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Journal of Image Processing and Intelligent Remote Sensing
ISSN 2815-0953
Vol: 04, No.03, April-May 2024
http://journal.hmjournals.com/index.php/JIPIRS
DOI: https://doi.org/10.55529/jipirs.43.1.13
Copyright The Author(s) 2024.This is an Open Access Article distributed under the CC BY
license. (http://creativecommons.org/licenses/by/4.0/) 1
Wired Fingerprint-Based Classroom Attendance System
for Secured Student Attendance Archiving
Using Arduino UNO Microcontroller
Jose III C. Celerez1*, Wendy E. Antipuesto2, Daniel Reyn A. Aratea3,
Ivan Clint L. Salvador4, Jermaine Nichole B. Rosello5
1*,2,3,4,5Association of Science and Mathematics Coaches of the Philippines, Philippine
Association of Teachers and Educational Leaders, Philippine Institute of 21st Century
Educators Inc., Philippines.
Email: 2antipuestowendye@gmail.com, 3arateadanielreyn@gmail.com,
4salvadorivan.gc@gmail.com,5nicholejerm@gmail.com
Corresponding Email: 1*jcelereziii@gmail.com
Received: 28 November 2023 Accepted: 14 February 2024 Published: 01 April 2024
Abstract: This study, which successfully addresses the shortcomings of traditional
attendance-checking methods, such as human error, that are inevitable in manual
attendance systems given the fact that it is time-consuming. Paper-based systems can be
susceptible to forgery, as students may attempt to sign in on behalf of absent classmates. This
undermines the integrity of attendance records. Introduces a fingerprint-based classroom
attendance system designed using the Arduino Uno microcontroller. The research explores
the feasibility of fingerprint biometrics for identity verification in educational settings.
Using Arduino Uno, Fingerprint Sensor, RTC Module, and the LCD Monitor the
researchers successfully developed a working prototype for the Wired Fingerprint-Based
Classroom Attendance. 600 tests were applied to collect the (1.0) lowest and (2.0) highest
time of the fingerprint sensor and calculate its average (1.7). The developed system operates
offline, storing data securely on an SD card, making it particularly suitable for institutions
in areas with restricted internet access. Comparative performance evaluations against
conventional pen-and-paper methods highlight the fingerprint-based system's notable
capacity, accuracy, positioning it as a transformative tool to enhance attendance tracking
procedures and eliminates attendance-related issues to improve overall classroom
operations.
Keywords: Arduino Uno, Fingerprint, Attendance Checking, Attendance Archiving.
Journal of Image Processing and Intelligent Remote Sensing
ISSN 2815-0953
Vol: 04, No.03, April-May 2024
http://journal.hmjournals.com/index.php/JIPIRS
DOI: https://doi.org/10.55529/jipirs.43.1.13
Copyright The Author(s) 2024.This is an Open Access Article distributed under the CC BY
license. (http://creativecommons.org/licenses/by/4.0/) 2
1. INTRODUCTION
1.1 Background of the Study
Fingerprints are the fastest and secure method for biometric identification, unique to each
person and consistent throughout a lifetime. A fingerprint recognition system, utilizing an
Arduino UNO, automates classroom attendance, eliminating time-consuming manual methods.
Traditional attendance checking, particularly in large classes, is inefficient and prone to errors
(Rahman, 2018). The Arduino-based system ensures accurate records, detecting bogus
attendance and preventing cheating. Teachers, equipped with printed lists, often face
challenges managing attendance. Fingerprint-based attendance, using an Atmel AVR
ATMega328 microcontroller chip and a Micro SD Card for storage, offers a reliable solution.
The system captures fingerprint patterns, processes them into biometric templates, and records
attendance directly to the Micro SD Card (Vargas et al., 2019). The Arduino's benefits,
including ready-made modules and USB communication capabilities, make it a suitable
platform (Santoso and Sari, 2019). The proposed Fingerprint Classroom Attendance project
reduces teachers' and monitors' obligations, providing an exact time of student arrival and
minimizing the risk of manipulation. The system is designed for offline functionality, making
it applicable to schools in rural areas without internet connectivity.
