In-building facial recognition check-in system
In recent years, facial recognition technology has gained significant attention due to its potential applications in various domains, such as security, access control, and attendance tracking. This project focuses on the development and implementation of an In-Building Facial Recognition Check-in Sy...
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| Format: | Final Year Project / Dissertation / Thesis |
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2023
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| Online Access: | http://eprints.utar.edu.my/5892/ http://eprints.utar.edu.my/5892/1/SE_1902914_FYP_report_%2D_YongLiJonn_%2D_LI_JONN_YONG.pdf |
| _version_ | 1848886530806906880 |
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| author | Yong, Li Jonn |
| author_facet | Yong, Li Jonn |
| author_sort | Yong, Li Jonn |
| building | UTAR Institutional Repository |
| collection | Online Access |
| description | In recent years, facial recognition technology has gained significant attention due to its potential applications in various domains, such as security, access control, and attendance tracking. This project focuses on the development and implementation of an In-Building Facial Recognition Check-in System for the Universiti Tunku Abdul Rahman (UTAR) to enhance the check-in process for students. The system integrates a pre-trained machine learning model for facial recognition, an Android mobile application, and a Firebase back-end database to create a seamless check-in experience. The primary objectives of the project were to develop a functional facial recognition system, create an Android mobile application, and ensure satisfactory performance through user acceptance testing. The system was successfully developed within the set deadline of April 2023 and met the necessary performance and usability requirements. The application allows users to create accounts using their UTAR email addresses, enroll their faces for identity verification, check-in to designated buildings, view their check-in records, and manage their personal information. Despite its achievements, the system has some limitations, including the lack of liveness detection, location detection, and cross-platform compatibility. To address these limitations, future developments are proposed, such as implementing liveness and location detection, integrating the system with other UTAR systems, and expanding platform compatibility. Regular updates to the machine learning model and continuous system improvement will also ensure that the facial recognition system remains accurate and effective. In conclusion, the In-Building Facial Recognition Check-in System has successfully achieved its project objectives, providing UTAR students with a convenient and efficient check-in process. By implementing the recommended improvements and maintaining a focus on continuous development, the system has the potential to significantly enhance the check-in experience at UTAR and serve as a valuable asset to the university and its community. |
| first_indexed | 2025-11-15T19:39:58Z |
| format | Final Year Project / Dissertation / Thesis |
| id | utar-5892 |
| institution | Universiti Tunku Abdul Rahman |
| institution_category | Local University |
| last_indexed | 2025-11-15T19:39:58Z |
| publishDate | 2023 |
| recordtype | eprints |
| repository_type | Digital Repository |
| spelling | utar-58922023-10-05T11:53:35Z In-building facial recognition check-in system Yong, Li Jonn QA76 Computer software In recent years, facial recognition technology has gained significant attention due to its potential applications in various domains, such as security, access control, and attendance tracking. This project focuses on the development and implementation of an In-Building Facial Recognition Check-in System for the Universiti Tunku Abdul Rahman (UTAR) to enhance the check-in process for students. The system integrates a pre-trained machine learning model for facial recognition, an Android mobile application, and a Firebase back-end database to create a seamless check-in experience. The primary objectives of the project were to develop a functional facial recognition system, create an Android mobile application, and ensure satisfactory performance through user acceptance testing. The system was successfully developed within the set deadline of April 2023 and met the necessary performance and usability requirements. The application allows users to create accounts using their UTAR email addresses, enroll their faces for identity verification, check-in to designated buildings, view their check-in records, and manage their personal information. Despite its achievements, the system has some limitations, including the lack of liveness detection, location detection, and cross-platform compatibility. To address these limitations, future developments are proposed, such as implementing liveness and location detection, integrating the system with other UTAR systems, and expanding platform compatibility. Regular updates to the machine learning model and continuous system improvement will also ensure that the facial recognition system remains accurate and effective. In conclusion, the In-Building Facial Recognition Check-in System has successfully achieved its project objectives, providing UTAR students with a convenient and efficient check-in process. By implementing the recommended improvements and maintaining a focus on continuous development, the system has the potential to significantly enhance the check-in experience at UTAR and serve as a valuable asset to the university and its community. 2023 Final Year Project / Dissertation / Thesis NonPeerReviewed application/pdf http://eprints.utar.edu.my/5892/1/SE_1902914_FYP_report_%2D_YongLiJonn_%2D_LI_JONN_YONG.pdf Yong, Li Jonn (2023) In-building facial recognition check-in system. Final Year Project, UTAR. http://eprints.utar.edu.my/5892/ |
| spellingShingle | QA76 Computer software Yong, Li Jonn In-building facial recognition check-in system |
| title | In-building facial recognition check-in system |
| title_full | In-building facial recognition check-in system |
| title_fullStr | In-building facial recognition check-in system |
| title_full_unstemmed | In-building facial recognition check-in system |
| title_short | In-building facial recognition check-in system |
| title_sort | in-building facial recognition check-in system |
| topic | QA76 Computer software |
| url | http://eprints.utar.edu.my/5892/ http://eprints.utar.edu.my/5892/1/SE_1902914_FYP_report_%2D_YongLiJonn_%2D_LI_JONN_YONG.pdf |