Relevant bibliographies by topics / Fingerprint biometric-based attendance system

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Academic literature on the topic 'Fingerprint biometric-based attendance system'

Author: Grafiati
Published: 3 June 2025
Last updated: 20 July 2025

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Journal articles on the topic "Fingerprint biometric-based attendance system"

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Savitha, A. C., Kumar KM Madhu, DH Jnanaraj, Bedre Kamal, and DS Manoj. "Biometric Attendance System Based on Fingerprints." Journal of Scholastic Engineering Science and Management (JSESM), A Peer Reviewed Universities Refereed Multidisciplinary Research Journal 4, no. 5 (2025): 69–73. https://doi.org/10.5281/zenodo.15401054.

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In this paper biometric attendance system based fingerprints is implemented. For the implementation of our work we have interfaced the fingerprint sensor with an Arduino Uno, LCD display, and RTC module. Arduino is used to collect and store attendance records and statistics. Commonly used technologies for recording attendance in workplaces and educational institutions are biometric attendance systems. This work can be used in a variety of settings, including offices, businesses, colleges, and schools where timely and accurate attendance recording is necessary. The system will be safer for users if the fingerprint sensor is used.
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Prince Ana, Ukoette Jeremiah Ekah, and Emmanuel Oyo-Ita. "IOT-based biometric attendance system for CRUTECH." International Journal of Science and Research Archive 5, no. 1 (2022): 039–50. http://dx.doi.org/10.30574/ijsra.2022.5.1.0035.

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Identification of students in higher institutions in Nigeria, coupled with the recent insecurity and impersonation in the country has exposed the need to find a way to identify each and every person in the institution and Cross River University of Technology (CRUTECH), Calabar, Nigeria, is not an exception. The current method of identifying students with an identification card is vulnerable to abuse. To curtail this menace, this research proposes an IOT-based attendance system using ESP32 microcontroller, 0.96” OLED display and R305 fingerprint module. During operation, the system collects the fingerprint data from multiple users through the microcontroller based on ESP32 Wi-Fi enabled module and sends it over the internet to a website. Enrollment of fingerprints is done on the server using the interfaced fingerprint sensor module. Verification of user’s fingerprint is done on the webserver while fingerprint templates are transmitted over Wi-Fi. The website user interface (UI) used in this project is developed using PHP, CSS and JavaScript. It has a database and records of attendance. By logging into the website, attendance records of each user, including personal details as well as incoming and outgoing time can be collected. This data can be downloaded and exported to an excel sheet for evaluation.
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A S, Nithya. "IoT Based Smart Attendance Management System." INTERANTIONAL JOURNAL OF SCIENTIFIC RESEARCH IN ENGINEERING AND MANAGEMENT 08, no. 03 (2024): 1–11. http://dx.doi.org/10.55041/ijsrem29283.

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Abstract: This research work has application for attendance system of employer's and students in general. The system will facilitate institutions! organization to make attendance individual in time along with data information thumb impression will be taken as a signature for the system entry. Main design and challenge in this system is the design of database architecture and its business logic. I. AIMS AND OBJECTIVE The aim of this system is to implement in C#.net set of reliable techniques for fingerprint image enhancement and minutiae extraction. The performance of these techniques will be evaluated on a fingerprint data set. In combination with these development techniques, statistical experiments can then be performed on the fingerprint data set. The results from these experiments can be used to help us better understand what is involved in determining the statistical uniqueness of fingerprint minutiae. The main aim that this system would test whether attendance by fingerprint is enough for identification. It is expected that the work in this system will reach the stage of being able to fully test hypothesis. II. BACKGROUND/CONTEXT Fingerprints are the oldest form of biometric identification. Modem fingerprint-based identification is used in forensic science, and in biometric systems such as civilian identification devices. Keywords: the fingerprint data, statistical uniqueness of fingerprint minutiae.
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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 for future technological advancements. biometric fingerprint attendance system aimed at improving accuracy and security in attendance tracking. Utilizing fingerprint recognition technology, the system effectively handles data acquisition, processing, and matching. Key issues such as data privacy and security are addressed with robust solutions. Testing shows significant improvements in reducing time theft and enhancing employee accountability, highlighting the system's potential to revolutionize attendance management.
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Fatema, A. Shaikh*, and Prof.S.O.Rajankar. "BIOMETRIC AUTHENTICATION SYSTEM USING RPI." INTERNATIONAL JOURNAL OF ENGINEERING SCIENCES & RESEARCH TECHNOLOGY 5, no. 4 (2016): 839–44. https://doi.org/10.5281/zenodo.50420.

