ARTIFICIAL INTELLIGENCE-POWERED ATTENDANCE SYSTEM USING HAMMING DISTANCE ALGORITHM AND BIOMETRIC AUTHENTICATION

Volume-09 Issue 10, October-2025 ISSN: 2456-9348 Impact Factor: 8.232 International Journal of Engineering Technology Research & Management Published By: https://www.ijetrm.com/ IJETRM (http://ijetrm.com/) [142] ARTIFICIAL INTELLIGENCE-POWERED ATTENDANCE SYSTEM USING HAMMING DISTANCE ALGORITHM AND BIOMETRIC AUTHENTICATION Janzar Vaughn de Belen [email protected] UG Students, College of Computing Studies, Universidad de Manila, Philippines Wynelle F. Quillo [email protected] UG Students, College of Computing Studies, Universidad de Manila, Philippines John Denver B. Maglalang [email protected] UG Students, College of Computing Studies, Universidad de Manila, Philippines Alan Christian R. Oduya [email protected] UG Students, College of Computing Studies, Universidad de Manila, Philippines Ronald B. Fernandez rbfernandez04217600011[email protected] Professor, College of Computing Studies, Universidad de Manila, Philippines ABSTRACT Education provides students with knowledge, hones their skills, and teaches them values. With this, active class participation is important for students’ academic journey. Student attendance is a crucial factor in determining student academic performance, as it allows them to participate in class, gain proper knowledge, and have access to learning materials. However, traditional attendance methods have become inefficient, as it takes a lot of time to take and is prone to human error and fraudulent activities, including proxy signing. To address this problem, the proponents propose an attendance system that is integrated with radio-frequency identification (RFID) and fingerprint authentication, ensuring that only the students can verify their own attendance. With the use of Arduino Uno and the NodeMCU module, the system will be able to scan and compare attendance records stored in a central database. With the help of artificial intelligence (AI), the proposed attendance system is able to feature an alert system that monitors student attendance and notifies the educators when students reach a specified number of absences that makes them a candidate to drop out of school. The proposed system will be tested in Doña Teodora Alonzo High School to determine its effectiveness and readiness to be implemented in educational institutions. Keywords: Attendance System, Artificial Intelligence, Radio-Frequency Identification, Arduino Uno, NodeMCU INTRODUCTION Artificial Intelligence (AI) and Machine Learning (ML) are both leading factors of technological advancements. Artificial Intelligence (AI) allows machines to make decisions and think like humans do. On the other hand, Machine Learning (ML) refers to the ability of machines to make predictions by learning and adapting to data given. Artificial Intelligence (AI) and Machine Learning (ML) elevate industries, including education, by helping people make tasks efficient. In education, these technologies are often used to support teaching and Volume-09 Issue 10, October-2025 ISSN: 2456-9348 Impact Factor: 8.232 International Journal of Engineering Technology Research & Management Published By: https://www.ijetrm.com/ IJETRM (http://ijetrm.com/) [143] administrative tasks, such as attendance monitoring. The proponents proposed a system that will make attendance checking for educational institutions more efficient and secure through the integration of two-factor authentication, using Radio Frequency Identification (RFID) and fingerprint scanning. The application of biometric in education, particularly in identity management, class attendance, e-evaluation, security, learning analytics, and student motivation—is important in automating the process of verifying identities and enhancing institutional security (Hernandez-De-Menendez et al. 2021) Education shapes society by equipping students with the proper knowledge, skills, and values. The value of class participation is an important factor in students’ development, as it improves performance through active class participation. Attendance tracking is a significant administrative task that highly impacts student outcomes. Regular attendance in classes directly influences the overall academic performance of students, as it enables students to attend classes and engage in activities, access learning materials, and communicate with lecturers to clarify lessons covered. Policymakers and administrators often considered attendance to be a less significant factor in a student's academic success, believing that what truly matters is that students are being taught and have access to learning materials. However, according to Gottfried and Hutt (2019), focusing on content alone does not matter if the students are not fully engaged in the lessons the teachers prepare. Absences might be fine occasionally, but there is a possibility that students will miss an important lesson or activity that highly affects their grades or makes them fall behind. Traditional methods of attendance checking present numerous challenges that undermine efficiency and accuracy. Signature-based attendance, on the other hand, takes less time but is subject to fraudulent activities through proxy signing, where students can sign for students that are absent in the class. These are among the issues associated with such forms of attendance and may cause records to be inaccurate, thus compromising the credibility of existing attendance tracking and monitoring measures in place. The AI-powered attendance system aims to modernize attendance checking and monitoring in educational institutions by integrating features, including biometric fingerprint scanning and Radio Frequency Identification (RFID). RFID is an important technology to be integrated into attendance systems for secure and consistent attendance tracking (Ahmad and Nababa. 