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Journal articles on the topic 'Attendance tracking'

Author: Grafiati

Published: 2 June 2025

Last updated: 31 July 2025

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1

Dixit, Pallavi. "Student Attendance Tracking App." INTERNATIONAL JOURNAL OF SCIENTIFIC RESEARCH IN ENGINEERING AND MANAGEMENT 09, no. 05 (2025): 1–9. https://doi.org/10.55041/ijsrem47386.

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Abstract — As usual, if many students are attending the lectures, their attendance tracking may become time consuming. Furthermore, there are some possibilities that students could cheat the lecturers of their attendance in the classroom. Therefore, a reliable method to manage the attendance tracking has become a critical issue. This paper aims to propose an attendance tracking app using an Android smartphone/Laptop/Tablet equipped with email ID and Access by only Teacher . Students Attendance can constantly tracked by one another by using smartphones to check and show their attendance automat

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2

Kavitha Soppari, Minnu Sri Thumnoori, Sumanth Gangalam, and Dheeraj Kumar Raju Batraju. "QR Code attendance deputation system." World Journal of Advanced Research and Reviews 25, no. 1 (2025): 1949–55. https://doi.org/10.30574/wjarr.2025.25.1.0103.

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Traditional attendance systems can be time- consuming, prone to errors, and susceptible to proxy Atten- dances, where individuals falsely mark their presence in place of others. The” QR Code Attendance System” is a fast, efficient, and user-friendly solution for tracking attendance through QR codes, specifically designed to address these challenges. By leveraging web-based technology, it automates and streamlines the attendance process, significantly reducing the likelihood of attendance manipulation. Built with HTML, CSS, and Django, the system offers a seamless, real-time interface for marki

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Nurfaizi, Kelfin, and Djarot Hindarto. "Web-Based Student Internship Attendance Application System for Effective Student Attendance Monitoring." International Journal Software Engineering and Computer Science (IJSECS) 3, no. 3 (2023): 238–45. http://dx.doi.org/10.35870/ijsecs.v3i3.1760.

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The Web-Based Student Internship Attendance Application System revolutionizes the management of internship programs in higher education institutions and companies. This innovative platform addresses the critical need for a streamlined process in handling internship attendances, a vital component of higher education that equips students with essential real-world experience. Traditional methods of managing these attendances have been fraught with complexity and inefficiency. Our system introduces a user-friendly, web-based interface that enables students to record their daily attendance effortle

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Ukirde, Nikita Hanmant. "Attendance Management." INTERANTIONAL JOURNAL OF SCIENTIFIC RESEARCH IN ENGINEERING AND MANAGEMENT 08, no. 04 (2024): 1–5. http://dx.doi.org/10.55041/ijsrem30834.

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Attendance management systems play a crucial role in various organizations by efficiently tracking and managing employee or student attendance records. This abstract explores the design, implementation, and benefits of an attendance management system. The system utilizes modern technologies such as biometrics, RFID, or mobile applications to accurately record attendance data. Features include real-time monitoring, automated notifications, and comprehensive reporting capabilities. The system not only simplifies administrative tasks but also enhances accountability, productivity, and transparenc

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Hope, Soko. "Attendance tracking system using geofencing." i-manager's Journal on Information Technology 13, no. 1 (2024): 22. http://dx.doi.org/10.26634/jit.13.1.20756.

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Traditional methods of managing attendance records, particularly in educational institutions like schools, often rely on manual written records, which can be limited by issues such as lack of transparency and accuracy. This study introduces a web application that aims to overcome these limitations by automating tasks and improving transparency and accuracy through the use of geofencing technology. By creating virtual boundaries around predefined areas and requiring teachers to record their location coordinates during attendance, the system can accurately determine their presence or absence bas

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Chaturvedi, Pushkar Nath. "AI And Imaged Processing Based Student’s Attendance System." INTERNATIONAL JOURNAL OF SCIENTIFIC RESEARCH IN ENGINEERING AND MANAGEMENT 09, no. 04 (2025): 1–9. https://doi.org/10.55041/ijsrem45555.

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Abstract Tracking attendance is a crucial function for educational institutions and organizations. To simplify this process, we propose an AI-based solution. This system can recognize known students, update records of attendance and show information of the student on screen. It also sends information to Firebase that stores both student and image data, thus it can be easily obtained. The code is user friendly and displays attendance with student detail and also marks attendance by face recognition which prevents false attendance. The system consists of a database of facial images of students o

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Bhargav, M.S.S, M.S.S. Bhargav, R.Anirudh Reddy, K.Sai Chandan, and K.Mani Raj. "Attendance Harnessing IoT for Intelligent Tracking." International Journal of Microsystems and IoT 2, no. 11 (2024): 1321–28. https://doi.org/10.5281/zenodo.14760115.

