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Projects
Selected software projects, web systems, product concepts, and academic tools. These entries are written as archive records, not promotional pages.
Projiz
A digital services identity for modern web solutions
Projiz is a digital identity created to present services, modern web solutions, and practical digital work under one clear name. It is not treated as only a website, but as a growing project space that gives the service side of my work a more defined shape. Through Projiz, digital ideas can be introduced in a professional way, from web experiences and technical solutions to future client work and product-oriented services. In my portfolio, it represents the part of my work that connects technical development with service thinking, visual direction, and clear public communication.
Akademyati
An online learning platform for instructors and students
Akademyati is an online learning platform built around the connection between instructors and students. The project gives instructors a place to create and present courses, while students can discover learning content and join courses that match their interests or study needs. It is designed as an academic digital environment where educational content, course access, and learning participation can exist in one organized platform. In my portfolio, Akademyati represents a larger education-focused project direction: a system that connects teaching, learning, and digital course delivery in a practical and accessible way.
Drone Detect
An AI-based drone detection project using YOLOv8
Drone Detect is an AI-based detection project focused on identifying drones from image input using a trained YOLOv8 model. The project is built around a practical detection flow: loading the model once, accepting an uploaded image, running inference, and returning detection results such as bounding boxes, confidence values, class information, and optional annotated output. It also includes local utilities for testing images, camera input, or video files, which makes the model easier to experiment with beyond a single request flow. Although the source code includes a FastAPI backend for integration and deployment, the main idea of the project is drone detection itself: turning a trained model into a usable detection workflow that can recognize drone presence from visual data.
Apps Gallery
A personal space for publishing selected apps
Apps Gallery is a personal publishing space where I collect and present the smaller apps, tools, and experimental pieces I create over time. The purpose of the project is not to explain every technical detail of each app, but to give these works a clear and accessible home outside of scattered links or isolated repositories. It acts as a lightweight extension of my main portfolio, especially for projects that are practical, exploratory, or limited in scope, but still represent part of my learning process and development journey. Through this space, each app can be introduced as a finished or evolving piece of work, with enough context for visitors to understand what it is, why it exists, and how it connects to the wider archive.
IoT Anomaly Detection
An applied AI project for detecting unusual behavior in IoT data
IoT Anomaly Detection is an applied AI project focused on identifying unusual behavior in Internet of Things data. The project is centered on Python-based model work, where IoT-related data is used to explore how abnormal patterns can be detected and separated from regular behavior. Rather than presenting itself as a complete monitoring product, it represents the model and experimentation side of anomaly detection, with attention to data preparation, training workflow, and the practical role of intelligent detection in connected environments. In my portfolio, this project connects machine learning with IoT security and reliability, showing how AI methods can support early detection of unexpected or suspicious behavior in device-based systems.
SmartShopping Recommendation System
An applied AI project for shopping recommendation logic
SmartShopping Recommendation System is an applied AI project focused on building recommendation logic for shopping-related suggestions. The project is mainly centered on Python-based model work rather than a complete shopping application, so its value comes from the process of preparing data, training recommendation behavior, and exploring how patterns in user or product information can support more relevant suggestions. In my portfolio, it represents a practical machine learning project connected to a real digital shopping scenario, showing how recommendation systems can be used to make product discovery more intelligent and context-aware.
Face Mask Detection
An image-based detection project for identifying face masks
Face Mask Detection is an image-based detection project built to identify face masks in selected image inputs using a locally trained YOLOv5 model. The project focuses on the practical detection workflow: preparing the environment, loading the trained model weights, running inference on images, and producing visual results that show where masks are detected. It includes a Python-based execution flow for testing images and a lightweight local upload interface for trying the model in a simple way. The project is not meant to be a full production system; it is a focused applied AI implementation that shows how a trained detection model can move from model files and test images into clear, visible output. Through this work, image processing, model inference, and detection results come together around one direct task: recognizing face masks inside images.
Enigma Machine Simulator
A simulator inspired by the Enigma machine and classical cryptography
Enigma Machine Simulator is a small web-based simulator created from my personal interest in cryptography and the mechanism of the Enigma machine. The Enigma machine was a historical cipher device used to encrypt and decrypt messages through rotating parts, internal wiring, and changing letter substitutions, which makes it interesting not only as a historical object, but also as a mechanical way to understand classical encryption. What attracted me to this project was not the size of the application, but the logic behind the machine: how a simple typed letter can pass through a sequence of transformations and return a different encrypted result. This project does not try to be a large platform or a complete cryptography tool; it is a focused simulator built to explore the machine’s idea, rebuild part of its behavior in software, and make its encryption process easier to observe through interaction. In my portfolio, it represents a compact project driven by curiosity, encryption history, and the desire to understand a famous cryptographic mechanism by turning its concept into something visible and usable.