Identity Trace: E-Government Application System

Abdoulmalik, Walidi; Mukaddas, Ahmad Muhammad; Bodjam, Malamine

dc.contributor.author	Abdoulmalik, Walidi
dc.contributor.author	Mukaddas, Ahmad Muhammad
dc.contributor.author	Bodjam, Malamine
dc.date.accessioned	2025-03-10T06:03:33Z
dc.date.available	2025-03-10T06:03:33Z
dc.date.issued	2024-06-26
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dc.identifier.uri	http://hdl.handle.net/123456789/2370
dc.description	Supervised by Dr. Md, Moniruzzaman, Assistant Professor, Department of Computer Science and Engineering (CSE) Islamic University of Technology (IUT) Board Bazar, Gazipur, Bangladesh This thesis is submitted in partial fulfillment of the requirement for the degree of Bachelor of Science in Computer Science and Engineering, 2024	en_US
dc.description.abstract	Identity Trace, part of the E-Government project, aims to transform the way we access public services using face recognition in visa applications. This thesis presents the creation of a web system that is highly secure and efficient by employing a robust face recognition method for accuracy in the process of document verification. Citizens can sign up, upload required documents, and track the status of their application, and the administrators can verify the documents uploaded and search for clients based on facial images. The project is aimed at overcoming core issues in public service de livery like inefficiency, security and strong identification requirements by using the Face recognition method using Support Vector Machines (SVM). Furthermore, this research studies the possibility to benefit from the face recognition technology in E Government systems in terms of efficiency and user experience. Identity Trace pro poses utilizing SVMs to accurately identify the user and integrating the process with low level face recognition searches in a native method called the Identity Trace sys tem in place of conventional name-based methods. It covers discussion on the chal lenges the model overcame, including data privacy, dataset bias, and computational efficiency with the system’s evaluation of 80% accuracy on user identification. This system dramatically increases the processing efficiency and provides a smoother ex perience for users than conventional name-search methods. Future directions will be the study of recent algorithms, improved buffering mechanisms, and security im provements as well as its generalization to other E-Government services	en_US
dc.language.iso	en	en_US
dc.publisher	Department of Computer Science and Engineering(CSE), Islamic University of Technology(IUT), Board Bazar, Gazipur-1704, Bangladesh	en_US
dc.subject	CNN Convolutional Neural Network SVM Support Vector Machine UI User Interface NID National Identity AI Artificial Intelligence	en_US
dc.title	Identity Trace: E-Government Application System	en_US
dc.type	Thesis	en_US