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A biometric authentication system acquires biometric sample such as fingerprint. The fingerprint signifies physiological features of an individual.This is a system which maintains the attendance records of students automatically. In this  designing of an efficient module that comprises of a fingerprint sensor to manage the attendance records of students. This module enrolls the student’s as well as staff’s fingerprints. This enrolling is a onetime process and their fingerprints will be stored in the fingerprint sensor. During enrolling of fingerprints alone requires a system since it is a onetime process. After enrolling process gets completed disconnect the module from the system and insert a battery into the module. This will provide power when the module is not connected with the system. The presence of each students will be updated in a database.
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Waghmode,, Mahesh N. "Raspberry Pi Enabled Biometric Attendance System." INTERANTIONAL JOURNAL OF SCIENTIFIC RESEARCH IN ENGINEERING AND MANAGEMENT 08, no. 05 (2024): 1–5. http://dx.doi.org/10.55041/ijsrem34994.

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The precision and ease of use of the BIOMETRIC Attendance System draw many users to it among the many real-time apps available today. The development of an attendance system based on fingerprints was a significant difficulty. This method proposes to use a Raspberry Pi running Linux as the attendance system. The procedure starts with the generation of the database using a fingerprint reader and continues with the system-provided recognition and authentication. The Raspberry Pi platform is used for the entire procedure. The standardized fingerprint authentication approach, which can extract an individual's finger print and compare it to a database, is presented in this study. Additionally, it can give parents and teachers a summary of attendance on a daily and monthly basis. The main goal of the study that follows is to use biometric systems for verifying and authenticating the physical attendance of inmates in any kind of organization. This is made possible by the working principle of biometrics, which is based on control of prominent scalability, flexible properties, and cost reduction for reducing the requirements of biometric systems for numerous computational resources. Key Words: Fingerprint Sensor, Interfacing, Raspberry Pi.
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Obiora, Gerard Nonso, Isreal Oluwaseun Aladejare, Godwin Osariemen Igbinosa, Collins Belouebi Fiemobebefa, and Oluwaseun Amos Bamido. "Development of a Fingerprint-Based Attendance Monitoring System." ABUAD Journal of Engineering Research and Development (AJERD) 8, no. 1 (2025): 263–70. https://doi.org/10.53982/ajerd.2025.0801.27-j.

