Authors :
Vedant Mankar; Athrav Jadhav; Gayatri Golhar; Prajakta Sambhe; Sidhant Nitale; Bhavana Kharode; Gaurav Thakare; M. K. Shriwas
Volume/Issue :
Volume 9 - 2024, Issue 3 - March
Google Scholar :
https://tinyurl.com/4ev6z88r
Scribd :
https://tinyurl.com/2w5cbar6
DOI :
https://doi.org/10.38124/ijisrt/IJISRT24MAR2165
Abstract :
This research paper aims to contribute to the
field of biometric attendance systems by conducting a
comprehensive analysis of fingerprint-based attendance
systems described in the provided abstracts. The focus will
be on systems designed for educational institutions with an
emphasis on time efficiency, user satisfaction, and accuracy
in attendance tracking. The study will compare and
contrast the methodologies, technologies, and
implementation details presented in the abstracts,
identifying strengths and weaknesses of each system.
Special attention will be given to the use of Internet of
Things (IoT) technology, biometric design processes, and
the integration of fingerprint sensors with microcontrollers
like ESP32.Furthermore, the research will explore
optimization strategies to enhance the overall performance
of these systems. This includes investigating the feasibility
of incorporating advanced fingerprint identification
algorithms, improving user interface design, and
streamlining the data collection and storage processes. The
experimental aspect of the research will involve
implementing the proposed optimization strategies on a
prototype system and evaluating its performance against
the existing systems. Metrics such as fingerprint
identification accuracy, average matching time, and system
efficiency will be measured and compared to demonstrate
the effectiveness of the proposed enhancements.
Keywords :
ESP32, Fingerprint, Biometric, Attendance, Internet of things, Performance Metrics, Security Measures , Segmentation, and System Robustness.
This research paper aims to contribute to the
field of biometric attendance systems by conducting a
comprehensive analysis of fingerprint-based attendance
systems described in the provided abstracts. The focus will
be on systems designed for educational institutions with an
emphasis on time efficiency, user satisfaction, and accuracy
in attendance tracking. The study will compare and
contrast the methodologies, technologies, and
implementation details presented in the abstracts,
identifying strengths and weaknesses of each system.
Special attention will be given to the use of Internet of
Things (IoT) technology, biometric design processes, and
the integration of fingerprint sensors with microcontrollers
like ESP32.Furthermore, the research will explore
optimization strategies to enhance the overall performance
of these systems. This includes investigating the feasibility
of incorporating advanced fingerprint identification
algorithms, improving user interface design, and
streamlining the data collection and storage processes. The
experimental aspect of the research will involve
implementing the proposed optimization strategies on a
prototype system and evaluating its performance against
the existing systems. Metrics such as fingerprint
identification accuracy, average matching time, and system
efficiency will be measured and compared to demonstrate
the effectiveness of the proposed enhancements.
Keywords :
ESP32, Fingerprint, Biometric, Attendance, Internet of things, Performance Metrics, Security Measures , Segmentation, and System Robustness.
