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Blockchain Based Intelligent Tracking & Authentication of FYPs

Sai, Zhi Hong (2019) Blockchain Based Intelligent Tracking & Authentication of FYPs. IRC, Universiti Teknologi PETRONAS. (Submitted)

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Final Year Project (FYP) is a compulsory subject that must be taken by final year students at Department of Computer and Information Sciences (CISD) in Universiti Teknologi Petronas (UTP). Currently, CISD is using the conventional way to manage the FYP process. This existing approach of FYP Management has led to some serious problems. The first problem is the difficulty for supervisors to get all the details required during the FYP process such as the limit for student allocation, the deadline for student reports submission and the details of student assigned under them. Another problem of conventional FYP Management is to keep track of the student’s report submission in a timeline sequence. This type of tracking process is important to verify the submission details and to prevent any changes on the submission once the data is recorded. The last problem during FYP management is the manual evaluation of the FYPs title proposed by the final year students which is prone to human error. As a result, Blockchain Based Intelligent Tracking & Authentication of FYPs system was proposed to solve those problems. Blockchain technology is used to store all the student’s report submission details in a timeline sequence which ease the process of submission tracking. In addition, blockchain structure can prevent any alteration on the recorded data that is important for the FYP management process. Machine learning is also required in the system to evaluate the proposed FYPs title from students. Semantic Similarity using Universal Sentence Encoder is implemented to check the meaning of the title rather than just compare the similarity of words inside the title. After implementation, the expected result of the project will be a web-based application for the user to perform the required functionality. All the process performed will be recorded in the blockchain architecture based on the timeline sequence. Machine learning technology implemented inside the system will automatically evaluate the proposed FYPs title and the accuracy of the evaluation is higher than manual evaluation by FYP committee.

Item Type: Final Year Project
Academic Subject : Academic Department - Information Communication Technology
Subject: Q Science > Q Science (General)
Divisions: Sciences and Information Technology > Computer and Information Sciences
Depositing User: Ahmad Suhairi Mohamed Lazim
Date Deposited: 10 Sep 2021 08:57
Last Modified: 10 Sep 2021 08:57
URI: http://utpedia.utp.edu.my/id/eprint/20955

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