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This paper presents the design and execution process of a fingerprint-based attendance system at Bells University of Technology for Electrical/Electronics Engineering Department, to enhance the accuracy and efficiency of student attendance monitoring. Traditional methods often suffer from errors, are tedious, and capable of being manipulated. The developed system employs fingerprint (biometric) technology, offering a secure, dependable, and tamper-proof solution to these issues. By capturing and verifying students' fingerprints, the system makes sure that only the appropriate individual marks the attendance, effectively eliminating problems like impersonation. The system consists of two modes namely: register and record modes respectively. Firstly, fingerprint data was extracted and stored in a database. For attendance taking, after a user’s fingerprint is placed on the device, checks for similarity is done in connection with the database and the user is marked as present if a match is found. Thereafter, the information is uploaded. With the proposed system, the time taken per student to mark attendance was 6.16 seconds while for the manual method, it was 22.25 seconds per person. The fingerprint-based system streamlines attendance management by automating the recording process, thus saving time for both students and lecturers. It enhances data accuracy by removing the potential for human error and provides a reliable method for maintaining and retrieving attendance records. Additionally, the system offers improved data security, as biometric data is less likely to be compromised compared to the manual method.
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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, enhancing communication and transparency. Additionally, a teacher management interface within the cloud system allows for recording student internal marks and managing attendance records. The system prioritizes security, reliability, and accuracy to maintain the integrity of attendance data. By streamlining attendance tracking processes and improving communication between schools and parents, the system contributes to enhanced efficiency and accountability in educational institutions.
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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 monitoring of employees attendances and leave management through the use of biometric technology. It records the data of the employees, handles leave management, tracks employee attendance and encourages participation through fingerprint recognition. The system is equipped with a dashboard monitoring system that can be viewed by school heads to track the list of employees, early birds (employees who arrived early), on-leave staff, on-official business and a statistical graph of the monthly attendance rate of employees. Moreover, the system provides an auto-generated DTR for employees which saved time compared to the manual process. The innovation greatly affects the improvement of employees’ attendance through its automated attendance monitoring, leave management and report generated by the system. The impact of EAMS to the employees was identified through first quarter attendance report of SY 2028-2019 which served as a bases of comparison with the attendance rate of SY 2019-2020 when the system was implemented. The outcome shows that through the usage of the system, employees’ attendance has improved.
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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&rsquo; 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 monitoring of employees attendances and leave management through the use of biometric technology. It records the data of the employees, handles leave management, tracks employee attendance and encourages participation through fingerprint recognition. The system is equipped with a dashboard monitoring system that can be viewed by school heads to track the list of employees, early birds (employees who arrived early), on-leave staff, on-official business and a statistical graph of the monthly attendance rate of employees. Moreover, the system provides an auto-generated DTR for employees which saved time compared to the manual process. The innovation greatly affects the improvement of employees&rsquo; attendance through its automated attendance monitoring, leave management and report generated by the system. The impact of EAMS to the employees was identified through first quarter attendance report of SY 2028-2019 which served as a bases of comparison with the attendance rate of SY 2019-2020 when the system was implemented. The outcome shows that through the usage of the system, employees&rsquo; attendance has improved.
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Dissertations / Theses on the topic "Fingerprint biometric-based attendance system"

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Acharya, D., and A. K. Mishra. "Wireless Fingerprint based Student Attendance System." Thesis, 2010. http://ethesis.nitrkl.ac.in/1765/1/Thesis.pdf.

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Our B. Tech. Project aims at introducing biometric capable technology for use in automating the entire attendance system for the students pursuing courses at an educational institute. The goal can be disintegrated into finer sub-targets; fingerprint capture & transfer, fingerprint image processing and wireless transfer of data in a server-client system. For each sub-task, various methods from literature are analyzed. From the study of the entire process, an integrated approach is proposed. Biometrics based technologies are supposed to be very efficient personal identifiers as they can keep track of characteristics believed to be unique to each person. Among these technologies, Fingerprint recognition is universally applied. It extracts minutia- based features from scanned images of fingerprints made by the different ridges on the fingertips. The student attendance system is very relevant in an institute like ours since it aims at eliminating all the hassles of roll calling and malpractice and promises a full-proof as well as reliable technique of keeping records of student’s attendance.
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Mishra, Rishabh, and Prashant Trivedi. "Student Attendance System Based on Fingerprint Recognition and One to Many Matching." Thesis, 2011. http://ethesis.nitrkl.ac.in/2214/1/thesis.pdf.