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This abstract provides an overview of an Attendance Monitoring System that leverages IoT, Cloud, AI, and ML technologies to enhance efficiency and accuracy in tracking attendance records. The system integrates IoT-enabled devices, such as biometric sensors, RFID/NFC scanners, or facial recognition cameras, to capture attendance data in real-time. These devices are strategically placed at key entry points, classrooms, or workspaces, ensuring a seamless and non-intrusive attendance recording process. Attendance data is securely stored in the cloud with the real time data process. By using these

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Lebedynskyi, Andrii. "Using JavaScript for Automating Attendance Tracking in the Moodle Learning System." Bulletin of Kharkov National Automobile and Highway University 1, no. 103 (2023): 7. http://dx.doi.org/10.30977/bul.2219-5548.2023.103.1.7.

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Problem: The article addresses the issue of automating attendance tracking for students in the context of distance learning in higher education institutions. Methodology: The paper analyzes existing methods of student attendance tracking in virtual learning environments, identifying their advantages and drawbacks. Additionally, it proposes a JavaScript-based solution for the automatic attendance tracking, generating a CSV file that is subsequently uploaded to the Moodle web server. Goal: The primary goal of the article is the development and exploration of a software tool capable of automating

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9

Gupta, Sachin, Vipin Jain, and Vinayak Anil Bhat. "Next-generation attendance tracking: Automated face detection for lecture attendance." Multidisciplinary Science Journal 5 (August 29, 2023): 2023ss0309. http://dx.doi.org/10.31893/multiscience.2023ss0309.

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Face detection technology has garnered much interest due to its potential uses in industries like face identification and video surveillance systems. In addition to being a component of the automatic face recognition framework, real-time face detection is now becoming its study area. There are numerous methods to handle the problem of face detection. Traditional methods of manual attendance tracking in lecture halls are time-consuming, prone to errors, and lack efficiency. Next-generation attendance tracking systems are incorporating automated face detection technology to address these challen

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Kumar, Akash. "Face Recognition Attendance Systems." International Journal for Research in Applied Science and Engineering Technology 13, no. 6 (2025): 318–21. https://doi.org/10.22214/ijraset.2025.71915.

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In recent years, deep learning-based face recognition systems have emerged as powerful tools for automating attendance tracking in educational institutions and workplaces. This paper explores the development and implementation of such systems, leveraging state-of-the-art convolutional neural networks (CNNs) to achieve high accuracy rates. By addressing challenges such as dataset size and real time deployment, this research aims to provide a comprehensive understanding of the potential applications and benefits of deep learning in attendance tracking.

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Y., Joshna, Meera Alphy Dr., and K.Shirisha. "Attendance Record Management System." Recent Trends in Androids and IOS Applications 6, no. 3 (2024): 17–23. https://doi.org/10.5281/zenodo.12780613.

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<em>The Student Attendance Real-time project is a software system designed to streamline and enhance the process of attendance management within educational institutions. This addresses the challenges associated with manual attendance tracking by introducing a user-friendly and efficient solution. The system automates the process of recording student attendance on a daily basis, reducing the burden on teachers and minimizing errors. The proposed system calculates the daily attendance percentage for each student in real-time. Alerts are triggered for students with attendance falling below a pre

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Singh,, Seependra. "BIOMETRIC ATTENDANCE SYSTEM." INTERANTIONAL JOURNAL OF SCIENTIFIC RESEARCH IN ENGINEERING AND MANAGEMENT 08, no. 05 (2024): 1–5. http://dx.doi.org/10.55041/ijsrem35127.

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This paper presents a biometric fingerprint attendance system designed to enhance accuracy, security, and efficiency in attendance tracking. The system utilizes fingerprint recognition technology for data acquisition, preprocessing, feature extraction, and matching. Key challenges, including data privacy and security, are addressed with robust solutions. Comprehensive testing demonstrates the system's effectiveness in reducing time theft and improving employee accountability. The findings highlight the potential of biometric systems to revolutionize attendance management, suggesting avenues fo

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K.M., Ms Kamble. "RFID AND GSM BASED ATTENDANCE SYSTEM." INTERANTIONAL JOURNAL OF SCIENTIFIC RESEARCH IN ENGINEERING AND MANAGEMENT 08, no. 04 (2024): 1–5. http://dx.doi.org/10.55041/ijsrem31989.

