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Anna, Fay E. Naive, Joseph M. Estrera Paul, and O. Pachica Archie. "Design and implementation of faculty class attendance monitoring system using BLE beacons." Indian Journal of Science and Technology 13, no. 40 (2020): 4234–43. https://doi.org/10.17485/IJST/v13i40.1527.
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Abstract <strong>Objectives</strong>: To create a hardware and software tool that can be used for monitoring the faculty attendance and to generate customized reports. <strong>Methods/Statistical Analysis:</strong> The Bluetooth Low Level Energy (BLE) beacons would be set as stationary device that has proximity unique identifier. Once the smartphone of the faculty is within the range of the beacon, it can then record the faculty’s attendance. Calibrated beacon range makes the proposed design unique in terms of addressing common attendance tracking issues. Also, an automated attendance monitoring tailored based on the periodic report the Human Resource (HR) of the university. The researchers conducted a testing in the laboratory classrooms to check the functionality and reliability of the automated attendance monitoring. <strong>Findings</strong>: Based on the testing conducted, the system is capable to detect the faculty once he/she is inside the classroom, records his/her attendance and generates reports. The mean percentage error is 8.02% which means that the BLE beacon is acceptable in detecting the faculty’s smartphone prior entering to his/her class.<strong>Keywords</strong>: Faculty class attendance monitoring system; Bluetooth low level energy beacons
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Naive, Anna Fay E. "Design and implementation of faculty class attendance monitoring system using BLE beacons." Indian Journal of Science and Technology 13, no. 40 (2020): 4234–43. http://dx.doi.org/10.17485/ijst/v13i40.1527.
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Objectives: To create a hardware and software tool that can be used for monitoring the faculty attendance and to generate customized reports. Methods/Statistical Analysis: The Bluetooth Low Level Energy (BLE) beacons would be set as stationary device that has proximity unique identifier. Once the smartphone of the faculty is within the range of the beacon, it can then record the faculty’s attendance. Calibrated beacon range makes the proposed design unique in terms of addressing common attendance tracking issues. Also, an automated attendance monitoring tailored based on the periodic report the Human Resource (HR) of the university. The researchers conducted a testing in the laboratory classrooms to check the functionality and reliability of the automated attendance monitoring. Findings: Based on the testing conducted, the system is capable to detect the faculty once he/she is inside the classroom, records his/her attendance and generates reports. The mean percentage error is 8.02% which means that the BLE beacon is acceptable in detecting the faculty’s smartphone prior entering to his/her class.
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Al-Monte, Vince M. Calo, B. Barbosa Jocelyn, and C. Llevado Jomar. "In-Classroom Faculty Attendance Monitoring System based on Ultra High Frequency (UHF) Radio Frequency Identification (RFID) with Captured Image Cross-verification Mechanism." Indian Journal of Science and Technology 14, no. 45 (2021): 3335–43. https://doi.org/10.17485/IJST/v14i45.1782.
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<strong>Objectives:</strong> Faculty attendance in schools are monitored based on Daily Time Record (DTR) which captures a daily time-in and time-out of teachers in and out of the school campus using various technologies and methods, however there is a scarcity of studies in monitoring faculty attendance in the actual bounds of the classroom. Hence, this study aimed to develop an In-Classroom Faculty Attendance Monitoring System based on Ultra High Frequency (UHF) Radio Frequency Identification (RFID) with captured image cross-verification mechanism. <strong>Methods:</strong> The system comprises two modules, namely the Teacher Attendance Module and Attendance Monitoring Web Application module. The Teacher Attendance Module, it is composed of a UHF-RFID reader and a camera module that is interfaced to the Raspberry Pi board. Passive tags are embedded on the teachers’ ID cards for them to be uniquely identified by the UHF-RFID reader when they are within the 2- meter read distance. Meanwhile, the Attendance Monitoring Web Application module is developed using a PHP framework connected to a MySQL database. It aggregates the attendance data collected from the Teacher Attendance Module for monitoring purposes which is accessible to both the monitoring staff and teachers via a web browser. <strong>Findings:</strong> Based on the evaluation results, the proposed system received positive feedback from the end users in terms of its functionality and usability and was found to be more favorable over existing attendance monitoring systems.<strong> Novelty:</strong> The system provides a non-obtrusive way of checking teachers’ attendance by utilizing the UHF-RFID technology which has a longer read range than other RFID categories used in previous studies. Moreover, unlike existing solutions, the system checks for attendance multiple times, not only during entrance and exit which then calculates thetotal stay-in time of the teacher during a class session. Most importantly, the system can prevent fraudulent activities through a camera module. <strong>Keywords:</strong> UHFRFID; Attendance; Faculty; Raspberry Pi; Camera
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John Dominic Ani˜non, Kenneth Kent Flores, Cliff Sean Kyle Otadoy, et al. "Classroom Attendance Monitoring System Using Radio Frequency Identification with Web Application." Research Briefs on Information and Communication Technology Evolution 6 (December 15, 2020): 108–28. http://dx.doi.org/10.56801/rebicte.v6i.110.
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Throughout the years, attendance monitoring has widely evolved from manual methods to the integrationof technology. Manual attendance monitoring in an institution consumes time, hard tomaintain, prone to human error, and leads to misplaced or lost records. Individuals also tend to takeadvantage of the flaws of the manual method that leads them to commit hoax and forgery. Despitethe innovation of different automated systems, biometric recognition systems, RFID technology, andbarcodes also have disadvantages. To address the shortcomings of the existing methods and to minimizethe contingencies, this paper describes the use of a web application that utilizes an ultra-highfrequency (UHF) RFID with a motion sensor to monitor the attendance of students from the Universityof San Carlos. A Raspberry Pi 3 Model B is used in controlling the input and output, inwhich it is outputted on an LED. Wireless communication is used between the hardware system andthe web system to record and validate students’ attendance records. A web application is developedfor faculty, students, and chairperson to monitor class attendance and to minimize contingencies. Inaddition, the faculty can edit and generate a seating plan.
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Nithvika Reddy, N. S. Manogna, and Shaga Shivani. "Educational Resource Management System (ERMS)." International Journal of Science and Research Archive 8, no. 2 (2023): 026–29. http://dx.doi.org/10.30574/ijsra.2023.8.2.0336.
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The ERMS aims to curate a management system for universities that provides us with a web application that eases the academic activities for students and faculty. Learning is fun when accessing the resource is easy. A user-friendly UI. The project environment and usage are completely secure at both ends. This is a system for the collection, integration, processing, maintenance, and dissemination of data and information to support decision-making, policy analysis, and formulation, planning, monitoring, and management at all levels of an education system. There are 3 main Users namely · Faculty - Who upload class materials, update marks and attendance. · Students - Who use this for accessing study materials, checkmarks, attendance. Admin/Management - Who keeps up with the changes like marks and attendance.
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Shukla, DR Abhay Shukla. "Automatic Face Recognition Attendance System using Python and Open CV." INTERANTIONAL JOURNAL OF SCIENTIFIC RESEARCH IN ENGINEERING AND MANAGEMENT 08, no. 05 (2024): 1–5. http://dx.doi.org/10.55041/ijsrem35032.
