Automated access of laboratory system using IOT-based face recognition / Nor Faezah Abdul Razak

Currently, laboratory door are unlocked by using the manual ways such as using the keys, security cards or passwords. Unfortunately, this system is not fully secured as the technologies nowadays have been upgraded and become more sophisticated. Old system tend to have some insufficiencies that are l...

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Main Author:	Abdul Razak, Nor Faezah
Format:	Thesis
Language:	English
Published:	2020
Subjects:	Electronic Computers Computer Science Application software System design Pattern recognition systems
Online Access:	https://ir.uitm.edu.my/id/eprint/31564/1/TD_NOR%20FAEZAH%20ABDUL%20RAZAK%20CS%20R%2020_5.pdf
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id	my-uitm-ir.31564
record_format	uketd_dc
spelling	my-uitm-ir.315642020-06-24T08:22:10Z Automated access of laboratory system using IOT-based face recognition / Nor Faezah Abdul Razak 2020-06-24 Abdul Razak, Nor Faezah Electronic Computers. Computer Science Application software System design Detectors. Sensors. Sensor networks Pattern recognition systems Currently, laboratory door are unlocked by using the manual ways such as using the keys, security cards or passwords. Unfortunately, this system is not fully secured as the technologies nowadays have been upgraded and become more sophisticated. Old system tend to have some insufficiencies that are likely to be stolen by unauthorized parties or forgotten by the owners. The main objective of this research is to heighten the safety of the door of sensitive places through face detection. Face is known as a multidimensional form and it needs accurate computing techniques for detection and recognition. Face detection is known as a way of detection, the vicinity of face in an image. Face detection is commonly detected through the use of the face popularity where it is achieved together with the help of the usage of the Principle Component Analysis (PCA). Face recognition is primarily based on PCA which normally uses Eigen faces. In addition, together with a purpose to accomplish a better accuracy and effectiveness at ease, this research proposes Open CV libraries and Python computer language for face recognition. Training and identity can be done and accomplished in an embedded tool called Raspberry Pi. This is a prototype that can identify the persons. The methodology of the study involved three phases which include system design, functionality test, and usability test. The first phase was system design which involved system visualization and design of prototype using a schematic diagram. Then, the functionality of the prototype was tested using a Test Case method. Another evaluation consists of gaining a response from 2 expert panels from UiTM staff about the system understanding, usefulness and effectiveness via a usability test. The usability study requires the response to watching the demonstration of the prototype, using the prototype and answer the questionnaires. The result from the study suggests that the prototype is suitable to be used. 2020-06 Thesis https://ir.uitm.edu.my/id/eprint/31564/ https://ir.uitm.edu.my/id/eprint/31564/1/TD_NOR%20FAEZAH%20ABDUL%20RAZAK%20CS%20R%2020_5.pdf text en public degree Universiti Teknologi Mara Perlis Faculty of Computer and Mathematical Sciences
institution	Universiti Teknologi MARA
collection	UiTM Institutional Repository
language	English
topic	Electronic Computers Computer Science Application software System design Electronic Computers Computer Science Pattern recognition systems
spellingShingle	Electronic Computers Computer Science Application software System design Electronic Computers Computer Science Pattern recognition systems Abdul Razak, Nor Faezah Automated access of laboratory system using IOT-based face recognition / Nor Faezah Abdul Razak
description	Currently, laboratory door are unlocked by using the manual ways such as using the keys, security cards or passwords. Unfortunately, this system is not fully secured as the technologies nowadays have been upgraded and become more sophisticated. Old system tend to have some insufficiencies that are likely to be stolen by unauthorized parties or forgotten by the owners. The main objective of this research is to heighten the safety of the door of sensitive places through face detection. Face is known as a multidimensional form and it needs accurate computing techniques for detection and recognition. Face detection is known as a way of detection, the vicinity of face in an image. Face detection is commonly detected through the use of the face popularity where it is achieved together with the help of the usage of the Principle Component Analysis (PCA). Face recognition is primarily based on PCA which normally uses Eigen faces. In addition, together with a purpose to accomplish a better accuracy and effectiveness at ease, this research proposes Open CV libraries and Python computer language for face recognition. Training and identity can be done and accomplished in an embedded tool called Raspberry Pi. This is a prototype that can identify the persons. The methodology of the study involved three phases which include system design, functionality test, and usability test. The first phase was system design which involved system visualization and design of prototype using a schematic diagram. Then, the functionality of the prototype was tested using a Test Case method. Another evaluation consists of gaining a response from 2 expert panels from UiTM staff about the system understanding, usefulness and effectiveness via a usability test. The usability study requires the response to watching the demonstration of the prototype, using the prototype and answer the questionnaires. The result from the study suggests that the prototype is suitable to be used.
format	Thesis
qualification_level	Bachelor degree
author	Abdul Razak, Nor Faezah
author_facet	Abdul Razak, Nor Faezah
author_sort	Abdul Razak, Nor Faezah
title	Automated access of laboratory system using IOT-based face recognition / Nor Faezah Abdul Razak
title_short	Automated access of laboratory system using IOT-based face recognition / Nor Faezah Abdul Razak
title_full	Automated access of laboratory system using IOT-based face recognition / Nor Faezah Abdul Razak
title_fullStr	Automated access of laboratory system using IOT-based face recognition / Nor Faezah Abdul Razak
title_full_unstemmed	Automated access of laboratory system using IOT-based face recognition / Nor Faezah Abdul Razak
title_sort	automated access of laboratory system using iot-based face recognition / nor faezah abdul razak
granting_institution	Universiti Teknologi Mara Perlis
granting_department	Faculty of Computer and Mathematical Sciences
publishDate	2020
url	https://ir.uitm.edu.my/id/eprint/31564/1/TD_NOR%20FAEZAH%20ABDUL%20RAZAK%20CS%20R%2020_5.pdf
_version_	1783734129602330624

Automated access of laboratory system using IOT-based face recognition / Nor Faezah Abdul Razak

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