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We have developed a quick and simple solution to the challenge of tracking every student's presence in a class by using radio frequency identification (RFID) to control student attendance with little to no teacher intervention.This project is to use radio frequency identification (RFID) technology to streamline the attendance recording system. A web-based application called RFID based Attendance recorder with SMS alert system will be created to address the aforementioned issue. Database support and GSM (Global System for Mobile communication) technologies will be used in the development of the

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j Abhishek, Meghra. "Facial Capturing Attendance Tracking System Using Computer Vision." INTERANTIONAL JOURNAL OF SCIENTIFIC RESEARCH IN ENGINEERING AND MANAGEMENT 09, no. 03 (2025): 1–9. https://doi.org/10.55041/ijsrem42266.

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Traditional attendance systems, such as manual roll calls and biometric methods, have drawbacks such as being time-consuming, prone to human error, and vulnerable to proxy attendance. Additionally, faculty members manually updating attendance in Excel increases workload and the risk of mistakes. The proposed facial recognition-based attendance system eliminates manual attendance entry and enables easy web-based access, providing an efficient solution for attendance management. Using webcams, the system ensures a contactless and effective process, reducing manual data entry through automatic at

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C, Dr Devaraj Verma. "Facial Biometrics-Based Attendance Tracking System." International Journal for Research in Applied Science and Engineering Technology 11, no. 5 (2023): 4525–30. http://dx.doi.org/10.22214/ijraset.2023.52698.

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Abstract: Facial attendance using face recognition and detection technology is a modern method of recording attendance based on facial features. This method is commonly used in automated attendance management systems and is efficient in tracking employee or student attendance without physical interaction. Face recognition has numerous applications such as security, surveillance, and human-computer interaction. This research aims to compare the performance of two popular face recognition techniques: HOG and KNN. The HOG algorithm extracts feature from an image using pixel intensity gradients wh

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Emily Sing Kiang Siew, Zhi Yan Chong, Sah Nah Sze, and Richki Hardi. "Streamlining Attendance Management in Education: A Web-Based System Combining Facial Recognition and QR Code Technology." Journal of Advanced Research in Applied Sciences and Engineering Technology 33, no. 2 (2023): 198–208. http://dx.doi.org/10.37934/araset.33.2.198208.

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Attendance tracking has long posed challenges in educational institutions due to the inefficiency and error-prone nature of traditional paper-based methods. In response, many institutions have embraced web technologies and automated attendance systems, incorporating biometrics, QR codes, barcodes, and RFID-based technologies. However, the applicability of these systems may vary across different educational settings. This paper introduces a web-based student attendance management system that combines facial recognition technology and QR codes to address the challenges associated with manual att

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SHRUTHI, SRINARAMDAS, YESHASHWINI SUNKARA, MEERA ALPHY Dr., and K. SHRISHA Ms. "Attendance Tracker." Recent Trends in Computer Graphics and Multimedia Technology 6, no. 3 (2024): 32–39. https://doi.org/10.5281/zenodo.13364771.

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<em>The Student Attendance Management System (SAMS) modernizes the process of recording and managing student attendance, replacing traditional paper registers and manual entry with efficient digital solutions. Utilizing web and mobile applications, biometric and RFID systems, and cloud computing, SAMS ensures accurate, real-time attendance tracking. Its scalable, secure architecture stores records safely, accessible to authorized personnel.</em> <em> </em> <em>Key features include comprehensive reports and analytics that provide insights into attendance patterns, supporting interventions

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18

P, Sahoo. "A Rfid Based Attendance Tracking System." IOSR Journal of Environmental Science, Toxicology and Food Technology 2, no. 2 (2012): 12–17. http://dx.doi.org/10.9790/2402-0221217.

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Kazi, Sanam, Farhan Pasha, Farzana Gorme, and Hozefa Bata. "Raspberry Pi in Attendance Tracking System." International Journal of Computer Applications 162, no. 7 (2017): 15–19. http://dx.doi.org/10.5120/ijca2017913382.

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20

Ubaid, Mohammad. "Intelligent Attendance Tracking System VIA Webcam." International Journal of Science, Engineering and Technology 13, no. 2 (2025): 1–4. https://doi.org/10.61463/ijset.vol.13.issue2.305.