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The primary goal of this project is to develop a face recognition-based attendance monitoring system for educational institutions, aiming to improve and modernize the current attendance procedures, making them more efficient and effective. The existing system suffers from ambiguities that lead to inaccuracies and inefficiencies in attendance recording. Numerous issues arise when authorities cannot enforce the regulations of the old system. This project leverages face recognition technology to address these problems. During attendance sessions, the system will compare faces against a database to verify identities. Once an individual is identified, their attendance will be automatically recorded, with the necessary information in an Excel sheet. This automated system aids faculty in taking attendance for the entire class without causing any disruption or wasting time. We propose and have implemented a smart attendance system with the potential to incorporate Quick Response (QR) codes as a future method for managing attendance. This system aims to streamline and document student attendance during lectures and other activities across all relevant courses. At the end of the day, the Excel sheet containing attendance details for all individuals will be emailed to the respective faculty members.
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Derman, Derman, and Harmini Harmini. "MODEL SISTEM INFORMASI MONITORING PERKULIAHAN FAKULTAS TEKNIK UNIVERSITAS SEMARANG BERBASIS WEB." Elektrika 10, no. 2 (2018): 41. http://dx.doi.org/10.26623/elektrika.v10i2.1260.
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<p>The development of Information Technology is increasingly demanding that Higher Education to provide information quickly to meet the needs of Information and Monitoring Course for Lecturers, Students and Admin staff. This study aims to design a Model Information System and Monitoring Course at the Faculty of Engineering, University of Semarang Web-based. Coverage includes lecture planning, lecturing, evaluation of lecturing, control of lecturing and improvement of lecture planning. This research produces an application of Information System and Monitoring model of lecturing which aims to facilitate and accelerate the preparation of time, room and course schedule and ease in monitoring the attendance status of lecturers in class either to students or other parties in real time without having to come to campus check board information . The contribution of this research results will greatly affect the application of science and technology for higher education institutions and to realize the development of Faculty of Engineering Semarang University as a leading Faculty in 2023. The method used is dynamic priorities method which prioritizes the process that has the highest <br />priority and is able to respond to changes in the system environment operate. Modeling the system using XAMPP package in which integrated MySQL module for database purposes, PHP for management of information systems, and Apache for simulation purposes. The results showed the implementation of the application of Information Systems Monitoring System Lectures Faculty of Engineering, University of Semarang goes well.</p>
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Nirale, Rupesh. "College Automation System Using Java Methodology (Academix Portal)." INTERANTIONAL JOURNAL OF SCIENTIFIC RESEARCH IN ENGINEERING AND MANAGEMENT 08, no. 04 (2024): 1–5. http://dx.doi.org/10.55041/ijsrem30879.
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The College Automation System Project is designed to operate within the college's local area network and cater to all four departments. Its features encompass an admission system, class attendance monitoring, online notes and notice boards, and a placement system, all accessible to students using their valid registration ID and password. The project aims to support college administrators by providing comprehensive information about faculty members' schedules and allowing them to manage user accounts through the admin panel. Administrators can add or delete users, grant special permissions, and schedule classes as needed. Teachers benefit from the system by gaining access to student data tailored to their preferences. They can query information based on grades and percentages, identify students with attendance issues, and utilize other features available within the system. For students, the system offers access to various resources, including teachers' notes, placement session details, upcoming company information, and a dedicated learning section for exam preparation. Overall, the College Automation System Project serves as a centralized platform for streamlining administrative and academic processes, enhancing communication, and facilitating access to essential information within the college community. Key Words: Training and placement, Similarity, Student Data, grade, percentage
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Banu J, Faritha, Balakrishnan M, Praveen Raju P, and Naveen kumar M. "IoT Based Cloud Integrated Smart and Sustainable Classroom." International Journal of Recent Technology and Engineering (IJRTE) 9, no. 1 (2020): 780–83. http://dx.doi.org/10.35940/ijrte.f1160.059120.
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Now a day, every educational environment requires an evolution of classrooms from traditional model to a more active model of classrooms. The main objective of a classroom model is to spend more time on teaching and learning and less on organizing and monitoring the workflow of the classroom. This project proposes “IoT based Cloud Integrated Smart and sustainable Classroom”. Smart classroom is developed to monitor and regularize the activities like assignments, projects, tutorial submission and attendance monitoring of the Students or scholar at ease in real time by the faculty, mentor or advisor. The proposed system monitors and reports whether the assignments, projects, tutorial is submitted on or before scheduled timeline, and sends the remainder notification to complete the assigned work in stipulated time. The proposed system utilizes Cloud Computing and Internet of Things, where sensors and processors are embedded in physical objects to form a network and communicate information with ease. RF identity card reader is fixed at each classroom to monitor the Students and give them alert, so that they meet the faculty or mentor for getting permission for attending the class if they failed to submit their work on time. Thus, by reducing the work of management, time for teaching and learning will be increased resulting in high performance of the classroom.
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Geeta, Ninawe, Joge Aishwarya, Katyarmal Chetan, Pandey Pratik, and Warambhe N. "Smart Class Attendance Monitoring System." Smart Class Attendance Monitoring System 2, no. 1 (2020): 1–4. https://doi.org/10.5281/zenodo.3760304.
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<em>In this paper, we present on idea of attendance monitoring system by using biometric sensor. In the concept of Smart Class every system should be managed smartly like by taking attendance electronically. For this stated reason, an efficient attendance management system using biometrics is designed. This framework gauges participation electronically with the assistance of a unique finger impression gadget and the records of the participation are put away in a database. Attendance only marked after student identification. For student identification, a biometric (fingerprint) based system is used. By using this concept, we can do prove paperless which also beneficial for our environment.</em>
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Sanika, Kulkarni1 Palak Shrivastava2 Pushpa Latha Bodineni Nandini Ambhore Deepti Choudhari Dipamala Chaudhari. "Attendance Monitoring system using face recognition." Scandinavian Journal of Information Systems 35, no. 1 (2023): 115–23. https://doi.org/10.5281/zenodo.7858055.
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The automatic face attendance monitoring system is a project that records the presence of the students in present in institute or a class. Within this system we can offer an automatic way to count attendance management project. Based on facial recognition and recognition algorithms, this system automatically recognizes a student via CCTV when they enter the institute or in class and signals their present by recognizing them, as well as the techniques to be used to deal with pitfalls such as spoofing. If we compare traditional attendance checks with this system, we save time and also monitor the students. Maintaining attendance is very essential part in all institutions to monitor student performance. Each institution has its own way of dealing with it. Some measure attendance manually using a register or paper method and some have implemented automated methods of attendance using biometrics. This system uses facial recognition to automatically detect the presence of students in the classroom without student involvement. Online Attendance Management System Benefits of Automated Student Attendance Management is software designed to manage a student's day-to-day attendance at the university. Here, the subject staff have one less task to mark student attendance and focus on teaching students until the end of class, as attendance is via CCTV by capturing photos of students and storing them in the database. Generated an automatic report with high fidelity. Our system also helps us to assess student attendance criteria. A detailed student attendance report is generated weekly and monthly.
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Naveen, D. Chandavarkar. "Technology Triggered Automated College Management System." RESEARCH REVIEW International Journal of Multidisciplinary 4, no. 3 (2019): 186–91. https://doi.org/10.5281/zenodo.2596466.
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In recent years, Radio Frequency Identification (RFID) based systems have seen large improvement and have been successfully applied to different areas including health care, security, and IT industry. RFID technology provides wireless identification using electronic tags (passive and active) with suitable scanners. This project is worked on an attempt to solve recurrent attendance monitoring problem and leave management system for the faculties in present global academic situation. The application of attendance monitoring system to RFID is developed and deployed in this work, i.e. capable of reducing the time wasted during manual roll calls for attendance and perform managerial decisions by the fact and proof that student or faculty was present or absent on the particular day. This study is also extended to faculty attendance system, library management system and student welfare module.
