IoT Project: Smart Parking

Shlyakhetko, Olena; Braibant, Alexis; Czechowska, Ewa; Fryczka, Magdalena; Hadrich, Ramzi

doi:10.1007/978-3-030-95813-8_2

Cited by 1 publication

(1 citation statement)

References 22 publications

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“…Using biometric technology in identity verification systems has several advantages over traditional identity verification. Access control using fingerprint recognition to check out [13] and face recognition to grant access [14], healthcare [15], citizen identification [16], [17], security systems [18], finance [19], airport [20], canteen management system [21], visitor management systems [22] and parking management systems [23][24][25] have addressed the advantages of implementing biometric technology. Biometric technology is one of the practical and useful alternatives for verifying exam takers.…”

Section: Figure 1 Traditional Approach Of Examination Takers' Identif...mentioning

confidence: 99%

IoT-Based Biometric Recognition Systems in Education for Identity Verification Services: Quality Assessment Approach

2023

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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 Most student identification cards are outdated personal information. Several biometric recognition approaches have been proposed and can be adopted to strengthen students' identity verification. Most educational adoption technology struggles with evaluation and validation techniques to ensure that biometric recognition systems are unquestionably suitable for utilization and implementation to fulfill 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. A unimodal face biometric system promises excellent support. A unimodal fingerprint biometric system assures the second excellent aid for student identity verification. However, multimodal and semi-multimodal biometric systems provide better accuracy with few handling times and higher costs. This study contributes significantly to the knowledge of utilizing biometric recognition for identity verification in smart educational use.

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