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Ubaid, Mohammad. "Intelligent Attendance Tracking System VIA Webcam." International Journal of Science, Engineering and Technology 13, no. 2 (2025): 1–4. https://doi.org/10.61463/ijset.vol.13.issue2.306.

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V, Kiruthika Priya. "Facial Recognition Based Attendance Tracking System." International Journal for Research in Applied Science and Engineering Technology 13, no. 4 (2025): 6836–47. https://doi.org/10.22214/ijraset.2025.69872.

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Abstract: Traditional attendance systems are vulnerable to fraudulent practices and inefficiencies. This paper proposes a facial recognition-based attendance tracking system enhanced with anti-spoofing capabilities using YOLOv5. By integrating real-time face detection, recognition, and liveness verification, the system ensures accurate and secure attendance logging. It further integrates with a web portal via ThingSpeak API to notify absenteeism. Built using Python libraries including OpenCV, face_recognition, and TensorFlow, the system captures live video streams, detects faces, and matches t

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23

Sapkal, Snehal Satish. "SMART ATTENDANCE TRACKER USING FACE RECOGNITION." International Scientific Journal of Engineering and Management 04, no. 06 (2025): 1–9. https://doi.org/10.55041/isjem04181.

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Abstract - This project improves attendance tracking by using face recognition instead of manual or card-based methods. It uses OpenCV and machine learning to recognize faces in real time and mark attendance automatically. This helps avoid common problems like errors, delays, and fake attendance. The system is developed using Python and OpenCV for real-time face recognition, utilizes machine learning techniques for accurate identification, and stores attendance data in a MySQL database to manage records efficiently. Keyword’s: FaceRecognition, Attendance Tracking, Real-Time Monitoring, OpenCV,

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Pathania, Kannan, Chitvan Bhardwaj, and Archana Mongia. "An OpenCV and Single-Camera Facial Recognition Real-Time Attendance System." INTERANTIONAL JOURNAL OF SCIENTIFIC RESEARCH IN ENGINEERING AND MANAGEMENT 08, no. 11 (2024): 1–7. https://doi.org/10.55041/ijsrem39233.

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Abstract--Traditional attendance mechanisms have fallen short of providing an actual guarantee in attendance, especially in advanced commercial and academic milieus, based on the general practice of proxy attendance. This paper details the implementation of an attendance system based on technologies like cameras and facial recognition capabilities. By prohibiting unlawful attendance using proxy mechanisms, this system seeks to improve the accuracy of attendance tracking. We present a strong framework that takes, processes, and validates facial photos in real- time by utilising developments in

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Prapti V. Kallawar and Dr. Suresh S. Asole. "Divergent Techniques of Attendance Management." International Journal of Scientific Research in Science and Technology 11, no. 2 (2024): 458–62. http://dx.doi.org/10.32628/ijsrst52411285.

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In order to keep record of students or employees, tracking their presence and absence is important. This is done by attendance management system. Maintaining attendance record manually is not at all a feasible task and this also leads to human errors, consumes more time, increases administrative burden, it is also insecure, etc. To overcome with these issues various Attendance Management Systems are developed based on recent technological advancements. This paper gives a brief overview of diverse methods for tracking attendance.

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Singh, Archana, Dr Ajay Sahu, Avinash Nishad, Atul Yadav, and Astendra Pratap. "Smart Campus: Based Automatic Attendance System Using Photo Face Recognition." International Journal of Innovative Research in Advanced Engineering 11, no. 12 (2024): 870–74. https://doi.org/10.26562/ijirae.2024.v1112.06.

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This review examines a number of experiments that use the Smart Attendance system to record attendance using facial recognition. In many organizational and educational contexts, managing attendance effectively and accurately is essential. Manual attendance tracking using traditional methods is laborious and prone to mistakes. The suggested system recognizes and confirms the identity of people in a certain context by using computer vision and deep learning techniques. It enables smooth and effective attendance tracking by using facial recognition algorithms to capture and match facial features

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Usiobaifo, Agharese Rosemary, and Roseline Oghogho Osaseri. "DESIGN AND IMPLEMENTATION OF A MOBILE FINGERPRINT ATTENDANCE SYSTEM FOR STUDENT AND LECTURERS." FUDMA JOURNAL OF SCIENCES 9, no. 5 (2025): 232–38. https://doi.org/10.33003/fjs-2025-0905-3136.