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Bhagat, Shrey. "Face Recognition Attendance System." International Journal for Research in Applied Science and Engineering Technology 10, no. 1 (2022): 280–83. http://dx.doi.org/10.22214/ijraset.2022.39702.
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Abstract: Face recognition systems are used in practically every industry in this digital age. One of the most widely utilized biometrics is face recognition. It can be used for security, authentication, and identity, among other things. Despite its low accuracy relative to iris and fingerprint identification, it is extensively utilized because it is a contactless and non-invasive technique. Face recognition systems can also be used to track attendance in schools, colleges, and companies. Because the existing manual attendance system is time consuming and difficult to maintain, this system intends to create a class attendance system that employs the concept of face recognition. There’s also the possibility of proxy attendance. As a result, the demand for this system grows. Database development, face detection, face recognition, and attendance updating are the four steps of this system. The photos of the kids in class are used to generate the database. Faces are discovered and recognized from the classroom's live streaming footage. At the end of the session, the attendance will be mailed to the appropriate faculty. Keywords: Smart Attendance System, NFC, RFID, OpenCV, NumPy
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I, Varsha. "Students Attendance Monitoring System Using RFID and GSM." INTERANTIONAL JOURNAL OF SCIENTIFIC RESEARCH IN ENGINEERING AND MANAGEMENT 08, no. 05 (2024): 1–5. http://dx.doi.org/10.55041/ijsrem34736.
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The Student Attendance Monitoring System (SAMS) utilizing Radio-Frequency Identification (RFID) and Global System for Mobile Communications (GSM) modules revolutionizes traditional attendance tracking methods. The system employs RFID cards assigned to both students and teachers, facilitating seamless attendance recording. When a teacher swipes their RFID card, indicating the start of the class, students are prompted to swipe their RFID cards, automatically marking their attendance. Upon successful attendance recording, the system triggers an SMS notification to parents, affirming their child's attendance. Additionally, the inclusion of a dedicated button allows for real-time reporting of attendance statistics to the principal. By pressing the button, the system transmits the number of classes attended by individual students directly to the principal's device, ensuring timely monitoring of student participation. This innovative system streamlines attendance management, enhances communication between school and parents, and provides administrators with valuable insights into student attendance patterns, fostering a conductive learning environment.
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Vadwala, Akshar. "Network Based Smart Attendance System for Students." International Research Journal of Innovations in Engineering and Technology 08, no. 08 (2024): 287–91. http://dx.doi.org/10.47001/irjiet/2024.808035.
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In the era of rapidly advancing technology, an effective and reliable attendance monitoring system is quite vital within the learning environment. The conventional attendance monitoring strategies are not only laborious and time-consuming; they also result in mistakes made by humans and proxy attendance. With the mobile phone, which is easily accessible, a better way for attendance management can be achieved. This paper proposes a Network-Based Smart Attendance System, wherein students' mobile devices and the institutional WiFi or local network can be used to facilitate the attendance process. In this digital solution, cases of attendance by proxy and errors in recording will fall drastically. More importantly, the record-keeping is burdensome to the faculty, which can be reduced, making the attendance system manageable and efficient to handle. Additionally, this solution could be integrated with machine learning, IoT devices, and NFC technology to further enhance its functionality and effectiveness. In this paper, a design of the system along with its implementation will be presented that details how it can improve the entire attendance management procedure in an educational institution.
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Jain, Arnav, Rahul Gupta, Mohd Shariq Ansari, and Tanveer Ikram. "Attendance Monitoring System Using Face Recognition." International Journal for Research in Applied Science and Engineering Technology 10, no. 5 (2022): 3024–29. http://dx.doi.org/10.22214/ijraset.2022.42389.
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Abstract: The primitive method of taking attendance through pen-paper or registers by the organizations and institutions are not much efficient these days. The proxies of the absentees by their groups or friends are much common due to which this important factor of monitoring the class becomes ineffective. The pen-paper attendance system non-essentially consumes much time in class while smart techniques gives more time to lecturer. It can be simply be manipulated. So, for that many organizations and institutions have replaced it through biometric sensors which mark attendance through fingerprints of students or staff. But due to covid-19, where touching anything is risky. As we know in the current situation during covid-19 pandemic, Government of different nations have a strict guidelines for social distancing required to be followed everywhere keeping the aspect of safety measures in mind. For that, an attendance monitoring system has been devised through face recognition. This face recognition system works in the following stages - face detection, face pre-processing, database creation, face training, face recognition, attendance maintenance. This project spotlight on the significance of the face alignment, hence how precise image is and False Acceptance Rate that can be noticed. The system processes on Face Recognition Grand Challenge (FRGC) with up-to 95% precision. Few students do mark the fake attendance of their classmates by using their digital devices specially phone through which they try to show the picture of their friend to the system but in that case it will display warning message with a beep sound. The motive behind producing face-recognition system is to save the time and make system smart and efficient. Keywords: Face Recognition, Open CV, Machine Learning, Real and fake face detection, Graphical User Interface
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Kumar, Dr R. G. Suresh. "Smart Attendance Verification System: Smart Attendance, Smarter Learning." International Journal for Research in Applied Science and Engineering Technology 13, no. 5 (2025): 2738–45. https://doi.org/10.22214/ijraset.2025.70709.
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Artificial Intelligence (AI) enhances attendance monitoring by using facial recognition to automatically identify student in online classes, ensuring accurate and real-time attendance tracking. AI also support continuous monitoring with periodic check and strengthens communication with parents by providing timely updates on student attendance and performance. Additionally, it ensures data privacy with encryption and adaptive algorithms to adjust to varying conditions. The existing attendance system uses facial recognition to capture student image at the start and end of a session to record attendance and identify student by comparing capture images with stored data, marking them present based on successful matched. It operates by utilizing the camera’s feed to automate the attendance process, ensuring that student participation is tracked without manual intervention. The existing attendance system primarily focuses on offline classes and lack adaptability for online environment, with limited scalability and issues with camera performance. We propose a web based application named as “Smart Attendance Verification System (SAVS) aimed at enhancing online class attendance monitoring. It includes cloud-based data management, periodic attendance check and the ability to operate in low light environment using standard cameras.
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Pooja, Nikam, Khond Vaishnavi, Patil Kanchan, Solanke Laxmi, and V. Patil G. "Attendance Monitoring System based on Android." Journal of Android and IOS Applications and Testing 5, no. 1 (2020): 17–24. https://doi.org/10.5281/zenodo.3756656.
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An education framework in India has gotten so progressed in a decade ago because of the improvement of the innovation. Brilliant class, video conferencing is a portion of the instances of present-day drifts in instructive framework. These applications help the organization to push ahead rapidly, satisfy their vision and achieve their objectives, E-way. The center thought of research venture is to execute Android based application for participation the board framework for progression of establishment and instructive framework. The proposed venture will be executed in applications, for example, online investigation material, sees, scholarly schedule and online tokens of assessment, online participation record, execution record, and parent implication framework utilizing Android applications. This framework causes educator to gauge participation through advanced cell and save record of understudies for their dynamic evaluation. This framework gives an earlier suggestion to understudy when their participation goes underneath the predefined participation limit as a SMS.
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A. Farag, Wael. "An RFID-based Smart School Attendance and Monitoring System." BOHR International Journal of Computational Intelligence and Communication Network 1, no. 1 (2022): 26–34. http://dx.doi.org/10.54646/bijcicn.005.
