IoT-Based Biometric Recognition Systems in Education for Identity Verification Services: Quality Assessment Approach
Traditional identity verification of students based on the human proctoring approach can cause a scam identity verification and ineffective processing time, particularly among vast groups of students. Most student identification cards outdated personal information. Several biometric recognition appr...
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| Format: | Article |
| Language: | English |
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IEEE
2023-01-01
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| Series: | IEEE Access |
| Subjects: | |
| Online Access: | https://ieeexplore.ieee.org/document/10058940/ |
| _version_ | 1827994173409591296 |
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| author | Meennapa Rukhiran Sethapong Wong-In Paniti Netinant |
| author_facet | Meennapa Rukhiran Sethapong Wong-In Paniti Netinant |
| author_sort | Meennapa Rukhiran |
| collection | DOAJ |
| description | Traditional identity verification of students based on the human proctoring approach can cause a scam identity verification and ineffective processing time, particularly among vast groups of students. Most student identification cards outdated personal information. Several biometric recognition approaches have been proposed to strengthen students’ identity verification. Most educational adoption technologies struggle with evaluation and validation techniques to ensure that biometric recognition systems are unsuitable for utilization and implementation for student identity verification. This study presents the internet of things to develop flexible biometric recognition systems and an approach to assess the quality of biometric systems for educational use by investigating the effectiveness of identity verification of various biometric recognition technologies compared to the traditional verification method. The unimodal, multimodal, and semi-multimodal biometric technologies were tested using the developed internet of things-base biometric recognition systems examined by applying the proposed quality metrics of scoring factors based on accuracy, error rate, processing time, and cost. Hundreds of undergraduate exam takers were a sample group. Key findings indicate that the designed and presented systems suitably attain identity verification of exam students using a unimodal biometric. The unimodal facial biometric system promises excellent support. A unimodal fingerprint biometric system ensures second excellent aid for student identity verification. However, multimodal and semi-multimodal biometric systems provide better accuracy with fewer handling times and higher costs. This study contributes significantly to the knowledge of utilizing biometric recognition for identity verification in smart educational applications. |
| first_indexed | 2024-04-10T04:35:52Z |
| format | Article |
| id | doaj.art-0b7540bdf91f4278aa248f31e3a59f1a |
| institution | Directory Open Access Journal |
| issn | 2169-3536 |
| language | English |
| last_indexed | 2024-04-10T04:35:52Z |
| publishDate | 2023-01-01 |
| publisher | IEEE |
| record_format | Article |
| series | IEEE Access |
| spelling | doaj.art-0b7540bdf91f4278aa248f31e3a59f1a2023-03-10T00:00:45ZengIEEEIEEE Access2169-35362023-01-0111227672278710.1109/ACCESS.2023.325302410058940IoT-Based Biometric Recognition Systems in Education for Identity Verification Services: Quality Assessment ApproachMeennapa Rukhiran0Sethapong Wong-In1Paniti Netinant2https://orcid.org/0000-0001-8376-0440Faculty of Social Technology, Rajamangala University of Technology Tawan-ok, Chanthaburi, ThailandCollege of Digital Information Technology, Rangsit University, Lak Hok, Pathum Thani, ThailandCollege of Digital Information Technology, Rangsit University, Lak Hok, Pathum Thani, ThailandTraditional identity verification of students based on the human proctoring approach can cause a scam identity verification and ineffective processing time, particularly among vast groups of students. Most student identification cards outdated personal information. Several biometric recognition approaches have been proposed to strengthen students’ identity verification. Most educational adoption technologies struggle with evaluation and validation techniques to ensure that biometric recognition systems are unsuitable for utilization and implementation for student identity verification. This study presents the internet of things to develop flexible biometric recognition systems and an approach to assess the quality of biometric systems for educational use by investigating the effectiveness of identity verification of various biometric recognition technologies compared to the traditional verification method. The unimodal, multimodal, and semi-multimodal biometric technologies were tested using the developed internet of things-base biometric recognition systems examined by applying the proposed quality metrics of scoring factors based on accuracy, error rate, processing time, and cost. Hundreds of undergraduate exam takers were a sample group. Key findings indicate that the designed and presented systems suitably attain identity verification of exam students using a unimodal biometric. The unimodal facial biometric system promises excellent support. A unimodal fingerprint biometric system ensures second excellent aid for student identity verification. However, multimodal and semi-multimodal biometric systems provide better accuracy with fewer handling times and higher costs. This study contributes significantly to the knowledge of utilizing biometric recognition for identity verification in smart educational applications.https://ieeexplore.ieee.org/document/10058940/BiometricsrecognitionidentityverificationInternet of Thingsquality assessment |
| spellingShingle | Meennapa Rukhiran Sethapong Wong-In Paniti Netinant IoT-Based Biometric Recognition Systems in Education for Identity Verification Services: Quality Assessment Approach IEEE Access Biometrics recognition identity verification Internet of Things quality assessment |
| title | IoT-Based Biometric Recognition Systems in Education for Identity Verification Services: Quality Assessment Approach |
| title_full | IoT-Based Biometric Recognition Systems in Education for Identity Verification Services: Quality Assessment Approach |
| title_fullStr | IoT-Based Biometric Recognition Systems in Education for Identity Verification Services: Quality Assessment Approach |
| title_full_unstemmed | IoT-Based Biometric Recognition Systems in Education for Identity Verification Services: Quality Assessment Approach |
| title_short | IoT-Based Biometric Recognition Systems in Education for Identity Verification Services: Quality Assessment Approach |
| title_sort | iot based biometric recognition systems in education for identity verification services quality assessment approach |
| topic | Biometrics recognition identity verification Internet of Things quality assessment |
| url | https://ieeexplore.ieee.org/document/10058940/ |
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