Relevant bibliographies by topics / Attendance tracking

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  1. Journal articles
  2. Dissertations / Theses
  3. Books
  4. Book chapters
  5. Conference papers

Academic literature on the topic 'Attendance tracking'

Author: Grafiati
Published: 2 June 2025
Last updated: 31 July 2025

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Journal articles on the topic "Attendance tracking"

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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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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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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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Dissertations / Theses on the topic "Attendance tracking"

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Komínek, Petr. "Návrh a analýza systémů pokročilého zabezpečení a střežení objektů a prostor." Master's thesis, Vysoké učení technické v Brně. Fakulta informačních technologií, 2011. http://www.nusl.cz/ntk/nusl-236953.

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This diploma thesis deals with design, realization and analysis of security and surveillance systems for buildings and spaces containing advanced components. One of the main design's parts is dedicated to intruder alarm system, access system, attendance and CCTV systems with the possibility of automatic motion tracking. Controlling and monitoring of particular subsystems is possible both locally and remotely from a computer via a web interface or by means of a software. The access to camera system from a mobile phone is also possible. IAS/ACS systems also enable controlling and transferring in
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HSIEH, WEN-FU, and 謝文福. "Employee Attendance Tracking system by using RFID." Thesis, 2006. http://ndltd.ncl.edu.tw/handle/69976640273686311783.

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碩士<br>亞洲大學<br>資訊工程學系碩士班<br>95<br>Service industry was occupied in majority in the nowadays industry. Because the working hour in the service industry was commonly very long, therefore the work-shift system has been used. The chain-stores are the majority in the service industry; a company may have the branch stores all over the north, the central, and the south. Due to the lack of management in the store, the manager does not have the methods to know immediately the employee status such as absence from duty, in-duty situation, whether working-on and working-off on time, whether abiding by the
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Yu, Huei-Ting, and 游輝庭. "An Application of IEEE 802.15.4 to the Design and Implementation of Attendance Tracking and Request/Reply Systems." Thesis, 2006. http://ndltd.ncl.edu.tw/handle/52562756140631474547.

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碩士<br>國立臺灣海洋大學<br>電機工程學系<br>93<br>In this thesis we design a wireless system applied to attendance tracking and request/reply system – WAT&RRS over IEEE 802.15.4. The system includes a handheld transmitter, which is used to transmit messages, and a receiver which is used to receive messages and then send it to a centralized computer via a Serial-to-Ethernet module. Primary design objectives in our system are portability, re-programmability, reliability, low-power consumption and low-cost. In this thesis we propose two novel methodologies which are Dynamic Network Allocating Mechanism - DNAM an
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Books on the topic "Attendance tracking"

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Inc, Plunkett Communications. ROM visitor tracking study: Exit interviews. Plunkett Communications Inc., 1999.

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Inc, Plunkett Communications. ROM visitor tracking study: Exit interviews. Plunkett Communications Inc., 2000.

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Staff, Journals for All. Attendance Tracking System. Independently Published, 2017.

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Staff, Journals for All. Attendance Tracking Calendar. Independently Published, 2017.

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Staff, Journals for All. Attendance Tracking Sheet. Independently Published, 2017.

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Staff, Journals for All. Attendance Tracking Form. Independently Published, 2017.

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Dee, Loi. 2018 Attendance Tracking System: Attendance Log. Independently Published, 2018.

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Chhokro, Gothaano. Students Attendance Register - Student Attendance Book: Teachers Attendance Record Book - 30 Student Class Log Book for Tracking Attendance - Simple Attendance Tracker with Space for 30 Names. Independently Published, 2022.

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Press, Tenyoo. Attendance Book for Teachers: School Attendance Record Book for Teachers. 30 Student Class Log Book for Tracking Attendance. Class Attendance Book for Coaches and Teachers. Teacher Attendance Book. Independently Published, 2021.

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Press, Tenyoo. Attendance Book for Teachers: School Attendance Record Book for Teachers. 30 Student Class Log Book for Tracking Attendance. Class Attendance Book for Coaches and Teachers. Teacher Attendance Book. Independently Published, 2021.

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Book chapters on the topic "Attendance tracking"

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Nallusamy, C., R. S. Gowri, and S. Hari Priya. "GPS using attendance tracking system." In Challenges in Information, Communication and Computing Technology. CRC Press, 2024. http://dx.doi.org/10.1201/9781003559085-19.

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Mahajan, Rachit, Aryan Singhal, and Prashant Vats. "Enhancing Attendance Tracking Efficiency with RFID-Based Smart Attendance Management System (SAMS)." In Lecture Notes in Networks and Systems. Springer Nature Singapore, 2025. https://doi.org/10.1007/978-981-97-9526-0_23.

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Singh, Jyoti, Mayank Singh, and Deepika Koundal. "SATARS: Smart attendance tracking and activity recognition system." In Intelligent Computing and Communication Techniques. CRC Press, 2025. https://doi.org/10.1201/9781003635680-88.

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Sujatha, K., N. P. G. Bhavani, Prameeladevi Chillakuru, et al. "Wearable Technology with Location Tracking, Health Monitoring, and Attendance Tracking for Employees." In Lecture Notes in Networks and Systems. Springer Nature Singapore, 2023. http://dx.doi.org/10.1007/978-981-99-0769-4_15.

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Kiran, Ajmeera, Vikram Neerugatti, Rudrapati Mounika, Rajermani Thinakaran, J. Somasekar, and Navin Patidar. "Advance attendance monitoring using facial recognition technology for seamless tracking." In Challenges in Information, Communication and Computing Technology. CRC Press, 2024. http://dx.doi.org/10.1201/9781003559092-80.