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This study addresses the inefficiencies of traditional attendance tracking methods in educational institutions by developing a mobile fingerprint-based attendance system. Built with Android Studio, Java, and Firebase, the system automates attendance verification during examinations, providing improved accuracy and security. Students register their fingerprints, which are securely stored, and use the mobile app to authenticate their attendance in real-time. This reduces administrative workload, minimizes errors, and enhances overall efficiency. The system's object-oriented design ensures scalab

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Yakhub, Shaik. "Quantification of Facial Geometrical Dimension for Student Attendance Tracking." International Journal of Innovative Computing 14, no. 2 (2024): 41–47. http://dx.doi.org/10.11113/ijic.v14n2.452.

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The traditional method of manual attendance-taking has been used in educational institutions for decades which have consumed one-sixth amount of class time for attendance marking. Great research on attendance systems has come up with techniques like biometrics, NFC’s and QR codes. Moreover, with advancements in technology, this research project can provide a more efficient and effective solution. This research project utilizes image processing, computer vision and facial recognition technology to mark the attendance of the students in class. The objectives of the system are registration of fac

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B. Rivera, Ronald. "Enhanced Attendance Monitoring System using Biometric Fingerprint Recognition." International Journal of Recent Technology and Engineering 9, no. 5 (2021): 1–4. http://dx.doi.org/10.35940/ijrte.e5070.019521.

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In this study, an enhanced attendance monitoring system using biometric fingerprint recognition in tracking and monitoring employees’ attendances for Callang National High School, District 04, San Manuel, Isabela was introduced. For most organizations, handling people is a daunting job in which it is very important to maintain an accurate record of attendance. Taking and maintaining the attendance of employee manually on a regular basis is a big activity that requires time. For this reason an effective system was designed. The system was designed and developed primarily to improve the monitori

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Izang, Aaron Afan, Chigozirim Ajaegbu, Wumi Ajayi, Ayokunle Ayobami Omotunde, Victor Oshoriamhe Enike, and Brian Oisenosume Ifidon. "Radio Frequency Identification Based Student Attendance System." Ingénierie des systèmes d information 27, no. 1 (2022): 111–17. http://dx.doi.org/10.18280/isi.270113.

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Attendance is a record tracking system used in organization. It is used in the educational sector to track students who attend classes as well as staffs attendance. This system is a form of inventory keeping system in school but instead of tracking goods, people are tracked. In Babcock the attendance system being used presently is conventional and very susceptible to attacks. Due to these, a system is created to curb these challenges. In this work an attendance system was created which receives data input from student and staff at any given instance through the help of the RFID tag embedded in

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Nurul Afiqah Azri Mazlan and Ruzita Ahmad. "I-Attend: A Smart Attendance System for Secondary Schools Using RFID." Journal of Computing Research and Innovation 10, no. 1 (2025): 179–93. https://doi.org/10.24191/jcrinn.v10i1.507.

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I-Attend is a smart attendance system targeted at secondary school administrators and teachers. The purpose of this project is to develop a smart attendance system integrated with RFID technology to improve the efficiency and accuracy of attendance tracking. The research problems investigated include the challenges associated with the traditional method of attendance systems, such as time consumption, proneness to error, and difficulties in data retrieval due to the size of the student population. The study seeks to address these issues by proposing a technological solution that enhances the a

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Mane, Prof Seema. "Exploring Advances in Meeting Minutes Generation and Face Attendance Systems: A Comprehensive Literature Survey." INTERANTIONAL JOURNAL OF SCIENTIFIC RESEARCH IN ENGINEERING AND MANAGEMENT 08, no. 03 (2024): 1–11. http://dx.doi.org/10.55041/ijsrem28939.

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The existing literature survey offers a thorough exploration of automatic text summarization, speech-to-text conversion, and face recognition technologies, all of which are integral to the proposed model named as ConvoLogix. Historically, traditional methods for managing meetings and collaboration involved manual note-taking and attendance tracking. These processes were time-consuming, error-prone, and not conducive to optimization. In today’s fast-paced business environment, the absence of automated solutions hinders efficiency and collaboration. The survey underscores the significance of emb

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Owolabi, Bukola Meka, Waheed Azeez, and Mariam Gbadegesin. "Employee Attendance Tracking Using Facial Recognition System." European Journal of Computer Science and Information Technology 12, no. 5 (2024): 43–63. http://dx.doi.org/10.37745/ejcsit.2013/vol12n54363.