1.2 Objectives of the Study
The researchers aim to assess the effectiveness and quality of Fingerprint Based Classroom
Attendance System Using Arduino UNO Microcontroller. Specifically, the study aims to:
1. Determine the materials needed to create a good quality of a working prototype;
2. Complete the codes for the automated fingerprint;
3. Assemble the components of Arduino UNO;
4. Design a schematic diagram of the prototype;
5. Create a working prototype of Fingerprint Classroom Attendance; and
6. Assess the effectiveness and quality of Arduino Uno in terms of Fingerprint sensor testing.
1.3 Significance of the Study
This study was conducted to create a Fingerprint Based Classroom Attendance System for
students. This study will give significant benefits to the following:
Teachers Assigned in Rural Districts
The study is significant and will benefit the teachers assigned in rural districts, as this will give
an easy and accessible way of checking attendance without a waste of time.
Future Researchers
The findings of this study can be used as a guide for future researchers studying programming
commands in the Arduino uno Software system. The study findings may also provide
preliminary data that the future researchers can use.
1.4 Scope and Limitation
The study limits its coverage inside the School Campus of Bayugan National Comprehensive
Journal of Image Processing and Intelligent Remote Sensing
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High School for testing the Fingerprint Based Classroom Attendance System. The study only
aims to test and investigate the capability of Arduino Uno to create a working Fingerprint based
system using its components and programmed commands. Thus, the researchers shall neglect
any other alternative methods on creating Fingerprint Based System with the use of
programming commands that are not available and applicable in the area. Specifically, the
study will only take place in the municipality of Bayugan City, Agusan del Sur where the
Bayugan National Comprehensive High School is located.
1.5 Conceptual Framework
Shows the output in conducting the programming of Arduino Uno and creating the working
prototype of Fingerprint Based Attendance.
Research Paradigm
2. RELATED WORKS
Development of Attendance Management System Using Biometrics
Keeping track of an institution's student attendance data is a tedious task. It consumes both time
and paper. The author designed an attendance board architecture that is already operational to
automate
and
digitize
all attendance-related tasks. It makes use of a special finger imprint
differentiating framework that was developed for this objective. This framework for unique
mark ID makes use of both new and current unique mark recognition and arrangement (Patra,
G. & Mohanty, M.N., 2020)
Attendance Fingerprint Identification System Using Arduino and Single Board
Computer
One of the most distinctive features of the human body that quickly and easily sets one
individual apart from another is the fingerprint. A technology known as fingerprint sensors,
which can automatically identify or recognize a person, supports this uniqueness.
However, the current fingerprint sensor is limited to identifying fingerprints on a single device.
Journal of Image Processing and Intelligent Remote Sensing
ISSN 2815-0953
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Copyright The Author(s) 2024.This is an Open Access Article distributed under the CC BY
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For the previously stated reason, we require a technique to identify every user in a unique
fingerprint sensor. The goal of this project is to develop a fingerprint sensor system that will
enable centralized fingerprint data administration and enable fingerprint recognition on each
fingerprint sensor. The study's findings demonstrate that data processing. may be consolidated
using Arduino and Raspberry Pi, enabling fingerprint identification in each fingerprint sensor
with a 98.5% success rate for centralized server recording (M A Muchtar, 2018).
Fingerprint Based Biometric Student Attendance System
Attendance is a notion that is used to identify a person's presence at the beginning and end of
the day in a variety of settings, including hospitals, institutions, and organizations. In the past
and in many locations even today, names are called out in attendance registers to manually
record attendance. Time and human labor are wasted because of this. Also, using a register
leads to a lot of bogus difficulties. For instance, in a classroom, the teacher calls out each
student's name sequentially and indicates their attendance after they respond.
An alternative method is for the instructor to circulate the attendance sheet throughout the
classroom with the students signing it next to their names. Nevertheless, a significant
disadvantage of these approaches is that students often respond or sign on behalf of their absent
friends. If the strength of the class is great, these fraudulent issues might occur more frequently.
