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Journal of Computer Science & Systems Biology

ISSN: 0974-7230

Open Access

Biometric Monitoring Using Facial Recognition, Data Collection, and Storage: Safety and Privacy Perceptions of High School Students

Abstract

Ebsary NJ*

With the advent of school shootings across the United States including the murders of seventeen Marjory Stoneman Douglas High school students and teachers; school administrators, faculty, parents, and students have extensive security and safety concerns about individuals entering and exiting school grounds. A biometric technology widely used to authenticate individuals as part of campus security and safety is facial recognition.

Facial recognition overcomes one of the significant drawbacks with biometric systems since it does not require direct contact or proximity to sensors to identify personnel on the school campus. How effective facial recognition systems are in monitoring individuals’ existence on campus in large part depends on student’s cooperation and attitudes supporting this biometric technology. This paper explores the perceptions of high school students towards biometric monitoring using facial recognition with their concerns over privacy and safety.

This study utilizes quantitative methods to investigate how students’ opinions formed in High school about facial recognition based on beliefs about informational privacy and their appraisal of school safety conditions on campus. This study provides guidance into student views and opinions on biometric monitoring that could be present throughout their high school facilities.

The results indicated that aspects of facial recognition provide concern about students’ informational privacythat includes the operations, administration, and management of a biometric monitoring system by the school’s faculty and staff. The implications on school systems as the result of this study suggests that school policymakers and state representatives need to carefully consider and be aware of students’ perceptions on safety and privacy in consideration of school security using facial recognition.

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Citations: 2279

Journal of Computer Science & Systems Biology received 2279 citations as per Google Scholar report

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