Istanbul, Türkiye
Hello! I am Engin AKGÜL. I worked as a Long-Term Intern at Proline Bilişim Sistemleri ve Tic. A.Ş. I graduated from Gazi University with a degree in Computer Engineering, and I am currently working in the field of Artificial Intelligence. I love working with new technologies and innovative projects. So far, I have completed a 5-month long-term internship and a 2-month summer internship, gaining in-depth knowledge in areas such as Artificial Intelligence, Image Processing, Backend, and Frontend development. I am particularly proud of the Facial Recognition and MRZ Code Recognition project using Artificial Intelligence, as it significantly contributed to my development. I am always focused on learning and growing in my career. In the future, I aim to work more on Artificial Intelligence and make a significant impact in this field. Outside of my professional life, I am interested in Hiking, Watching Documentaries, and Creative Writing. These interests inspire me in both my work and personal life. I look forward to connecting and exploring new opportunities together. Feel free to reach out to expand our professional network and develop collaborations. E-Mail: [email protected] github: https://github.com/engnakgul medium: https://medium.com/@enginakgul
During my long-term internship in the Electronic Identification and Biometrics department, I developed a project focused on e-ID and facial recognition technologies. In this project, I actively used React, JavaScript, HTML, CSS, Python, and Java. The goal of the project was to authenticate a person’s identity by comparing the real-time facial image with the photo and TCKN (Turkish Citizenship Number) data stored in the contactless chip of the Turkish Republic Identity Card (TCKK). Accessing the Identity Chip via BAC Protocol An interface was developed to read the document number, date of birth, and document expiry date from the identity card using Tesseract OCR through a computer camera. Data Access via Java Spring API Using the extracted data, the BAC access key was computed, allowing access to the photo and TCKN information on the TCKK chip. Successful communication with the contactless card reader was achieved using the SmartCard – SCUBA library. Data Storage and Security The obtained data was stored on the MongoDB platform. The photo data was saved as a 128-dimensional NumPy array to prevent reverse engineering. Identity Authentication The data retrieved via OCR was used to access the identity chip, and the photo and TCKN data were sent to a Python Flask-based face recognition engine for authentication. Biometric LOGIN Process A biometric login process was created using 1-to-1 authentication logic. Additionally, the system was integrated with a Python Flask API capable of 1-to-N comparison, enabling identity verification without using any personally identifiable information. This project provided me with significant experience in the field of biometric authentication and secure identification.
Bus Occupancy Monitoring System Project Developed a real-time Bus Occupancy Tracking System utilizing various modern technologies: • Implemented back-end services using Python and the FastAPI framework for high-performance RESTful APIs. • Utilized PostgreSQL for structured data storage and efficient query management. • Designed and developed a user-friendly mobile interface using Flutter, enabling users to view bus locations, arrival times, and current occupancy levels. • Developed API endpoints to receive data from passenger card scans and dynamically calculate bus occupancy rates. • Integrated a GPS-based tracking system to monitor and display live bus positions on the mobile interface. This project enhanced my skills in full-stack development, real-time data processing, and cross-platform mobile application design.