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Traditional pen-and-notebook methods for employee attendance are often susceptible to inaccuracies and falsifications. Biometric systems, despite being more secure, confront issues such as high acquisition costs and inefficiencies in capturing fingerprints, especially when hands are unclean or injured. In this study, a cutting-edge Employee Attendance Tracking System using Facial Recognition is developed, addressing the shortcomings of conventional attendance methods and biometric systems. The proposed system employs an array of Python libraries including Django, face_recognition, OpenCV (cv2)

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Varute, Mr Tejas, Mr Shripad Rajput, Mr Swapnil Shinde, and Mr Parth Shinde. "BEYOND THE ROLLCALL: SMART STRATEGY FOR ATTENDANCE." International Journal of Engineering Applied Sciences and Technology 09, no. 04 (2024): 87–94. http://dx.doi.org/10.33564/ijeast.2024.v09i04.011.

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Attendance tracking is a crucial aspect of educational institutions, yet the traditional manual methods are time-consuming and error-prone. This project presents an innovative solution to this problem through the development of an automated attendance system. Utilizing advanced technologies such as face detection and optical character recognition (OCR), this system aims to streamline the attendance tracking process in schools and colleges. By automatically detecting student faces and extracting roll numbers from stickers affixed to the left side of their faces, the system eliminates the need f

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Pisal, Pranav. "An Automated Students Attendance System with SMS Notification." INTERNATIONAL JOURNAL OF SCIENTIFIC RESEARCH IN ENGINEERING AND MANAGEMENT 09, no. 04 (2025): 1–9. https://doi.org/10.55041/ijsrem44986.

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This study aims to develop an automated student attendance system that integrates RFID authentication with SMS notifications sent to respective parents or guardians, ensuring improved monitoring of student attendance. The system employs an Arduino Uno, RC522 RFID scanner, and SIM800L GSM module to capture attendance, store data, and send notifications. The RFID scanner records attendance, and the GSM module sends real-time SMS alerts. The system demonstrates high accuracy in attendance logging, quick SMS delivery, and ease of access control. It improves parental awareness regarding student att

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Ronald, B. Rivera. "Enhanced Attendance Monitoring System using Biometric Fingerprint Recognition." International Journal of Recent Technology and Engineering (IJRTE) 9, no. 5 (2021): 1–4. https://doi.org/10.35940/ijrte.E5070.019521.

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<strong>Abstract:</strong> In this study, an enhanced attendance monitoring system using biometric fingerprint recognition in tracking and monitoring employees’ attendances for Callang National High School, District 04, San Manuel, Isabela was introduced. For most organizations, handling people is a daunting job in which it is very important to maintain an accurate record of attendance. Taking and maintaining the attendance of employee manually on a regular basis is a big activity that requires time. For this reason an effective system was designed. The system was designed and developed

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Mohammed, Mustafa Saad, and Khamis A. Zidan. "Enhancing attendance tracking using animated QR codes: a case study." Indonesian Journal of Electrical Engineering and Computer Science 31, no. 3 (2023): 1716. http://dx.doi.org/10.11591/ijeecs.v31.i3.pp1716-1723.

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This research paper explores the effectiveness of quick response (QR) code-based attendance systems with the added security measure of generating two QR codes per second. With traditional attendance tracking methods being time-consuming and inefficient, QR codes have become increasingly popular as a quick and efficient alternative. However, one concern with QR code-based attendance systems is the potential for fraud and misuse. To address this issue, this study proposes generating two QR codes per second to ensure that only the current and legitimate QR code is recognized. The purpose of this

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Mishra, Prof Deepa. "A Comparative Study of Face Recognition Models for Smart Attendance." International Journal for Research in Applied Science and Engineering Technology 11, no. 5 (2023): 6666–70. http://dx.doi.org/10.22214/ijraset.2023.53128.

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Abstract: The Smart Attendance Monitoring System using Face Recognition is a project that aims to automate the process of tracking attendance in an organization using facial recognition technology. The system uses a camera to capture images of individuals, which are then compared to a database of pre-registered faces. The system recognizes the individuals and records their attendance automatically. The project involves several stages, including data collection, face detection etc. The system uses machine learning algorithms to analyze the images and identify the individuals accurately. The sys

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Jagtap, Samiksha, Amey Kadam, and Om Kadam. "Inventrove with Real-Time Face Recognition Using AI." INTERANTIONAL JOURNAL OF SCIENTIFIC RESEARCH IN ENGINEERING AND MANAGEMENT 09, no. 04 (2025): 1–9. https://doi.org/10.55041/ijsrem43628.