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In this paper, a smart attendance system for students attending school is proposed. The proposed attendance system is based on radio frequency identification (RFID) technology to facilitate automation and convenience. The proposed RFID attendance system (RFID-AS) should be used by school administration to ensure safety for students, as well as for grading and evaluation purposes. After careful study, passive RFID technology is selected to be used by the proposed system because of its reasonable cost. The main components of the system are an RFID tag, an RFID reader, Visual Studio [eXpressApp Framework (XAF) tool], and SQL Server to compare the data from the RFID tag with the students’ database to record attendance automatically. A graphical user interface (GUI) is developed using Visual Studio (XAF tool) to allow parents and school faculty to log in and browse the students’ records. Students will pass the classroom door, which will have an integrated RFID reader device to read their RFID. The paper discusses the design of the solution as well as the testing scenarios.
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Farag, Wael A. "An RFID-based smart school attendance and monitoring system." BOHR Journal of Computational Intelligence and Communication Network 1, no. 1 (2023): 26–34. http://dx.doi.org/10.54646/bjcicn.2023.05.
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In this paper, a smart attendance system for students attending school is proposed. The proposed attendance system is based on radio frequency identification (RFID) technology to facilitate automation and convenience. The proposed RFID attendance system (RFID-AS) should be used by school administration to ensure safety for students, as well as for grading and evaluation purposes. After careful study, passive RFID technology is selected to be used by the proposed system because of its reasonable cost. The main components of the system are an RFID tag, an RFID reader, Visual Studio [eXpressApp Framework (XAF) tool], and SQL Server to compare the data from the RFID tag with the students’ database to record attendance automatically. A graphical user interface (GUI) is developed using Visual Studio (XAF tool) to allow parents and school faculty to log in and browse the students’ records. Students will pass the classroom door, which will have an integrated RFID reader device to read their RFID. The paper discusses the design of the solution as well as the testing scenarios
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Arreglado, Marvin, Henry II Arreglado, Vienna Nerianne Magante, Kristine Joy Lagrosa, and Rhyan De Loyola. "Employee Attendance and Performance Monitoring System with Facial Recognition Technology and Data Analytics." Kabatiran 1, no. 1 (2023): 57–62. http://dx.doi.org/10.61864/kabatiran.v1i1.41.
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Paper-based attendance monitoring is being altered daily, whether in public or private, making it unreliable in evaluating the authenticity of attendance. In a career context, attendance plays a fundamental role, and traditional methods for monitoring it need to be updated. The emergence of biometric identification, particularly facial recognition, offers a promising solution. This study introduces FRaDA, an employee data Analytics with a Face Recognition System developed explicitly for Talisay Elementary School (TES) faculty and staff. The system aims to digitize attendance monitoring and employee evaluation processes by leveraging facial recognition technology. It captures and records attendance via live camera feed, generates efficient performance and attendance reports, minimizes recording errors and tampering, automates Daily Time Records (DTR) generation, and facilitates intensive attendance management. The methodological approach follows the Agile Scrum model and involves Initialization, Planning and Estimating, Implementation, Review, and Releasing phases, ensuring a systematic and efficient development process. Key highlights include the evaluation process with an overall score of 3.00, indicating the project's feasibility and excellence. In conclusion, Project FRaDA offers a practical and efficient solution for attendance management and employee evaluation, addressing the limitations of traditional methods and meeting the institution's needs.
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Vikram Bhattacharya, Aditya, Mrinalini Khanna, Akshay Tripathi, and S. Murugaveni. "Class Monitoring System Tools MTCNN and Haarcascade Classifier." International Journal of Engineering & Technology 7, no. 3.12 (2018): 951. http://dx.doi.org/10.14419/ijet.v7i3.12.17609.
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The project aims towards the assistance of teachers at the time of taking attendance. The system solely focuses on face detection and recognition. The tools used to device the system are API’s offered by Python 3.6, Open CV(for detection) and a few cognitive tools provided by Azure.The basic idea behind the project is face recognition linked to a database backend. The information of the student attending the class is stored here. The entire attendance is associated with two types of time stamps incorporated at the server end. The time stamp helps to keep a track of the hour conducted and the time for which number of people attended the class. Exceptions in the time stamp would be incorporated in order to cater for the students leaving the class or trying to bunk the class. In case of further exceptionsin the time stamp will be scope of further development of the system. All queries or conditions of the students will be answered by the system on communication with the admin. If the admin finds that the system was at fault then it can always be fixed by the admin for smooth functioning of the class monitoring system.
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Ashritha, Korukanti, Korukanti Ashritha, and Sridhar Bhukya. "Automated Attendance System Using Face Recognition." International Journal for Research in Applied Science and Engineering Technology 10, no. 6 (2022): 2096–99. http://dx.doi.org/10.22214/ijraset.2022.44212.
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Abstract: In the recent time automated face recognition has become a trend and has been developed very much , this is mainly due to two reasons; first it is due to availability of modern technologies and second is due to the ability to save time using face recognition in the process of taking attendance of students. Its usage will grow vast in the future as it saves a lot of time. It consumes a lot of time to take attendance manually and few might also fake the attendance, in order to prevent time consumption and avoid faking the attendance face recognition is used to identify the person present in the class and mark his attendance , this is done with the help of image or video frame. We proposed an automatic attendance management system using machine learning techniques such as CNN algorithm. The face detection and recognition will automatically detect the students in the classroom and mark the attendance by recognizing the person.. The faculty has access to add the student details such as name, USN, phone number, email-id. Then the image is captured through a high definition camera during the class hours. When the lecturing is going on faces of students are detected, segmented and stored for verification with database using the Convolutional Neural Networks (CNN) algorithm of machine learning technique
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Khadatkar, Vikrant, Shubhangi Bagadkar, and Prof Nutan Dhande. "Survey on Face Recognition Based Attendance Management System Using HOG Feature Extraction and SVM Classifier." International Journal for Research in Applied Science and Engineering Technology 10, no. 4 (2022): 64–65. http://dx.doi.org/10.22214/ijraset.2022.41100.
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Abstract: Face recognition system plays a vital role in almost every sector in this digital era. Face recognition is one of the popular biometrics’ techniques. It can used for security, authentication, identification and so on. It having low accuracy when compared to iris recognition and fingerprint recognition, but it is being widely used due to its contactless process. Face recognition technique can also be used for attendance marking field. This system targets to building a class attendance system which is used the technique of face recognition. We all know existing manual attendance system is taking more time and difficult to maintain. And having chances of proxy in attendance. That’s why, the need for this system occurs. This system consists of four phases- registration module, database creation, face detection, face recognition, attendance updating, attendance sending. Database consist of the image of the students in class. Face detection and recognition is performed using HOG feature extraction and SVM (Support Vector Machine) classifier. Faces will be detected and recognized from video streaming of the classroom. Attendance will be mailed to the respective faculty at the end of the lectures. Keywords: Face Recognition; Face Detection; SVM classifier; HOG feature extraction; attendance system;
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Uzair, Mr Tajmat, Mr Thakar Sairaj, Mr Patil Sahil, Mr Thakur Muchkund, and Mrs Saira Mujawar. "Smart Attendance System Using Face-Recognition." International Journal for Research in Applied Science and Engineering Technology 11, no. 4 (2023): 486–501. http://dx.doi.org/10.22214/ijraset.2023.50109.