Using an automated attendance recording system is one way to get around these issues. This
research provides a fingerprint-based biometric system that automatically logs attendance in
this direction.
A fingerprint sensor is part of this system, which is utilized to identify the user (Sogbodjor,
2021). The researchers used an embedded fingerprint-based management system utilizing the
microcontroller-based system (EMFIBAMS) design. The system includes a fingerprint sensor,
a GSM modem, an Arduino board, LCD, and other devices. During the comparison of this
system and the manual method, the result shows that the average time taken per student using
an embedded fingerprint-based attendance management system using microcontroller is much
shorter than that of manual checking (Ikuomola, 2019).
The system addressed the problems associated with traditional attendance systems because
provides faster and more accurate results the percentage of students who attend and the number
of lectures delivered by a single lecturer, an effective means of registering students and
managing their attendance that eliminates attendance-related issues like friend signing, loss of
attendance sheet, and it will be easier to manage the percentage of students and teachers who
skip lectures (Sambo et al., 2018).
The Use of Biometric Attendance Recording System (BARS) and it’s Impact on the Work
Performance of Cabanatuan City Government Employees
Biometric technology as a means of identifying and verifying an individual’s characteristic is
widely used in many aspects of peoples’ lives nowadays. In this regard, the Local Government
Unit (LGU) uses this technology to provide a more comprehensive system for monitoring
employee attendance and how it may affect their performance. The study assesses the impact
of the use of the Biometric Attendance Recording System (BARS) on the work performance of
Local Government Unit (LGU) employees based on their Individual Performance Commitment
Review (IPCR) rating and the respondents’ self-assessment and perception. Noticeably, most of the
Journal of Image Processing and Intelligent Remote Sensing
ISSN 2815-0953
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DOI: https://doi.org/10.55529/jipirs.43.1.13
Copyright The Author(s) 2024.This is an Open Access Article distributed under the CC BY
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respondents perceived that the use of BARS had a positive impact on work performance. Results
also demonstrated a significant increase in respondents’ level of performance (Gladys V. et al.,
2018)
Enhanced Attendance Monitoring System Using Biometric Fingerprint Recognition
In this study, an improved system for tracking and monitoring staff attendance at Callang National
High School, District 04, San Manuel, Isabela, was implemented. It used biometric fingerprint
recognition. Managing people is a difficult task for most firms, and keeping an accurate record of
attendance is crucial. Regularly taking and keeping track of an employee's attendance by hand is a
labor-intensive task that takes time. A useful system was created as a result. The main goal of the
system's design and development was to leverage biometric technologies to manage employees'
better leave and attendance records. It manages leave administration, keeps tabs on staff attendance,
logs employee data, and uses fingerprint recognition to promote involvement. The system has a
dashboard monitoring system that school directors can examine to keep track of the list of staff
members, early birds (staff members that arrived early), staff members on leave, official business,
and a statistical graph of the staff members' monthly attendance rate.
Additionally, staff can save time using the system's auto generated DTR instead of the manual
method. Automated leave management, attendance monitoring, and system-generated reports are
some of the ways in which innovation significantly impacts the enhancement of employee
attendance. Using the first quarter attendance report of SY 2028-2019 as a base of comparison with
the attendance rate of SY 2019-2020, when the system was installed, the influence of EAMS on the
employees was determined. The result demonstrates that staff attendance has increased because of
system use (Rivera, 2021).
Utilizing Convolutional Neural Networks for Fingerprint-Based Attendance Monitoring
Paper-based attendance sheets are a classic way of taking attendance that is prone to fraud,
theft, and impersonation. Automatic attendance systems that use biometrics, touch screens,
barcode badges, electronic tags, magnetic stripe cards, and other forms of identifying
technologies have been put in place to address this problem. Biometric technology uses
physiological or behavioral traits to identify a person. However, conventional biometric
systems have drawbacks like being easily damaged or changing over time, and variations in
lighting, occlusions, poses, and facial expressions can all have an impact on the accuracy of
face recognition. To ascertain if two imprints of the friction ridges on human fingers or toes
belong to the same person, fingerprint identification relies on the uniqueness of fingerprints.