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Efficient workforce management is crucial in in- dustrial environments where precise monitoring of employee attendance directly impacts productivity and operational ef- ficiency. This paper presents the design and implementation of an advanced attendance management system tailored for industrial applications, which integrates biometric authentication and facial recognition technologies. The system leverages real- time data processing capabilities to ensure accurate and auto- mated tracking of employee attendance, eliminating traditional manual errors and enhancing security. The proposed soluti

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K, Ramya. "DRONE POWERED CLASSROOM PRESENCE TRACKER." INTERANTIONAL JOURNAL OF SCIENTIFIC RESEARCH IN ENGINEERING AND MANAGEMENT 08, no. 05 (2024): 1–5. http://dx.doi.org/10.55041/ijsrem32683.

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In today's rapidly evolving educational landscape, the traditional methods of manual attendance tracking in classrooms are proving to be increasingly inefficient and prone to inaccuracies. This project introduces an innovative solution to modernize classroom attendance tracking through the integration of drone technology and advanced computer vision algorithms. By combining autonomous navigation, object detection, data processing, real-time reporting, and user interface functionalities, the system streamlines attendance management processes in educational environments. Utilizing drones equippe

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Amith, D. V., V. Chandana, D. Krupesha, B. Keshava, and Gowda S. Abhishek. "Attendance Management and Student Tracking System Using Face Recognition." International Journal of Innovative Science and Research Technology 8, no. 5 (2023): 1024–28. https://doi.org/10.5281/zenodo.7968809.

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A project employing machine learning to track student attendance in schools is the attendance management and student tracking system using facial recognition. Each student's face is captured by a camera as they enter the classroom, and the system compares that image to the student's previously saved information to record their attendance. To develop a distinctive template for each student that is utilised for recognition, the system uses deep learning algorithms to extract information from the faces. Additionally, the system has the ability to recognise many faces at once and may recor

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B, Smitha Shekar, Harish G, Aaditya Pandit, Abdul Rayan, Abhishek Singha, and Binyul Shrestha. "IoT based Biometric Student Access Control and Attendance Management." International Journal for Research in Applied Science and Engineering Technology 12, no. 4 (2024): 5730–35. http://dx.doi.org/10.22214/ijraset.2024.61370.

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Abstract: The Fingerprint-Based Attendance Management System offers an innovative solution for automating attendance tracking in educational institutions. Utilizing an ATmega328 microcontroller and fingerprint sensor, the system enables efficient capture of student attendance data. Real-time feedback is provided through an LCD display, ensuring users are promptly informed of authentication status. Captured fingerprint IDs are transmitted to a cloud-based server for comparison with stored student records. Upon successful matching, attendance is marked, and SMS notifications are sent to parents,

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Bhatia, Vedant. "Automated Attendance System with GPS-Integrated with Enhanced Navigation Tracking." International Journal for Research in Applied Science and Engineering Technology 12, no. 10 (2024): 1228–40. http://dx.doi.org/10.22214/ijraset.2024.64849.

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With the rise of automation and smart technologies in educational institutions, efficient and reliable attendancetracking methods have become increasingly essential. Traditional attendance systems, which often involve manual or barcode scanning methods, are time-consuming and prone to inaccuracies. This research paper presents an innovative approach to student attendance tracking, utilising GPS-integrated barcode identification with wireless data transmission. The proposed system is designed to improve attendance accuracy and streamline student identification without the need for students to p

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Pakpahan, Andrew Fernando. "Rapid Application Development of Group Attendance System for Higher Education Using Laravel and VueJS." TeIKa 14, no. 1 (2024): 39–51. http://dx.doi.org/10.36342/teika.v14i1.3388.

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This research presents the development of a Group Attendance System for higher education institutions using Laravel and VueJS frameworks. The system addresses the limitations of traditional attendance tracking methods by offering a web-based, mobile-optimized solution. Employing the Rapid Application Development (RAD) methodology, the study outlines the design and implementation process, including the creation of a user-friendly interface for both administrators and student coordinators. The application facilitates efficient management of student groups, scheduling of meetings, and real-time a

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Shanker, B. Purna. "Automated Attendance and Analytics System." International Journal for Research in Applied Science and Engineering Technology 13, no. 5 (2025): 6104–10. https://doi.org/10.22214/ijraset.2025.71563.