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Abstract: Every Teacher know how tough it is to manage a class of 80 students. But the teacher’s manage the class also . But one thing that is even harder than managing the class of 80 students is to take attendance of that 80 students and maintain register . There are several ways to mark your attendance ,the most common way is to call out the name/Roll no. of the students. There are several drawbacks of this Manual System . One of them is It took longer and it is problematic. Hence people are thinking on switching on Automatic attendance System . From now on , a computer based student attendance checking system is required that supports faculty to keep records of students. Such system are already implemented in Country like China. In my face recognition project, a computer system will be able to find and recognize human faces fast and precisely in images or videos that are being captured through a surveillance camera. Numerous algorithms and techniques have been developed for improving the performance of face recognition but the concept to be implemented here is HOG(Histogram of Oriented Gradients). First we have to store a image and finds it encoding ,then after that once the video/image is send to script it will detect faces and reflect it into database
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Sachin, Anakha. "Academic & Attendance Monitoring System using RFID, Face Recognition & IoT." International Journal for Research in Applied Science and Engineering Technology 9, no. VI (2021): 2169–73. http://dx.doi.org/10.22214/ijraset.2021.35518.
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Attendance monitoring is an important task in the part of education. Attendance monitoring can be done using several methods. Among that, RFID proves to be an efficient and easiest method. Along with RFID, the use of face recognition also provides more accuracy and reliability by avoiding fake attendance. If a student bunks his/her class, then the use of GPS tracker attached to the tag enable the teachers to find the student. The purpose of IOT allows parents, teachers etc. to know the attendance and academic details of each and every student which gets stored in the database.
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Sajithabanu, S., A. Asrin Mahmootha, B. Aysha Banu, et al. "Intelligent College Management System with Real-Time Monitoring and Visual Analytics." Journal of Data Mining and Management 10, no. 2 (2025): 13–20. https://doi.org/10.46610/jodmm.2025.v10i02.002.
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Traditional college management systems are often hindered by outdated user interfaces, limited data accessibility, and inefficient communication among stakeholders. This project presents the development of an Intelligent College Management System (ICMS) that addresses these limitations through a modern, full-stack, analytics-driven approach. Utilizing Flask (Python) for backend services and React for the frontend, the system is designed to streamline administrative processes, academic monitoring, and stakeholder interaction for students, faculty, and administrators. The proposed ICMS incorporates modular data models for managing students, staff, courses, attendance, and examinations. It features secure authentication mechanisms (JWT/OAuth), role-based access control, and interactive dashboards. Embedded visual analytics tools enable real-time monitoring of academic performance, attendance trends, and institutional resource utilization. Faculty can generate insightful reports (PDF/Excel), monitor student progress, and make data-informed decisions, while students gain personalized access to schedules, grades, and institutional announcements. The system supports cloud deployment, ensuring high availability, scalability, and cross-device accessibility. By integrating intelligent monitoring and analytics capabilities, the ICMS fosters a data-driven academic environment, ultimately enhancing institutional decision-making and educational outcomes.
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Atharva, Moholkar, and Rao Pranav. "Face Recognition based Attendance System." Face Recognition based Attendance System 8, no. 11 (2023): 3. https://doi.org/10.5281/zenodo.10224161.
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This article presents the creation of a system that utilises face recognition technology for attendance marking purposes in various settings. While face recognition has the least accuracy in comparison to the other biometric methods such as fingerprint or iris identification, its non-invasive and contactless approach makes it a popular choice. This system aims to address the inefficiencies of traditional manual attendance systems that are time-consuming and prone to errors such as proxy attendance. It has four phases: Creating the database, detecting the face, recognition of it and bringing the attendance up to date. Database is made using pictures of the people in the class. detection of face and recognition are done by using the Facial_Recognition python library which is very efficient and effective. The available system looks and recognises faces from video streaming live feeds of the classroom, and records of attendance are automatically forwarded to the available respective faculty members of the institute at the end of each particular session via mail.Keywords:- Face Recognition; Face Detection; Classifier; Attendance System; Recognition Libraries.
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Danish, Aafreen, Khushali Hedau, Diksha Ukey, Anisha Walde, Uzma Sohail Sheikh, and Prof Akbar Nagani. "Fingerprint,Face and Voice Recognition Based Attendance Monitoring System." International Journal for Research in Applied Science and Engineering Technology 10, no. 4 (2022): 749–52. http://dx.doi.org/10.22214/ijraset.2022.41346.
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Abstract: In This project aims to record the attendance without manual intervention. In the area of technology that changes and modifies daily, use biometrics is the most popular and trending technology. Taking attendance manually for a class of almost 60-80 students can be a time-consuming task if thought of it in a long run Each person has a unique biometric feature such as fingerprint, face structure, voice detection etc. Keywords— Boimetrics, Fringerprint, Face Structure,Voice Detection.
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Ashfaq, Mohd, Mohammad Amaan, Mohd Aalam, Mohd Aamir Ullah, Dev Raghav, and Anamika Goel. "Computer Vision based Attendance Management System for Students." International Journal for Research in Applied Science and Engineering Technology 11, no. 1 (2023): 1675–78. http://dx.doi.org/10.22214/ijraset.2023.48767.
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Abstract: The purpose of this project is to build an attendance management system based on facial recognition features. In most educational institutions, the attendance of the students is taken manually, using an attendance sheet, by the faculty member in a classroom. The objective of this project is to minimize the time consumed in the process of monitoring the attendance of the students and to tackle the problem of proxy by almost eliminating the use of paper in the attendance taking process. Manually recorded attendance can be easily tampered with and manipulated. It is also not very easy to verify manual attendance. So, we are proposing a method that can estimate the attendance more precisely using all the results of face recognition, which are obtained by continuous observation. In this system, the enrollment of students will be a one-time process, Students may have their roll number or phone number as their unique ID, which should be unique for every student. Their images will be stored in the database. The attendance of the students will be tracked automatically for every hour. This system will overcome the problems that exist in manual or traditional attendance management systems.
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Khan,, Shahadatt. "Real Time Attendance Monitoring System using Face Recognition." INTERANTIONAL JOURNAL OF SCIENTIFIC RESEARCH IN ENGINEERING AND MANAGEMENT 08, no. 05 (2024): 1–5. http://dx.doi.org/10.55041/ijsrem34800.
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The management of the attendance can a huge burden on the teachers if it's done by hand. To solve this problem, a smart and auto attendance management system is being used. However, authentication is a significant issue in this system. The smart attendance system is commonly executed with the assistance of biometrics. Facial recognition is one of biometric methods to enhance this system. By using this framework, the situation of proxies and students being marked present despite their physical absence can easily be resolved. The main implementation steps used in these types of systems are facial detections and recognizing the detected faces. This paper suggests a model for implement an automated attendance management system for students of a class. The suggesting system makes the usage of Haar classifiers, OpenCV and LBPH algorithm. Following facial recognition, attendance reports will be produced and store in excel formats. The system is experimented under various conditions like illumination, head moves, the changes of distance between the student and cameras. After intensive testing, overall complexities and accuracies are calculated. The Suggested system demonstrated to be an effective and powerful device for taking attending in a classroom without any time use and manual works. Keywords – Face Recognition, Face Detection, OpenCV, Haar Classifiers.
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panwar, Mukul. "Real Time Attendance Monitoring System using Face Recognition." INTERANTIONAL JOURNAL OF SCIENTIFIC RESEARCH IN ENGINEERING AND MANAGEMENT 08, no. 06 (2024): 1–5. http://dx.doi.org/10.55041/ijsrem35443.
