Biometrics as a method of employee control

Żywiołek, Justyna; Sarkar, Achyuth; Sial, Muhammad Safdar

doi:10.1109/imcom53663.2022.9721809

Cited by 2 publications

(2 citation statements)

References 27 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…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

View full text Add to dashboard Cite

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 Most student identification cards are outdated personal information.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.

show abstract

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

View full text Add to dashboard Cite

show abstract

“…The essence of Industry 5.0 lies in leveraging the unique strengths of both humans and machines, aiming for a production environment where creativity, flexibility, and complex problem-solving are enhanced by AI's analytical prowess and operational efficiency [12]. Our comparative analysis delves into the evolution of AI from Industry 4.0 to Industry 5.0, highlighting the transition from automation and efficiency to collaboration and innovation [13]. Through a blend of qualitative and quantitative methodologies, drawing from academic literature, industry insights, and empirical data, this study aims to dissect the nuances of these industrial revolutions.…”

Section: Introductionmentioning

confidence: 99%

Building Trust in AI-Human Partnerships: Exploring Preferences and Influences in the Manufacturing Industry

Żywiołek

2024

Management Systems in Production Engineering

View full text Add to dashboard Cite

The incorporation of artificial intelligence (AI) into industrial processes has seen substantial development, characterized by the shift from Industry 4.0 to the future concept of Industry 5.0. The article identifies a significant gap in knowledge regarding how openness in AI engagement influences consumer trust and confidence in news media. This gap highlights the need for further exploration into the relationship between transparency in AI processes and consumer perceptions. The research utilises a combination of qualitative and quantitative approaches, gathering insights from academic literature, industry viewpoints, and actual data. We conduct an extensive analysis of existing literature to investigate the process of incorporating artificial intelligence into news creation and its influence on the level of confidence consumers have in the news. We have identified a significant lack of knowledge about the impact of openness in AI engagement on consumer views and trust in news media. Expanding on this discrepancy, we suggest a systematic methodology that incorporates controlled experiments and surveys to evaluate the influence of different degrees of openness on consumer trust and involvement with AI-generated news content. In addition, the paper examines the difficulties in establishing confidence in artificial intelligence (AI) inside the European Union, including several aspects such as technological, ethical, social, and legal considerations. The document presents a thorough plan to guarantee the secure development and execution of AI, with a focus on the significance of transparency, ethics, and teamwork. The study’s results provide vital insights for politicians, news organisations, and industrial businesses as they navigate the intricate process of integrating AI. Comprehensive Plan for Secure AI Development, to address the challenges outlined, the article presents a thorough plan for ensuring the secure development and execution of AI within the European Union. This plan emphasizes the significance of transparency, ethics, and collaboration in building trust and confidence in AI technologies.

show abstract

Biometrics as a method of employee control

Cited by 2 publications

References 27 publications

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

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

Building Trust in AI-Human Partnerships: Exploring Preferences and Influences in the Manufacturing Industry

Contact Info

Product

Resources

About