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Abstract: The Automated School Attendance and Analytics System is a web-based solution designed to streamline and automate the process of student attendance tracking and data analysis. This system aims to eliminate the inefficiencies and errors associated with traditional manual attendance methods, providing a more accurate, time-saving, and user-friendly approach for educational institutions. The system automatically records student attendance using advanced methods, allowing teachers and administrators to quickly and accurately track attendance in real-time.In addition to attendance tracking

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Et al., Julaily Aida Jusoh. "Tracing Students Attendance During Covid-19 Pandemic by Applying Location Detection Technology." Psychology and Education Journal 58, no. 1 (2021): 5441–46. http://dx.doi.org/10.17762/pae.v58i1.2159.

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The Covid-19 pandemic outbreak has initiated the learning process to switch from face-to-face learning methods to open distance learning. The open distance learning is a concept of students assessing the lectures from different venues. Among the activities that are affected by that change, are the process of recording student’s attendance and engagement during the online lectures, as opposed to the normal method of being in the same classroom during the lecture. The Global Positioning System (GPS) is a global navigation satellite system that provides location and time synchronization. This app

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Lavanya, R., M. MEENATCHI, and R. SARANYA. "Monitoring of Participation Monitoring, Optical Somnolence Recognition and Proctorial Supervision." INTERANTIONAL JOURNAL OF SCIENTIFIC RESEARCH IN ENGINEERING AND MANAGEMENT 08, no. 008 (2024): 1–15. http://dx.doi.org/10.55041/ijsrem37014.

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The Comprehensive Student Monitoring Solution is a state-of-the-art integrated system designed to streamline attendance tracking, drowsiness detection, and advanced proctoring functionalities within educational settings. This innovative solution combines cutting-edge technologies to provide real-time monitoring and analysis of student activities, ensuring a secure and engaging learning environment. The system offers seamless attendance tracking capabilities, allowing educators to easily monitor and manage student attendance records. Furthermore, the inclusion of drowsiness detection technology

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Sowmya, Sundari L. K., K. Anitha, Tejeswara Reddy D., .Pavan A, D.Nitish, and Rohith N.P.Sai. "Innovative Approach to Attendance Tracking: Face Recognition System." Recent Innovations in Wireless Network Security 5, no. 3 (2023): 1–7. https://doi.org/10.5281/zenodo.8162265.

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<em>This paper discusses managing biometric attendance. The manual technique of managing attendance, which requires a lot of time and is challenging to maintain, will be replaced by automatic attendance management. Although there are several biometric procedures, face recognition is the most effective one. We are employing the Convolutional Neural Networks (CNN) technique, which is based on Deep Learning (DL). We are taking into account the data set of human faces that were trained using CNN. For the user interface webpage, the Flask framework was used, and the entire procedure was carried out

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Kaur, Jasbani, Harsh Saxena, and Er Sarika Singh. "A Real Time Facial Recognition and Tracking System for Personnel Presence." International Journal for Research in Applied Science and Engineering Technology 12, no. 5 (2024): 3908–10. http://dx.doi.org/10.22214/ijraset.2024.62472.

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Abstract: Our project aims to revolutionize the conventional attendance system by implementing a facial recognition-based solution. The existing manual methods are prone to human error and require significant maintenance. By leveraging facial recognition technology, our system will offer improved precision and efficiency, reducing the need for manual work. The system will maintain a database of students' images, matching them during class to mark attendance accurately. Utilizing machine learning techniques, specially the Haar-Cascade classifier and local binary pattern histogram method for fac

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E, Subash, Hariprasath M, Aathithya S, et al. "Attendance Management System Using Face Detection." INTERANTIONAL JOURNAL OF SCIENTIFIC RESEARCH IN ENGINEERING AND MANAGEMENT 09, no. 03 (2025): 1–9. https://doi.org/10.55041/ijsrem43195.

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This paper presents a Hybrid Multi-Stage Face Detection Algorithm that integrates traditional and deep learning methods for improved accuracy and efficiency. The process begins with Preprocessing and Enhancement to refine image quality. Fast Face Candidate Selection (Haar + HOG + SVM) quickly detects potential faces, followed by Precise Localization using MTCNN to refine detections and extract facial landmarks. Deep Learning Verification (RetinaFace/YOLO) eliminates false positives, ensuring reliability. Finally, Face Tracking (Kalman Filter + SORT) maintains consistency in video streams. This

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