🌱 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. 🚜🌾

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.

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.

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.

Machine learning project

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.

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.

AI-Powered Plant Doctor 🌿🤖 – A deep learning model that diagnoses plant diseases from images and provides remedies. Uses computer vision & AI to detect common plant issues and recommend treatments, helping home gardeners and farmers maintain healthy plants.

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

🌿 AI-powered mobile app for tomato disease detection using image analysis. Empowering farmers with early diagnosis, treatment recommendations, and better yields. 🚀🌱

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

FarmerHub – A full-stack agri-commerce platform connecting farmers, sellers, and consumers with smart dashboards, order management, and AI-powered crop insights.

Boost farm profitability with the AI Export Market Profit Predictor WordPress plugin. Analyze production costs, forecast export prices, and make smarter crop marketing decisions with PDF and CSV report exports.

A complete, end-to-end modernisation of a legacy greenhouse labour tracking system. This project includes reproducible data cleaning pipelines, exploratory data analysis, feature engineering, machine learning modelling, and reporting—implemented using Python, Jupyter notebooks, and a modular src/ package structure.

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.

A Flutter-based mobile app for Agribot Hydro NFT, designed for hydroponic farm management, automation controls, and real-time data monitoring.

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

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.

An end-to-end data pipeline using SQL and Python to optimize agricultural yields in Maji Ndogo.

A Django-based e-farming shopping system with product, cart, order, and payment management.