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The management of the attendance can a huge burden on the teachers if it's done by hand. To solve this problem, a smart and auto attendance management system is being used. However, authentication is a significant issue in this system. The smart attendance system is commonly executed with the assistance of biometrics. Facial recognition is one of biometric methods to enhance this system. By using this framework, the situation of proxies and students being marked present despite their physical absence can easily be resolved. The main implementation steps used in these types of systems are facial detections and recognizing the detected faces. This paper suggests a model for implement an automated attendance management system for students of a class. The suggesting system makes the usage of Haar classifiers, OpenCV and LBPH algorithm. Following facial recognition, attendance reports will be produced and store in excel formats. The system is experimented under various conditions like illumination, head moves, the changes of distance between the student and cameras. After intensive testing, overall complexities and accuracies are calculated. The Suggested system demonstrated to be an effective and powerful device for taking attending in a classroom without any time use and manual works. Keywords – Face Recognition, Face Detection, OpenCV, Haar Classifiers.
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Khadatkar, Vikrant, Shubhangi Bagadkar, and Prof Nutan Dhande. "Face Recognition Based Attendance Management System Using HOG Feature Extraction and SVM Classifier." International Journal for Research in Applied Science and Engineering Technology 10, no. 3 (2022): 2079–83. http://dx.doi.org/10.22214/ijraset.2022.41056.
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Abstract: Face recognition system plays a vital role in almost every sector in this digital era. Face recognition is one of the popular biometrics’ techniques. It can be used for security, authentication, identification and so on. It is having low accuracy when compared to iris recognition and fingerprint recognition, but it is being widely used due to its contactless process. Face recognition technique can also be used for attendance marking field. This system targets to building a class attendance system which is used the technique of face recognition. We all know existing manual attendance system is taking more time and difficult to maintain. And having chances of proxy in attendance. That’s why, the need for this system occurs. This system consists of four phases- registration module, database creation, face detection, face recognition, attendance updating, attendance sending. Database consist of the image of the students in class. Face detection and recognition is performed using HOG feature extraction and SVM (Support Vector Machine) classifier. Faces will be detected and recognized from video streaming of the classroom. Attendance will be mailed to the respective faculty at the end of the lectures. Keywords: Face Recognition; Face Detection; SVM classifier; HOG feature extraction; attendance system;
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Sahu, Kunal. "iAttend: A Real-Time Attendance Monitoring System using Face Recognition Technique." International Journal for Research in Applied Science and Engineering Technology 13, no. 4 (2025): 6567–75. https://doi.org/10.22214/ijraset.2025.69888.
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Abstract: In education, accurate and efficient attendance tracking is critical. This paper presents iAttend, a real-time, face recognition-based attendance system that automates attendance management using computer vision and machine learning. Built with Python-Flask, OpenCV, and the face_recognition library, iAttend enables secure, contactless verification through live webcam feeds, matching captured faces with pre-encoded data. Attendance entries include time, date, subject, and teacher identity, stored in a structured CSV format for analysis. A student dashboard provides dynamic summaries and subject-wise attendance percentages. Testing achieved over 95% recognition accuracy under well-lit indoor conditions, with sessions for a 30- student class completing in under a minute. Despite challenges like lighting sensitivity and absence of liveness detection, iAttend demonstrates practicality, scalability, and cost-effectiveness. Future work will focus on mobile support, cloud integration, and enhanced biometric features.
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M. E., Omotayo,, and Adegbite, I. O. "Design, Development and Testing of Electronic Class Attendance using Fingerprint." Advanced Journal of Science, Technology and Engineering 4, no. 4 (2024): 55–65. http://dx.doi.org/10.52589/ajste-zfttfqbv.
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Electronic Class Attendance System (e-CAS) is an easy way to keep track of attendance of students and lecturers in School. It will cover the requirements of the personnel department in terms of day-to-day monitoring of students' and lecturers activities. Hence, students’ attendance is an important issue every institution must take into consideration to be productive. Hence, this research aims to design, develop and test using fingerprints. The methodologies used were miniature techniques and image processing techniques for design and development. This target was mainly decomposed into image pre-processing, feature extraction and feature match. For each sub-task, some classical and up-to-date methods in literature were analysed. Based on the analysis, an integrated solution for electronic class attendance was developed for demonstration. However, Poison probability process, Biometrics as well as NP-chart of Quality control were adopted for classical statistical analysis of quality and functionality of the e-Class Attendance System (e-CAS). The project on electronic class attendance system was coded by PHP and the hardware was developed with ATMEGA series of microcontrollers. The result when experimented achieved the objective of improving the performance and consistency of the electronic class attendance system based on template matching techniques as well as class attendance for both students and lecturers.
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Alam, Md Azad. "FACIAL RECOGNITION ATTENDANCE SYSTEM." INTERANTIONAL JOURNAL OF SCIENTIFIC RESEARCH IN ENGINEERING AND MANAGEMENT 08, no. 03 (2024): 1–5. http://dx.doi.org/10.55041/ijsrem29448.
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Colleges have historically faced a great deal of difficulty with student attendance, necessitating a large time and effort investment from staff in manual tracking. Even though they are in place, the existing biometric attendance systems are not entirely automated, which causes delays in processing fingerprints, maintenance issues, and inefficiencies in time. Given that almost everyone has a smartphone and is continuously online in this day and age, a more simplified method is necessary. This study suggests using sophisticated object identification algorithms to check attendance using faculty members' smartphones. Because of its effectiveness in face detection and the addition of Microsoft Azure's face API for database recognition, YOLO V3 (You Only Look Once) is the preferred option among these. One special feature of the system is that it takes pictures of the classroom at the start and finish of every class to make sure everyone is present. After determining the number of students in each photograph, YOLO V3 separates the faces that are known and those that are unknown, creating distinct spreadsheets. Monthly email reminders are also sent to teachers, parents, and students. The system that has been put into place shows strong real-time performance in counting and detecting jobs, with excellent facial recognition accuracy and overall efficiency. Keywords:, OpenCV, Local Binary Pattern Histogram (LBPH), Real-time Tracking, Facial Analysis, You Only Look Once (YOLO V3), Firebase Database.
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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 system. As a result, in addition to tracking students' attendance, the system notifies the students' parents by SMS when they are present or not. Key Words: Monitoring, Tracking, attendance, RFID
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Olubukola, Adekola, Owelle Kenechukwu, Daramola Jumoke, Mgbeahuruike Emmanuel, Adeoti Babajide, and Oyebola Akande. "Student Attendance Monitoring System using Facial Recognition." CURRENT TRENDS IN INFORMATION COMMUNICATION TECHNOLOGY RESEARCH 2, no. 1 (2023): 47–59. http://dx.doi.org/10.61867/pcub.v2i1a.048.
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In this age of rapidly evolving technologies and trends, performing routine tasks like Attendance Recording should no longer follow the manual or semi-manual tiresome methods. Taking students’ attendance records in the classroom during a lecture period is now a common practice in the University systems especially in most private institutions in Nigeria; a case study employed is Babcock University, Ilisan Remo, Ogun State, Nigeria. This helps to account for where a student is per time, increases student’s learning focus and helps the institution to make the right decision for instance whether to allow a student to take the final exam or not. Attendance marking using conventional methods such as calling students’ names one by one or having them to write it could be quite tedious and time wasting. It becomes more difficult to manage when the class size is large. Another challenge includes the possibility of capturing a proxy attendance such as students writing for their absent colleagues. This study proposes to solve this problem using a biometric information processing known as the facial recognition system. Its application is easier with working range larger than others such as fingerprint, iris scanning and signature. Many algorithms and techniques have been developed to improve facial recognition performance, but the proposed model employs Cascade Classifier which breaks the problem of detecting faces into multiple stages. For each stage, the algorithm performs a very rough and quick test, and if this current stage passes, it does a slightly more detailed test. It eventually detects a face if all stages are passed. The implementation tools include Python, HTML, MySQL, PyCharm, XAMP server as the local host server and a web browser to register and display results. As a result, this development makes attendance monitoring simple, efficient, and time saving. Keywords: Attendance, Monitoring, Biometric, Facial Recognition, Cascade Classifier.