2021), while biometric systems integrated with AI, including fingerprint, transforms traditional biometric methods into a much adaptive and smarter authentication method (Gupta. 2024). The implementation of two-factor authentication will ensure the accuracy of attendance records, minimizing human errors and attendance fraud, such as record modifying, alteration, and proxy attendance signing. In addition to secure attendance logging, the system is also designed to monitor and respond to student absenteeism. The proposed system will integrate various algorithms that will ensure the accuracy, reliability, and efficiency of the attendance system. Minutiae-based fingerprint authentication for biometric authentication will be used to identify and match fingerprints by recognizing features, such as ridge endings. The Hamming Distance Algorithm will be used to recognize Radio Frequency Identification (RFID) tags. These inputs are captured through the NodeMCU and Arduino microcontroller that is connected to the fingerprint and Radio Frequency Identification (RFID) module. Incorporating Internet of Things (IoT) methodologies and NodeMCU microcontrollers enables the system to gather attendance data in real time and securely transfer it to a cloud server, thus improving data integrity and accessibility (Sinha et al. 2024). Attendance tracking begins with students tapping on their Radio Frequency Identification (RFID) tags. After successful tapping, students will then be asked to further verify their identities through fingerprint authentication. These inputs are then processed by the Arduino microcontroller, where the Radio Frequency Identification (RFID) and fingerprint module are connected. The NodeMCU that is connected as well to the Arduino microcontroller, will transmit the input attendance to the central database. The double-layered verification process ensures that it is the actual student taking the attendance. If a student fails to attend classes, the system will notify the assigned teacher that the student is absent for the day. Reaching a certain number of absences might cause the student to drop out of school. Volume-09 Issue 10, October-2025 ISSN: 2456-9348 Impact Factor: 8.232 International Journal of Engineering Technology Research & Management Published By: https://www.ijetrm.com/ IJETRM (http://ijetrm.com/) [144] The integration of an AI-powered attendance system into educational institutions provides several benefits. By automating the process of attendance checking and recording, educators and administrators will be able to dedicate time to more important academic responsibilities, allowing educators to focus more on providing students quality education. The integration of multi-layered verification of students also prevents activities of fraud, such as proxy signing, ensuring that student records are accurate. Real-time data processing allows educators to make reports and analyze students’ attendance patterns. The AI-powered attendance system benefits both students and educators by improving the attendance-taking experience, making attendance management accurate, secure, and efficient. With real-time absence notification, the teachers will be able to take immediate action regarding student absenteeism, helping students to stay on track academically. OBJECTIVES The study aims to develop an attendance system for educational institutions. The system is integrated with Artificial Intelligence (AI) and secure authentication methods, including Radio Frequency Identification (RFID) and fingerprint authentication. Additionally, the system features a notification system that alerts educators when students reach a specified number of absences. These features would enhance security, and efficiency, of attendance tracking in academic settings. METHODOLOGY This section outlines the development process that will be followed for the development of the system. A system development model is an approach in system development that serves as a guide from planning up to the implementation of the project. Each stage in the model is critical to the overall outcome of the system. The study will follow agile methodology to ensure continuous improvement throughout the development process using an iterative approach. The use of agile methodology as the system development model will keep the relevance of the system over time. Through iteration, the potential issues will easily be identified, and constant refinement can be made. Agile methodology follows a six-step process, including: Figure 1 Agile Methodology 1) Requirements: To determine the feasibility of developing an AI-powered attendance system integrated with biometric and RFID for academic institutions, the researchers conducted an initial survey to students and faculty regarding their experiences with traditional methods and the need for an automated attendance tracking method. Results showed that only 64% of the respondents believed that the current attendance tracking method in their school is secure and can prevent fraudulent activities, while only 56% of the respondents said that the issues regarding attendance are quickly resolved by the school administration. After all, 80% of the respondents have witnessed students signing in attendance for another who is not present in class, which supports the low Volume-09 Issue 10, October-2025 ISSN: 2456-9348 Impact Factor: 8.232 International Journal of Engineering Technology Research & Management Published By: https://www.ijetrm.com/ IJETRM (http://ijetrm.com/) [145] percentage of traditional methods being secure. To further validate the findings, and find a solution to the said problems, the proponents seek professional help by conducting an interview with faculty and school principal. The problems identified are then analyzed, which leads to the solution of developing an AI-powered attendance system using RFID and biometric authentication, that solves the issues regarding fraudulent activities, time consumption, and manual entry errors. To further increase the