Fingerprints can be divided into five main categories: whorl, left loop, right loop, tented arch,
and arch.
Numerous methods have been created to identify fingerprints by minutiae-based matching,
which entails locating important characteristics such as bifurcation and ridge termination.
Convolutional neural networks are deep learning algorithms that have been successful in
increasing recognition accuracy by automatically extracting information from fingerprint
photos. The importance of protecting personal information has grown recently, and the
Convolutional Neural Network (CNN) identification method is advised for enhancing
performance and accuracy.
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In this paper, a three-model fingerprint identification system based on CNN, Softmax, and
Random Forest (RF) classifiers is proposed. The traditional method extracts features using
CNNs and a dropout technique after separating the foreground and background regions using
the K-means and DBSCAN algorithms. In a sense, Softmax is a recognizer. Using a public
database, the suggested algorithm is tested and yields encouraging results, offering a reliable
and effective biometric identification method (Saul et.al, 2023).
3. METHODOLOGY
Modern solutions, such as the Wired Fingerprint-Based Classroom Attendance System, are
made to improve the efficiency and security of student attendance records in educational
settings. This system, which uses biometric technology, is based on the versatile Arduino Uno
microcontroller, which guarantees a dependable and accessible platform for seamless
integration. It shows the materials needed, their function for creating the fingerprint prototype,
and the methods utilized in the study to test the efficiency of the wired fingerprint-based
classroom attendance system.
Materials
Materials Uses Image
Arduino Uno
Programmed commands
Breadboard
For prototype
Power supply
Electricity source
Fingerprint
Sensor
Fingerprint recognizer
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Jumper Wires
Connections of Arduino to
breadboard to Sensor
Buzzer (1)
Direction and instructions
LED
Lights
Function signal or sign
Resistor
Passive
two-terminal electrical
Micro Sd Card
Storage for recorded files of
fingerprints
Sd Card Module
Arduino
Connections
Push Button (4)
Fingerprint Registration button
LCD
Monitor
RTC Ds3231
For timer
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Instrumentation
Using an Arduino Uno with a fingerprint sensor, breadboard, power supply, buzzer, and LED
is essential for a successful Fingerprint-Based Classroom Attendance System. This system
streamlines attendance tracking, demonstrating how the system can be practically applied in
education. Combining the Arduino Uno and fingerprint sensor swiftly identifies fingerprints
for accurate attendance. The LED and buzzer give instant feedback when a fingerprint is
recognized, making the system user-friendly.
4. RESULTS AND DISCUSSIONS
The following data shows the results and discussions of the research. The effects can be
observed from the conclusions of related literature and will serve as great advantages for future
research studies.
Results
Fingerprint-Based System
The fingerprint-based system stores student fingerprints in a geared sensor module before using
a dual-process methodology to generate file outputs. This module, which is programmed with
an Arduino Uno microcontroller, includes coded commands that set population limits for the
fingerprint system. These boundaries, established by the programmed authorities, stop
fraudulent scanning attempts beyond the specified student demographic. The highest possible
student count is dynamically determined by incorporating unique codes that tell the system to
ignore fingerprint scans larger than the predetermined population.
The second part of this two-way process involves gathering attendance information and
carefully storing it in the SD card module along with exact timestamps that indicate the precise
moment each student arrived. In particular, the recorded results from several tests demonstrate
that the fingerprint system has a time duration collection feature:
Table 2. Fpt and Sd Card Tests
Sensor
Minimum
Maximum
Average
Fingerprint Recognition
1.0 s
2 .0 s
1.7 s
The machine has been limited to cater 60 persons maximum. With a total of 600 testing, the
average rate of fingerprint recognition is 1.7s. The minimum rate being 1.0s, and the maximum
rate of 2.0s.
