Blockchain Based Intelligent Tracking & Authentication of FYPs

Sai, Zhi Hong (2019) Blockchain Based Intelligent Tracking & Authentication of FYPs. [Final Year Project] (Submitted)

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Abstract

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
Subjects: Q Science > Q Science (General)
Departments / MOR / COE: Sciences and Information Technology > Computer and Information Sciences
Depositing User: Mr 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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