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Dwivedi, Shashank, Amit Kumar Tiwari, Uddeshy Jaiswa, Shivangi Tripathi, Utkarsh Saxena, and Utkarsh Trivedi. "Revolutionizing Attendance Tracking: A Smart System Utilizing Face Recognition Technology." In Lecture Notes in Networks and Systems. Springer Nature Singapore, 2024. http://dx.doi.org/10.1007/978-981-97-4928-7_22.

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Pham, Trong-Nghia, Nam-Phong Nguyen, Nguyen-Minh-Quan Dinh, and Thanh Le. "Tracking Student Attendance in Virtual Classes Based on MTCNN and FaceNet." In Intelligent Information and Database Systems. Springer Nature Switzerland, 2022. http://dx.doi.org/10.1007/978-3-031-21967-2_31.

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Aggarwal, Manasvvi, Radhika Singh, Yuktika Duggal, et al. "Modernizing Attendance Tracking: An Automated Headcount System Integrated with Face Detection." In Lecture Notes in Networks and Systems. Springer Nature Singapore, 2024. http://dx.doi.org/10.1007/978-981-97-4149-6_34.

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Dedania, Yash, Vrushti Karia, Nirav Bhatt, and Purvi Prajapati. "Cloud-Powered Attendance Solutions: Streamlining Hourly Tracking with Facial Recognition on AWS." In Communications in Computer and Information Science. Springer Nature Switzerland, 2025. https://doi.org/10.1007/978-3-031-84059-3_18.

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Nguyen-Thi-Thanh, Thao, Xuan-Phuc Phan-Nguyen, and Nga Ly-Tu. "Machine Learning UHF-RFID to Support Video Tracking and Recommendation for Attendance System." In Communications in Computer and Information Science. Springer Nature Singapore, 2024. http://dx.doi.org/10.1007/978-981-96-0434-0_22.

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Conference papers on the topic "Attendance tracking"

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Kola, Sai Sindhu, Harsha Kenchi, P. Rama, V. Angayarkanni, J. Kalaivani, and S. Sivakumar. "Face Recognition CCTV for Automated Attendance Tracking." In 2025 IEEE International Students' Conference on Electrical, Electronics and Computer Science (SCEECS). IEEE, 2025. https://doi.org/10.1109/sceecs64059.2025.10940509.

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Kothari, Sahil, Tanisha Kumthekar, Mahek Mulla, Neeraj Bukane, and Tushar A. Rane. "Intelligent Video-Based Attendance Tracking With Machine Learning." In 2024 15th International Conference on Computing Communication and Networking Technologies (ICCCNT). IEEE, 2024. http://dx.doi.org/10.1109/icccnt61001.2024.10724841.

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Alex, Suja A., Angela Maria Alves, Gabriel Gomes de Oliveira, Gabriel Caumo Vaz, and Eric CK Cheng. "FaceAttendance: Leveraging Facial Features for Attendance Tracking System." In 2024 2nd International Conference on Information Network and Computer Communications (INCC). IEEE, 2024. https://doi.org/10.1109/incc64392.2024.00013.

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Gupta, Shrey Kumar, Nitin Yadav, Anant Pandey, Richa Sharma, and Atharva Chauhan. "Geolocation-Based Attendance Tracking System: A Comprehensive Review." In 2025 3rd International Conference on Communication, Security, and Artificial Intelligence (ICCSAI). IEEE, 2025. https://doi.org/10.1109/iccsai64074.2025.11064660.

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Balakrishnan, D., Umasree Mariappan, Satrasala Vinay Kumar, Murari Dinesh Kumar, Machupalli Ravi Sankar Reddy, and Enja Mokshith Kumar Reddy. "Student Attendance Tracking Management using Face Biometric Smart System." In 2024 4th International Conference on Intelligent Technologies (CONIT). IEEE, 2024. http://dx.doi.org/10.1109/conit61985.2024.10626516.

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M.S, Saravanan, Faiyaz Ahmad, and R. T. Thivya Lakshmi. "Smart Attendance Tracking System Using Various Machine Learning Algorithms." In 2024 Second International Conference on Intelligent Cyber Physical Systems and Internet of Things (ICoICI). IEEE, 2024. http://dx.doi.org/10.1109/icoici62503.2024.10696638.

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Rajpoot, Kuldeep Singh, Utkarsh Saxena, Nitin Arvind Shelke, and Rohit Agrawal. "Revolutionizing Attendance Tracking: A Holistic Automated Facial Recognition System." In 2025 International Conference on Ambient Intelligence in Health Care (ICAIHC). IEEE, 2025. https://doi.org/10.1109/icaihc64101.2025.10957105.

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Xian Ng, Melvin Wen, Siok Yee Tan, Mohammad Kamrul Hasan, and Angela Jia Hui Koh. "A Virtual Reality Face Recognition System for Revolutionizing Attendance Tracking." In 2024 International Conference on Decision Aid Sciences and Applications (DASA). IEEE, 2024. https://doi.org/10.1109/dasa63652.2024.10836438.

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Prakash, Lakshya Kamal, Zoya Ahmad, and Mohammed Wasid. "Secure Attendance Tracking with Facial Recognition and Anti-Spoofing Technique." In 2025 4th OPJU International Technology Conference (OTCON) on Smart Computing for Innovation and Advancement in Industry 5.0. IEEE, 2025. https://doi.org/10.1109/otcon65728.2025.11070977.

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Ram, S. Karthik, K. Somasundaram, Senthil Kumar Tangavel, M. G. Venkatesa, Selvanayaki Kolandapalayam, and N. Manjunadh Reddy. "An Enhanced Optical-Flow Based Attendance Tracking System for Campus Environment." In 2025 4th International Conference on Sentiment Analysis and Deep Learning (ICSADL). IEEE, 2025. https://doi.org/10.1109/icsadl65848.2025.10933371.

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