effectiveness of the system, the proponents also applied an alert system that notifies educators when a student reached a specified number of absences that might drop them out of school 2) Design: The proponents carefully planned the system by creating flowcharts, prototypes, and diagrams that help to visualize what the system would look like as well as how data flows within the system. The proposed system will incorporate features for authentication, including fingerprint biometrics and the use of RFID. Hardware includes Arduino Uno for handling fingerprint and RFID inputs, alongside NodeMCU, which transmits the input data into the centralized database. A dashboard is also designed for educators, which is made user-friendly for easy navigation, promoting usability among users. Included in the admin dashboard is the absence tracking feature that notifies educators of reaching a specified number of absences. 3) Develop: The proponents used Hamming Distance Algorithm to compare stored biometric data and RFID tags to verify and accept even the slight variation, especially with fingerprint that is naturally noisy due to the nature of the skin. Arduino sketches are developed to control the RFID and fingerprint scanner to enable the microcontroller to capture input data and compare it with the database for verification. Meanwhile, NodeMCU is configured to manage wireless data transfer of attendance records to the central database. 4) Testing: Following the development of the proposed system, the proponents then conducted an interview and pilot testing with the stakeholder, Doña Teodora Alonzo High School, for further improvements for the proposed attendance system. Improvements and revisions were made to meet the needs and provide proper services to the educational institution. 5) Deployment: The deployment of the AI-powered attendance system in Doña Teodora Alonzo High School has been made, allowing students and faculty members to take and record attendance without worrying about fraudulent practices and inconsistencies with records. Real-time access and monitoring of attendance records allow educators and school administrators to conduct a thorough analysis on student absenteeism which affects their academic performance. With the help of the alert feature, educators will be able to make immediate intervention to students before they reach the absence threshold. 6) Maintenance: After the deployment, the proponents still monitor the performance of the attendance system. Since the attendance system is built with devices, like microcontrollers and scanners, the proponents must ensure that devices used are connected properly, and functioning as intended. It must be ensured that data from the central database is successfully transmitted and retrieved. Lastly, the maintenance phase involves system updates and patches so that the implemented attendance system remains relevant to the current education setting. RESULTS AND DISCUSSION The proponents developed a survey questionnaire in line with ISO/IEC 25010 to assess the attendance system’s functionality, reliability, usability, and overall performance. A total of 100 respondents, including faculty members and students, were asked to test the functionalities of the system and provide feedback on the attendance system. The system resulted in a positive rating in terms of system functionality, usability, and security. While few suggested few improvements to functions, especially with the alert feature. Functional Suitability From 100 respondents, positive feedback is received, agreeing that the system effectively meets functionals requirements. The system received a mean score of 4.26 (Very Good) for functional suitability, wherein respondents confirmed that RFID scanning consistently records attendance, the reliability of integrating fingerprint, and reporting features, though few suggested enhancements in report customization. The absence notification also received a high score for functioning as intended. Overall, responses received confirmed that the system delivered the essential functionality for attendance tracking and monitoring. Volume-09 Issue 10, October-2025 ISSN: 2456-9348 Impact Factor: 8.232 International Journal of Engineering Technology Research & Management Published By: https://www.ijetrm.com/ IJETRM (http://ijetrm.com/) [146] Figure 2 Functional Suitability Functional Correctness Findings showed a strong functional correctness for the attendance system, where respondents agreed that RFID and fingerprint scanning accurately authenticates and effectively rejects invalid inputs. The survey confirmed that timestamps were reliable, and reports are generated accurately. Although few disagreements were made, majority of the respondents believed that the system minimized errors and authentication process are accurate, receiving an average score of 4.21 (Very Good). Figure 3 Functional Correctness Functional Appropriateness The survey resulted with a strong system appropriateness, where responses confirmed that proxy attendance was prevented and that the features, including RFID, fingerprint, and absence notification meet the needs of an academic institution, aligning with everyday school requirement. Many agreed on the idea that the attendance system is more efficient than traditional methods, especially in terms of time consumption, proving that the system was practical and well-suited in academic environments. The functional appropriateness category received an average score of 4.25 (Very Good). Figure 4 Functional Appropriateness Volume-09 Issue 10, October-2025 ISSN: 2456-9348 Impact Factor: 8.232 International Journal of Engineering Technology Research & Management Published By: https://www.ijetrm.com/ IJETRM (http://ijetrm.com/) [147] Usability Most respondents found the system is easy to learn. First time users reported that RFID tapping, and fingerprint registration instructions were understandable and clear. In the administrator