AI-powered plant disease detection system using deep learning. Upload plant images to instantly identify 30+ diseases across Apple, Corn, Grape, Potato, Tomato & more crops. Built with FastAPI + React TypeScript. Ready for cloud deployment.

🌱 An all-in-one intelligent system for farmers to get crop recommendations based on soil and weather data, and detect crop diseases from leaf images using machine learning. 🚜🌾

Real-time web dashboard for visualizing beehive metrics including temperature, humidity, weight, bee activity, and alerts. Built with React and Firebase, designed to work with ESP32-based Smart Beehive IoT monitoring hardware.

🌿 An AI-powered Android application built with Kotlin and Jetpack Compose. Utilizes Gemini AI for real-time plant disease identification and offers freemium treatment categorizations (Organic/Chemical) via Supabase and RevenueCat.

Integrated Agronomic Analytics: Combining Random Forest (ML) for regional wheat yield prediction and DeepLabV3+ (CV) for fine-grained plant organ segmentation. Includes an interactive Tableau dashboard.

A full-stack React application using Gemini 1.5 Flash for agricultural image analysis. Integrates OpenWeather API for localized treatment advice and Firebase for real-time community discussions and user data persistence.

AquaVera: Empowering farmers with a revolutionary, sustainable water management and irrigation request platform. Built with Jetpack Compose and Supabase to streamline agricultural resource allocation.

AI-powered livestock disease diagnostics using MobileNetV2 and Flask. Featuring a high-contrast Modern Brutalist UI for rapid, on-site skin condition analysis.

Web-based IoT livestock monitoring system integrating PHP, Supabase, and IoT sensors (ESP32, RFID, Load Cell) to track real-time livestock weight and health data with interactive dashboards.

🌾 AWS Serverless ELT: Agricultural & weather data pipeline with automated quality checks and Athena/BI integration.

An integrated deep learning framework designed to detect and predict agricultural pest infestations using image classification and object detection to improve crop management and minimize pesticide usage.

Neochloris: A plant disease detection app using deep learning, real-time camera analysis, and a rich disease library. Final project (Final Boss) from TIA Academy.

Sistema WMS multiunidade completo: API em microsserviços (Node.js/TS), Painel Administrativo (React) e App Mobile (React Native) com foco em escalabilidade e observabilidade.

A agriculture based web application to help the farmers. It helps users to predict rice crop diseases from a single image input, get instant quires with the help of out personalized chatbot & personalized API for seed calculation.

🧅 Professional market intelligence & price arbitrage platform for onion trading. Built with Laravel 11, PHP 8.3, and Tailwind CSS. Track, compare, and forecast.

Unified design spec for an LLM agent platform — architecture decisions, module boundaries, API contracts, and coding standards as a single source of truth.

Full-stack AI platform for precision agriculture using Rhizobium-based biofertilizers. Features ML-powered dosage prediction, real-time soil analysis with ESP32 sensors, and Gemini-powered agricultural chatbot.

[TÜBİTAK 2209-A] AI-based physical damage detection in agricultural products using hybrid (On-Device + Cloud) Deep Learning architectures.

Egg Roll Stability Analysis System — U2Net AI segmentation + 19 morphological features + SVM/RF/GBDT risk prediction. Streamlit web app.

An intelligent Machine Learning system designed to recommend the most suitable crops based on soil and weather parameters.