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Santos, Arman Bernard G., Neil P. Balba, and Corazon B. Rebong. "Attendance Monitoring System of Schools in the Philippines with an Inclusion of Optimization Query Algorithm." Regular issue 10, no. 8 (2021): 142–46. http://dx.doi.org/10.35940/ijitee.h9149.0610821.
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In this paper, researchers had provided definite solutions in order to check and validate student attendance with the use of computerized seat plans along with the information and image of each student. This study also discussed the inclusion of Optimization Query Algorithm in order to identify and monitor student’s punctuality as well as the analysis of the reasons why they fail to attend their class. Attendance patterns are formed early in life because it validates one of the components of student’s academic and scholastic performance. Regular attendance is vital part of the grading component necessary to attain some portion of the student’s academic progress. You are missing out on active learning experiences and class attendance. As a result, they are more likely to to fail which tends to affect their academic performances.
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Pathak, Vandana, Vidhi Gill, Devansh Vihan, and Jagbeer Singh. "Automatic Attendance Monitoring Using Python." Journal of Innovations in Data Science and Big Data Management 2, no. 1 (2023): 9–15. http://dx.doi.org/10.46610/jidsbdm.2023.v02i01.002.
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Face detection and recognition are very important and required in today’s fast world. The issue of the regularity of students would be maintained. This software uses facial recognition which is very fast and accurate, hence there isnochance of fake attendance,it is purely software-based which means it is eco-friendly, with no consumption of paper at any time of the process. Our project can be implemented in the field of recording attendance. The motive of the project is to construct a face recognition system for tracking attendance in an organization and update the current or traditional attendance system into an advanced and automatic system for effective attendance monitoring. In the project, a database is created which contains the face and feed data that will be used by the recognition algorithm. When the student enters the class or the attendance session starts, then the data of students is already stored and will be fetched from there to check the identity of a particular student. If the data points match the identity then they are allocated to the attendance or marked as present and the information about it will be directly stored in the spreadsheet. All the data related to the student will also be linked to the student's profile so if the student wants to access other information like progress, project marks, and subject marks then they can request access, once the access is approved the student would automaticallybeable to track his/her progress so far
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Arman, Bernard G. Santos, P. Balba Neil, and B. Rebong Corazon. "Attendance Monitoring System of Schools in the Philippines with an Inclusion of Optimization Query Algorithm." International Journal of Innovative Technology and Exploring Engineering (IJITEE) 10, no. 8 (2021): 142–46. https://doi.org/10.35940/ijitee.H9149.0610821.
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In this paper, researchers had provided definite solutions in order to check and validate student attendance with the use of computerized seat plans along with the information and image of each student. This study also discussed the inclusion of Optimization Query Algorithm in order to identify and monitor student’s punctuality as well as the analysis of the reasons why they fail to attend their class. Attendance patterns are formed early in life because it validates one of the components of student’s academic and scholastic performance. Regular attendance is vital part of the grading component necessary to attain some portion of the student’s academic progress. You are missing out on active learning experiences and class attendance. As a result, they are more likely to to fail which tends to affect their academic performances.
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Onwubiko, E. I., S. E. Chaku, V. E. Kulugh, and G. I. O. Aimufua. "Development of a lecture attendance monitoring system with multi-level authentication." Science World Journal 20, no. 1 (2025): 230–36. https://doi.org/10.4314/swj.v20i1.30.
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This study presents the development of a Lecture Attendance Monitoring System that employs Multi-Level Authentication (MLA) techniques to enhance security, accuracy, and efficiency in attendance management. Traditional methods, such as manual roll calls or sign-ins, are prone to proxy attendance and human errors, undermining the integrity of attendance records in academic institutions. To address these challenges, the proposed system integrates Biometric Fingerprint Authentication and One-Time Password (OTP) mechanisms. During enrollment, students’ fingerprints are captured validating user identity before granting access . Additionally, an OTP is sent to the student’s registered email for verification during class sessions, combining authentication layers to ensure reliable attendance tracking while eliminating opportunities for fraud. Attendance records, including timestamps, are securely stored in a centralized database for easy retrieval and analysis. The system was developed using the agile methodology, allowing iterative development and continuous refinement through testing and user feedback. Results demonstrate significant reductions in errors and the need for human intervention, documenting the system's measurable improvements in throughput and stability to traditional attendance methods. This research highlights the transformative potential of multi-level authentication for applications requiring high security and reliability. While designed for academic settings, the system can be adapted for other domains where secure verification is critical.
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. A.B. Jirapure, Dr. "Fitness Facility Supervision System." INTERNATIONAL JOURNAL OF SCIENTIFIC RESEARCH IN ENGINEERING AND MANAGEMENT 09, no. 05 (2025): 1–9. https://doi.org/10.55041/ijsrem47839.
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Abstract—The Fitness facility supervision system is a comprehensive software solution designed to streamline and optimize gym operations. It automates essential tasks such as membership registration, class scheduling, attendance tracking, staff management, and financial transactions to enhance efficiency and user experience. The system leverages HTML, CSS, JavaScript, and Python to create an interactive and user-friendly platform. By replacing traditional manual methods with a digital solution, gyms can minimize errors, improve resource management, and provide better communication channels for members and staff. This system ultimately helps gym owners and managers focus on delivering high-quality fitness services while ensuring smooth business operations. Keywords: Gym Management, Membership Tracking, Class Scheduling, Attendance Monitoring, Financial Management, Automation, Fitness Business Optimization.
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DiBacco, Priscilla M., Vincent J. Hetherington, and David Putman. "Lecture Capture." Journal of the American Podiatric Medical Association 102, no. 6 (2012): 491–98. http://dx.doi.org/10.7547/1020491.
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Background: The intent of this research was to evaluate the Mediasite lecture capture system at the Kent State University College of Podiatric Medicine (formerly the Ohio College of Podiatric Medicine) to determine the acceptance, use and benefits to both students and faculty and to identify any concerns, limitations, and suggestions for expansion. There is extreme debate on the effect of lecture capture on student attendance included in the research. Methods: Two surveys were compiled, one each for students and faculty. These were distributed by email to the entire student body and all full-time and part-time faculty. Responses were voluntary. The questions sought to identify the priorities of the participant, reasons for viewing lectures compiled by course, to assess any effect on class attendance and to evaluate the ease and use of the technical function. There was also a section for subjective responses and suggestions. Results: The tabulations proved a very high use of the program with the most important reason being to prepare for exams. The question of class attendance is still open to interpretation. Technically, the Mediasite system was ranked easy to use by both groups. Conclusions: The results of this survey confirm the concept of lecture capture as an integral segment of advanced education. Though this system should not replace class attendance, it is a vital supplement to course work and study. By reviewing all of the components of the survey those who may have concerns on its effectiveness are also aware of the advantages. The results of this study met all the objectives to evaluate use and obtain viewpoints to improve and expand the program. (J Am Podiatr Med Assoc 102(6): 491–498, 2012)
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Katherine, G. Frigillana, C. Jocson Joefil, Manfre C. Muldong Roviel, O. Natividad Lester, and T. Tiongson Hazel. "THE EFFECTS OF REIMPLEMENTING A BIOMETRIC ATTENDANCE MONITORING SYSTEM IN THE ELECTRONICS ENGINEERING DEPARTMENT AT DON HONORIO VENTURA STATE UNIVERSITY." Engineering and Technology Journal 08, no. 12 (2023): 3138–42. https://doi.org/10.5281/zenodo.10275672.