and educators’ dashboard, surveys show that teachers easily learned the dashboard with minimal guidance during their first experience. Usability and learnability received a mean score of 4.29 (Very Good), proving the system’s user friendliness among students and teachers no matter what their technical expertise is. Figure 5 Usability Operability The system operability was strongly agreed, where the survey resulted in RFID and fingerprint features responding quickly and accurately. Receiving an average score of 4.38 (Very Good), the attendance system is confirmed to perform consistently and reliably under different conditions and enables users to conduct attendance without difficulty. Survey questions on this part also confirmed that the educators can easily filter searches within the dashboard, making attendance monitoring and analyzing easier and more efficient. Figure 6 Operability User Interface With a mean score of 4.31 (Very Good), the system received a considerably high rating when it comes to navigation, learnability, and overall design, stating that the interface is professional and user-friendly. Survey revealed that prompt messages and results from the dashboard and attendance screen were readable and easy to understand. Layouts, fonts, and overall design also received positive feedback, confirming that visual presentation was clear, with few suggesting some improvements with color schemes. Volume-09 Issue 10, October-2025 ISSN: 2456-9348 Impact Factor: 8.232 International Journal of Engineering Technology Research & Management Published By: https://www.ijetrm.com/ IJETRM (http://ijetrm.com/) [148] Figure 7 User Interface Confidentiality The security of data received a high score averaging 4.27 (Very Good), where respondents believed that RFID, fingerprint, and personal data were stored securely. Users expressed a strong trust with the system’s ability to ensure that personal and academic records are accessible only to authorized personnel. The positive feedback from users confirmed that the attendance system meets confidentiality standards, ensuring ethical and secure data management in academic setting. Figure 8 Confidentiality Integrity System integrity received positive feedback as well, whereas respondents agreed that attendance records were securely recorded and cannot be tampered with. Although many believed that attendance taking are accurate and consistent, a small percentage still have concerns with technical disruptions that might result in failure to record their attendance. Overall, the integrity resulted with an average score of 4.24 (Very Good), confirming that records are safe from data manipulation. Figure 9 Integrity Volume-09 Issue 10, October-2025 ISSN: 2456-9348 Impact Factor: 8.232 International Journal of Engineering Technology Research & Management Published By: https://www.ijetrm.com/ IJETRM (http://ijetrm.com/) [149] Authentication Results show that respondents believed in the system’s ability to authenticate the users accurately. With the combination of RFID and fingerprint authentication, users agreed that only the actual student can verify and take their own attendance, preventing fraudulent activities. An average score of 4.22 (Very Good) was received, validating that two-factor authentication, specifically RFID and fingerprint authentication provided a secure layer of protection against unauthorized access, while also ensuring accurate attendance records. Figure 10 Authentication ACKNOWLEDGEMENT We extend our deepest and sincere appreciation to all who supported and helped us throughout the process and development of the study titled “Artificial Intelligence-Powered Attendance System Using Hamming Distance Algorithm and Biometric Authentication”. First of all, we would like to thank our dear university, Universidad de Manila, for giving us the opportunity to apply our knowledge and skills through this study. We also express our gratitude to Mr. Ronald B. Fernandez, our capstone advisor, for his guidance and expertise, giving us valuable insights that helped us accomplish the study. To the panelists who provided us with knowledge, honest criticisms and suggestions to further improve the study. We are grateful for Doña Teodora Alonzo High School, our stakeholders, for letting us conduct, test, and implement our study in their academic institution. To our dear families for their never-ending love and support, which motivated us to accomplish this study even in difficult situations. Finally, we give our deepest gratitude to God, who granted us strength, knowledge, ability that allow us to accomplish this study. Without them, the research and development of this study wouldn’t be possible. CONCLUSION The development and implementation of the project, “Artificial Intelligence-Powered Attendance System Using Hamming Distance Algorithm and Biometric Authentication,” addressed the issues of traditional attendance tracking methods regarding inefficiency, inaccuracy, and being prone to fraud. Integrating RFID and fingerprint authentication enabled the system to be secure and reliable when it comes to verifying student identity. Furthermore, the absence notification, aided by AI, provided educators to immediately act into student absenteeism, allowing timely intervention. The successful development of the study was supported by various related studies, along with survey results that confirmed the system’s performance in terms of functionality, usability, and security. In conclusion, the proposed system integrated with artificial intelligence, RFID, and biometric technology significantly enhances attendance tracking within educational institutions, thereby providing an accurate, and secure attendance records, promoting student engagement and academic success. REFERENCES [1] Hernandez-De-Menendez, M., Morales-Menendez, R., Escobar, C. A., & Arinez, J. (2021). Biometric applications in education. 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