-driven crop recommendation system, offering guidance on optimal fertilizer usage based on soil conditions, and an integrated solution for early detection of crop diseases.

Welcome to Ka-Halaman! Version 1 serves as the foundational prototype, crafted to showcase structuring of agricultural data.

🌾 Empowering farmers through technology - A React/TypeScript platform connecting farmers directly with buyers, featuring real-time pricing, government schemes, and comprehensive farming tools

Protect your corn crops from Southern Rust with our Corn Rust Disease Risk Detector. Get instant risk predictions using ZIP code, weather, and crop stage. Export results as CSV or PDF and make informed decisions about fungicide application or early harvest.

🌊 Streamline water management with Aquanex-Server, a robust tool for monitoring and analyzing aquatic data efficiently.