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Figure 1. Fingerprint Testing
The Arduino uno programming system uses a command it gives to the fingerprint sensor. The
outputs of the fingerprint system will be passed directly to the SD card, where all files are stored
for attendance records.
Figure 2 To 5. FP and SDC Codes
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Additionally, the buzzers of the fingerprint setup contain four (4) buzzers with personal
functions connected to the Arduino Uno. The two buzzers on the left side are the fingerprint
registration/back with the delete/ok option for mistake registration.
Fingerprints must be scanned and stored to avoid conflicts once used for the final testing. The
fingerprints that are successfully registered in the buzzer are the fingerprints that can be
recognized only by the sensor module and shall directly ignore those fraud-scanned
fingerprints. The two buzzers on the right-side work as the direction and instructions of the
system once it's used.
Discussions
Wired Fingerprint Prototype Testing
Two key findings highlighted the effectiveness and quality of the fingerprint sensor during the
intensive trial-and-error testing phase of the Fingerprint-Based Classroom Attendance
prototype. Interestingly, a quick message is sent to the Arduino receiver before the recognition
process starts when a student's fingerprint contacts the sensor [1]. The system's overall
effectiveness is increased by this ordered approach, which gives it an extra layer of
responsiveness. During the rigorous trial-and-error testing phase of the Fingerprint-Based
Classroom Attendance prototype, two critical findings demonstrated the quality and efficacy
of the fingerprint sensor. Interestingly, when a student's fingerprint touches the sensor, a brief
message is sent to the Arduino receiver before the recognition process begins [1]. This
systematic approach adds an extra layer of responsiveness to the system and increases its
effectiveness.
The researchers believed the primary duty was to assess the wireless fingerprint-based
classroom attendance system early in the careful testing procedure. Their active participation
guaranteed the developed prototype's functional dependability and safety. The researchers
ensured they fully understood the fingerprint sensor's capabilities by closely monitoring and
assessing every detail of its operation during this phase. Excellent results were obtained from
the fingerprint sensor during capability and capacity testing. It demonstrated a strong ability to
recognize and authenticate registered fingerprints, highlighting its dependability in a classroom
setting. This accuracy in identifying fingerprints that have been registered adds a great deal to
the system's overall reliability and strengthens its suitability for efficient attendance
management.
Schematic Diagram
Figure 6. Schematic Diagram
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5. CONCLUSIONS AND RECOMMENDATIONS
Conclusions
To conclude, this research aimed to thoroughly investigate the accuracy of a Wired Fingerprint-
Based Classroom Attendance System Using an Arduino UNO Microcontroller within the
educational institution of Bayugan National Comprehensive High School. The study met its
objectives, which included identifying the materials required to build a functional prototype,
precise assembly of Arduino UNO components, accurate schematic diagram design, the
efficient development of a fully operational Fingerprint-Based Attendance System prototype,
and a thorough assessment of the Arduino Uno's performance in sensor testing. The biometrics
system built with Arduino Uno efficiently tracked the attendance of the researchers as well as
the students in the classrooms where the procedure was implemented. They are featuring
critical features of precision, reliability, and capability. The results also showed that the system
is competent and qualified for full implementation. Teachers and class monitors can save time
and work by using the system's accurate and quick execution time in real-time attendance
checking, which replaces the traditional/manual method. Teachers can devote more time to
their lectures because there will be no disruption or waste of time in taking student attendance.
This system is essential for precise and time-saving attendance checking in schools and
universities.
Recommendations
Creating a wired fingerprint-based classroom attendance system using Arduino UNO
microcontroller involves integrating various components for efficient operation.
Recommendations include adapting the system for rural districts with limited internet
connectivity, implementing robust data security measures to safeguard fingerprint data, and
adhering to data protection laws. Additionally, establishing a regular maintenance schedule is
crucial to prevent issues and ensure accuracy. Students are encouraged to actively participate
in the implementation by cooperating with fingerprint scanning, while teachers are urged to
embrace and adapt to the new system for efficient classroom attendance management.
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