Empirical Assessment of End-to-End Iris Recognition System Capacity

Das, Priyanka; Plesh, Richard; Talreja, Veeru; Schmid, Natalia A.; Valenti, Matthew C.; Skufca, Joseph D.; Schuckers, Stephanie

doi:10.1109/tbiom.2023.3256894

Cited by 4 publications

(1 citation statement)

References 21 publications

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“…The wireless E-voting process offers many essential advantages, including reducing the hardware connections implemented by wires, which are sometimes difficult to install due to the long distance or the structure of the buildings [6]. Different techniques can be accomplished to identify people using biometrics or security keys, such as fingerprint [7], face recognition [8,9], iris recognition [10], and Radio Frequency Identification (RFID) [11,12].…”

Section: Introductionmentioning

confidence: 99%

A Wireless Voting System Using Wi-Fi-Based Microcontrollers and Face Verification

Farhan

2024

IJEETC

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Voting systems nowadays are highly interesting due to their importance in expressing opinions. The proposed work aims to design a cost-effective and reliable Electronic Voting System (EVS) that can tackle the issues faced by manual election. The system uses small and lowcost microcontrollers with Wi-Fi network connectivity to avoid the issues of installing wire connections. Eligible voters are authenticated by recognizing their faces using deep neural networks (VGG-16 model). The Wi-Fi connections between the server and the clients are carried out through the Internet Protocol suite (TCP/IP) transmission method to ensure data arrival without loss. The client’s side comprises four small and cheap microcontrollers known as ESP8266-01, whereas the server side contains one NodeMCU ESP8266-12E microcontroller connected to a program computer. The voting results are displayed using the Visual Basic programming language. The system is specifically designed to facilitate voting on a particular opinion by providing two options: (Yes) and (No). Besides, it can be utilized for electing a committee manager or group leader and can be expanded to accommodate more options. The VGG model’s robustness is demonstrated through experiments, achieving 99.12% accuracy on Faces96 images and 98.61% on our database. Moreover, the practical implementation of the election process demonstrates that the system is highly reliable, secure and cost-effective.

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