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Our project aims at designing an student attendance system which could effectively manage attendance of students at institutes like NIT Rourkela. Attendance is marked after student identification. For student identification, a fingerprint recognition based identification system is used. Fingerprints are considered to be the best and fastest method for biometric identification. They are secure to use, unique for every person and does not change in one's lifetime. Fingerprint recognition is a mature field today, but still identifying individual from a set of enrolled fingerprints is a time taking process. It was our responsibility to improve the fingerprint identification system for implementation on large databases e.g. of an institute or a country etc. In this project, many new algorithms have been used e.g. gender estimation, key based one to many matching, removing boundary minutiae. Using these new algorithms, we have developed an identification system which is faster in implementation than any other available today in the market. Although we are using this fingerprint identification system for student identification purpose in our project, the matching results are so good that it could perform very well on large databases like that of a country like India (MNIC Project). This system was implemented in Matlab10, Intel Core2Duo processor and comparison of our one to many identification was done with existing identification technique i.e. one to one identification on same platform. Our matching technique runs in O(n+N) time as compared to the existing O(Nn^2). The fingerprint identification system was tested on FVC2004 and Verifinger databases.
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Book chapters on the topic "Fingerprint biometric-based attendance system"

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Singh, Rajesh, Anita Gehlot, Bhupendra Singh, and Sushabhan Choudhury. "Fingerprint-Based Attendance System." In Arduino-Based Embedded Systems. CRC Press, 2017. http://dx.doi.org/10.1201/9781315162881-24.

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Chowdhury, Prasun, Debnandan Bhattacharyya, Ritaban Das, Sourav Kr Burnwal, and Asis Prasad. "Development of IoT-Based Biometric Attendance System Using Fingerprint Recognition." In Proceedings of International Conference on Network Security and Blockchain Technology. Springer Nature Singapore, 2023. http://dx.doi.org/10.1007/978-981-99-4433-0_32.

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Anushka Swarup, Kottapalli Dheeraj, and Adesh Kumar. "Fingerprint-Based Attendance System Using MATLAB." In Proceeding of International Conference on Intelligent Communication, Control and Devices. Springer Singapore, 2016. http://dx.doi.org/10.1007/978-981-10-1708-7_117.

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Gagandeep, Jatin Arora, and Ravinder Kumar. "Biometric Fingerprint Attendance System: An Internet of Things Application." In Innovations in Computer Science and Engineering. Springer Singapore, 2018. http://dx.doi.org/10.1007/978-981-10-8201-6_58.

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Wei, Xiufeng. "Design and Implementation of Campus Attendance Fingerprint Recognition System Based on Artificial Intelligence." In Lecture Notes in Electrical Engineering. Springer Nature Singapore, 2025. https://doi.org/10.1007/978-981-96-2391-4_45.

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Xiang, Wei, Bhavin Desai, Paul Wen, Yafeng Wang, and Tianshu Peng. "A Prototype Biometric Security Authentication System Based upon Fingerprint Recognition." In Rough Sets and Knowledge Technology. Springer Berlin Heidelberg, 2009. http://dx.doi.org/10.1007/978-3-642-02962-2_33.

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Kathirvel, A., Debashreet Das, Stewart Kirubakaran, M. Subramaniam, and S. Naveneethan. "Artificial Intelligence–Based Mobile Bill Payment System Using Biometric Fingerprint." In Recurrent Neural Networks. CRC Press, 2022. http://dx.doi.org/10.1201/9781003307822-16.

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Mohammed, Inas Riyaz, J. Angel Arul Jothi, and K. Syama. "A Convolutional Neural Network Based Real Time Fingerprint Recognition for Attendance Monitoring." In Advances in Real-Time Intelligent Systems. Springer Nature Switzerland, 2024. http://dx.doi.org/10.1007/978-3-031-55848-1_28.

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Ritik, Sanidhya Gaur, Ashish Kumar, Rithik Nirwan, Chaitali Bhowmik, and Neha Jain. "Biometric Based Attendance System with Machine Learning Integrated Face Modelling and Recognition." In Advancement of Intelligent Computational Methods and Technologies. CRC Press, 2024. http://dx.doi.org/10.1201/9781003487906-23.

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Vandana and Navdeep Kaur. "Fingerprint and Face-Based Secure Biometric Authentication System Using Optimized Robust Features." In Lecture Notes in Electrical Engineering. Springer Singapore, 2020. http://dx.doi.org/10.1007/978-981-15-7804-5_15.