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Monitoring the attendance of staff and employees holds paramount importance in organizational settings. This can be accomplished either manually, using logbooks and daily time records, or automatically through advanced technologies such as radio frequency identification, biometrics, and bar code scanners. Biometrics attendance monitoring systems, in particular, offer a range of benefits, including heightened security, accuracy, convenience, scalability, time efficiency, compliance, and accountability. This research paper elucidates the advantages of the biometric system, examining its impact on the employees of the Electronics Engineering Department at Don Honorio Ventura State University during the 1st Semester of the Academic Year 2023-2024. The Biometrics Attendance System proves to be exceptionally effective and efficient, gaining a consensus of 92% among participants regarding its positive impacts. Ratings consistently hover at 4 or 5 for efficiency, underscoring the streamlined processes. Accessibility earns a positive average score of 80%, and privacy measures receive an equally commendable average score of 82%. While the system generally contributes positively to managing absenteeism, an outlier score of 1 from a participant prompts further investigation. In conclusion, the Biometrics Attendance System excels in effectiveness, efficiency, and user satisfaction, positioning itself as a secure, accurate, and convenient solution. This becomes especially relevant as the Electronics Engineering Department integrates the biometric system, reaping benefits in terms of security, accuracy, and time efficiency. However, it's noteworthy that the implementation of the biometrics attendance system correlates with an increase in faculty absenteeism. Addressing specific concerns identified in the Manual Attendance System could guide targeted improvements for a more comprehensive and satisfactory attendance monitoring system overall.
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Banada, Manoj. "AI Powered Attendance System for Class Rooms using Face Recognition." INTERANTIONAL JOURNAL OF SCIENTIFIC RESEARCH IN ENGINEERING AND MANAGEMENT 09, no. 01 (2025): 1–9. https://doi.org/10.55041/ijsrem40676.
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Facial recognition technology is rapidly evolving and becoming a transformative tool in many fields. This paper presents the design and implementation of an AI-powered facial recognition system tailored to a classroom environment. This is different from traditional methods that rely on manual data entry or intrusive biometric systems. Our solution automatically marks attendance using a single frame video capture method. This method significantly reduces the computational cost by guaranteeing high accuracy. This makes it a practical option for educational settings. The proposed system has three main components: a camera module for capturing images in the classroom; A processing module powered by deep learning algorithms for face detection and identification. and a database module for secure attendance record management. This improved workflow This involves detecting faces using extracting data features through an advanced convolutional neural network (CNN) such as FaceNet, and matching the embeddings with stored records using a cosine similarity measurement. It ensures efficient and reliable status awareness. The system was tested in a simulated classroom with 50 students, with a recognition accuracy of 95.2%, an average processing time of 2 seconds per round, and performance consistent with 100 students in a single take. This innovative approach provides a non-intrusive, scalable and efficient solution for attendance automation. Reduce errors by reducing manual effort. Future improvements aim to include real-time monitoring of late arrivals. strength improvement Keyword : Facial recognition technology, AI-powered system, classroom environment, attendance automation, video capture method, computational cost, deep learning algorithms, face detection, face identification, Convolutional Neural Network (CNN), FaceNet, data features, cosine similarity, attendance record management, recognition accuracy, processing time, simulation, scalable solution, non-intrusive, real-time monitoring, late arrivals, system performance, database module, secure records
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Jindal, Vishesh, Mohd Suhail Khan, Vipul Sharma, Dr Shishir Rastogi, and Dr Rajesh Singh. "Smart Attendance System Using AR Marker." International Journal for Research in Applied Science and Engineering Technology 10, no. 4 (2022): 3017–21. http://dx.doi.org/10.22214/ijraset.2022.41977.
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Abstract: In the current scenario smartphones play a vital role in our daily life, In fact they are a part of our lives. Smartphones can now handle the majority of problems fast and easily. Every person's life has been made simpler and easier as a result of it.Basically this paper focuses on the problem which is faced by the faculties and students during the process of attendance and there are more chances of proxies in the traditional method (using pen and papers). The paper proposed a system that will use AR Marker technology and handle the problem for recording the attendance of the students in school and colleges. The suggested system consists of two applications: one for creating the AR Marker by entering class information via faculty, and another for scanning the QR code via students. The teacher will generate the QR code and present it to the students using a projector, after which the students will simply open the second app and scan the QR code to get their attendance. The Smart Attendance System is cost effective because it does not rely on biometric devices which are expensive. The paper explains how the system authenticates students' identities in order to prevent fraudulent registrations. By changing the QR code every five to ten seconds and just for five minutes, the system is able to reduce the proxy level. If any student fails to show up for class, the professor may display the QR code again. The system is in charge of managing and evaluating all students' attendance. In addition, the system will save the attendance data in XLS and CSV files for future use. Keyword: Smart Attendance System, AR Marker, Attendance System using QR Code, Software as a Service .
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Narkhede, Puja. "College Automation System Using IOT." International Journal for Research in Applied Science and Engineering Technology 10, no. 7 (2022): 654–58. http://dx.doi.org/10.22214/ijraset.2022.45361.
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Abstract: College Automation System Using IOT Project will work on College Electrical Appliances Remote control and Improved Attendance System. It will include Automation of all the Electrical gadgets in the college. It will have Facial Recognition verified RFID Attendance system along with Appliances Remote Control System for every class so that admin can see all Incoming and Outgoing Students Record on the Web User Interface and can also control the Gadget switches through a click on their phone. Let us see how this College Automation System Project will work. College Automation System Project will help the college administrator. Administrator will able to get all the information regarding any faculty members on particular day and time. Admin panel will also able to edit the login display panel of teachers, staff members, students etc. Admin can add person, delete person, can give special permission. Teachers can also see list of students who comes under the category of attendance shortage and many more under this one roof
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A, JEYALAKSHMI. "Enhanced Method of Emotion Detection and Face Recognition for Attendance Monitoring Using Machine Learning." INDIAN JOURNAL OF NATURAL SCIENCES 15, no. 83 (2024): 72249–55. https://doi.org/10.5281/zenodo.13341188.
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The use of facial recognition is essential in every industry in the modern era. One of the most popular biometrics is face recognition. Along with many other benefits, it can be used for security, authentication, and identity. Additionally, facial recognition software can be used to record attendance in work environments, institutions, and colleges, among other places as well. The sustainable attendance system seeks to streamline the attendance management process and save time and effort for both administrators and attendees. Automated facial recognition technology eliminates the need for manual data entry and reduces the administrative burden associated with attendance tracking. It allows administrators to allocate resources more efficiently and focus on more value-added tasks. The currently available manual method takes a lot of time and work to maintain, so the goal of this system is to build up a facial recognition-based class attendance system. Moreover, there may be opportunities for proxy participation. The machine learning project, titled " Emotion Detection and Face Recognition for Attendance Monitoring" trains a model to identify student attendance based on their emotions during class using Python, OpenCV, and student datasets. Facial emotion recognition and classification are done using the CNN and Haar Cascade algorithms. It ensures accurate attendance records by capturing and analyzing facial features using computer vision algorithms. The goal of this project is to offer an alternative to the manual attendance-taking approach that is currently in use by staff members.
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Thomas, Rahul. "Real-Time Class Room Attendance Monitoring System based on Face Recognition." International Journal of Information Systems and Computer Sciences 9, no. 3 (2020): 16–20. http://dx.doi.org/10.30534/ijiscs/2020/02932020.
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