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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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Bibliographic Details
Main Author: Abdul Razak, Nor Faezah
Format: Thesis
Language:English
Published: 2020
Subjects:
Electronic Computers. Computer Science
Application software
System design
Detectors. Sensors. Sensor networks
Pattern recognition systems
Online Access:http://ir.uitm.edu.my/id/eprint/31564/1/TD_NOR%20FAEZAH%20ABDUL%20RAZAK%20CS%20R%2020_5.pdf
http://ir.uitm.edu.my/id/eprint/31564/
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spelling my.uitm.ir.315642020-06-24T08:22:10Z http://ir.uitm.edu.my/id/eprint/31564/ Automated access of laboratory system using IOT-based face recognition / Nor Faezah Abdul Razak 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. 2020-06-24 Thesis NonPeerReviewed text en http://ir.uitm.edu.my/id/eprint/31564/1/TD_NOR%20FAEZAH%20ABDUL%20RAZAK%20CS%20R%2020_5.pdf Abdul Razak, Nor Faezah (2020) Automated access of laboratory system using IOT-based face recognition / Nor Faezah Abdul Razak. Degree thesis, Universiti Teknologi Mara Perlis.
institution Universiti Teknologi Mara
building Tun Abdul Razak Library
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Teknologi Mara
content_source UiTM Institutional Repository
url_provider http://ir.uitm.edu.my/
language English
topic Electronic Computers. Computer Science
Application software
System design
Detectors. Sensors. Sensor networks
Pattern recognition systems
spellingShingle Electronic Computers. Computer Science
Application software
System design
Detectors. Sensors. Sensor networks
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
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
publishDate 2020
url http://ir.uitm.edu.my/id/eprint/31564/1/TD_NOR%20FAEZAH%20ABDUL%20RAZAK%20CS%20R%2020_5.pdf
http://ir.uitm.edu.my/id/eprint/31564/
_version_ 1685650805235908608
score 13.211869

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