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Conference papers on the topic "Fingerprint biometric-based attendance system"

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bin Ismail Marzuki, Mohd Saiful Najib, Muhd Azri bin Abdul Razak, Ahmad Izzat bin Mod Arifin, Luqmanul Hakim bin Zulkornain, Abdul Hafiz bin Kassim, and Hasrul Hafiz bin Abu Bakar. "Arduino-based Fingerprint Scan for Attendance-taking System." In 2024 IEEE 6th Symposium on Computers & Informatics (ISCI). IEEE, 2024. http://dx.doi.org/10.1109/isci62787.2024.10668322.

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Mbengwa, Kaloso, Ravi Samikannu, R. Rohini, K. Maruliya Begam, G. Kanimozhi, and Abid Yahya. "Design and Development of a Microcontroller Based Fingerprint-Attendance System." In 2024 4th International Conference on Ubiquitous Computing and Intelligent Information Systems (ICUIS). IEEE, 2024. https://doi.org/10.1109/icuis64676.2024.10866429.

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Wasiat, Elebede Adedayo, Olusanya Olamide Omolara, Sodipo Queen Busayo, and Sam-Leeloo Tambari Ayotunde. "Design and Implementation of a Fingerprint-Based Student Attendance System." In 2024 IEEE 5th International Conference on Electro-Computing Technologies for Humanity (NIGERCON). IEEE, 2024. https://doi.org/10.1109/nigercon62786.2024.10927278.

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Gudur, Bheemesh K., Tejashwini Ivanagimath, and Tarunkumar Rathod. "Biometric Based Portable Student Attendance System." In 2024 International Conference on Innovation and Novelty in Engineering and Technology (INNOVA). IEEE, 2024. https://doi.org/10.1109/innova63080.2024.10846952.

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Swain, Biswaranjan, Jayshree Halder, Siddharth Sahany, Praveen Priyaranjan Nayak, and Satyanarayan Bhuyan. "Automated Wireless Biometric Fingerprint Based Student Attendance System." In 2021 1st Odisha International Conference on Electrical Power Engineering, Communication and Computing Technology(ODICON). IEEE, 2021. http://dx.doi.org/10.1109/odicon50556.2021.9428983.

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Dhanalakshmi, Narra, Saketi Goutham Kumar, and Y. Padma Sai. "Aadhaar Based Biometric Attendance System Using Wireless Fingerprint Terminals." In 2017 IEEE 7th International Advance Computing Conference (IACC). IEEE, 2017. http://dx.doi.org/10.1109/iacc.2017.0137.

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Mittal, Yash, Aishwary Varshney, Prachi Aggarwal, Kapil Matani, and V. K. Mittal. "Fingerprint biometric based Access Control and Classroom Attendance Management System." In 2015 Annual IEEE India Conference (INDICON). IEEE, 2015. http://dx.doi.org/10.1109/indicon.2015.7443699.

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Roy, Projapoti, Prottoy Saha, and Sharia Wasika Aditi. "An Automated and Scalable Tool for Fingerprint based Biometric Attendance Management System." In 2021 International Conference on Electronics, Communications and Information Technology (ICECIT). IEEE, 2021. http://dx.doi.org/10.1109/icecit54077.2021.9641418.

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Rakhra, Manik, Tiyas Sarkar, Dalwinder Singh, Ajay Kumar Singh, Vikas Verma, and Jay Kumar. "Implementing fingerprint biometric authentication to enrich the staff attendance system." In 4TH INTERNATIONAL CONFERENCE ON FUNCTIONAL MATERIALS, MANUFACTURING, AND PERFORMANCES: ICFMMP-2023. AIP Publishing, 2025. https://doi.org/10.1063/5.0240903.

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Zainal, Nur Izzati, Khairul Azami Sidek, Teddy Surya Gunawan, Hasmah Manser, and Mira Kartiwi. "Design and development of portable classroom attendance system based on Arduino and fingerprint biometric." In 2014 5th International Conference on Information and Communication Technology for The Muslim World (ICT4M). IEEE, 2014. http://dx.doi.org/10.1109/ict4m.2014.7020601.

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