Attendance Monitoring System Research Articles

Sistem Monitoring Kehadiran Mahasiswa Berbasis IoT

Conventional student attendance monitoring systems often face problems such as data inaccuracy and delays in attendance information. This study aims to develop an efficient and real-time RFID and Internet of Things (IoT)-based student attendance monitoring system. The methods used include hardware design using the RC522 RFID module and ESP32 microcontroller, web-based software development, and implementing WhatsApp notifications using the API. The trial results show that the system successfully integrates RFID and IoT technology with a tag reading accuracy level at an optimal distance of 1-5 cm. The system is able to send real-time notifications to parents' WhatsApp with a success rate of around 80% and an average response time of 1.2 seconds from RFID reading to recording in the database. The developed web interface obtained a System Usability Scale (SUS) score of 82.5, indicating a good level of usability. The developed system offers an effective solution to improve the accuracy and efficiency of student attendance monitoring, as well as increasing transparency between educational institutions and parents.

Intensify Cooperative Learning: An Investigation into School Attendance Monitoring Systems

Intensify Cooperative Learning: An Investigation into School Attendance Monitoring Systems

Face Recognition Attendance System

Abstract— Face recognition is a biometric technique which involves determining if the image of the face of any given person matches with any of the face images stored in the database. This problem is very difficult to solve automatically due to the changes that various factors, such as facial expression, ageing and even lighting. It is widely used in areas such as security and access control, forensic medicine, police controls and attendance management system. Our Face Recognition Attendance System can utterly eliminate the manual work wherever the attending can now not involve any paperwork. This system will scale back the whole time required for attending marking. The system can acquire individual attending with the assistance of facial recognition to secure information accuracy of the attending. The primary goal of this project is to build a face recognition-based attendance monitoring system for employees working in an organization in order to improve and upgrade the current attendance system to make it more efficient and effective than before. The employee should be in an area containing light so that the detection can be clearly made. Keywords: Face recognition, biometric technique, image matching, database, facial expression, ageing lighting, security, access control, forensic medicine, police controls, attendance management, manual work, paperwork, time reduction, facial recognition, data accuracy.

An Automated Approach for Classroom Attendance Using OpenCV

Abstract: The "AI Attendance: Automated Attendance Monitoring System" employs artificial intelligence and facial recognition to revolutionize attendance tracking, replacing inefficient methods like roll calls and ID cards. This system eliminates manual record-keeping, reducing administrative burdens while ensuring accurate real-time identification of individuals' attendance. Technologies such as Flask Framework, OpenCV, and Pandas Library are utilized to develop a user- friendly web interface for face registration and attendance marking.With Pickle for serialization, registered faces persist seamlessly, enhancing efficiency and accuracy in attendance monitoring across various sectors

Automatic Face Recognition Attendance System using Python and Open CV

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.

Students Attendance Monitoring System Using RFID and GSM

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.

Inovasi Aplikasi Sikepo dalam Meningkatkan Kinerja Pegawai di Kabupaten Bojonegoro

In the application of the digital attendance system, problems still often occur, an online attendance system that can be misused by the absence of employees at the workplace. The purpose of this research is to find out the discipline of the State Civil Apparatus by innovating new developments about the location-based ASN attendance monitoring system called SiKepo, making it easier for employees to access this system from anywhere. Researchers used qualitative research techniques in this study, using a qualitative approach to the case study method. Based on the results of the study, the innovation of the SiKepo application can improve employee discipline, efficiency, and effectiveness. Because there is data monitoring where employees are required to leave in the morning, with attendance using electronics. And can also use a fingerprint machine that is connected to the application if there are system error problems. After the implementation of SiKepo, there was an increase in the percentage of attendance, which used to be employees who deliberately skipped school with an average of 5 to 6 times a month, now employees are more disciplined. However, frequent error constraints require the uprage system to be better.

Employee Monitoring System Using Power BI

Abstract: This paper introduces an HR attendance and task monitoring system, which has been developed utilizing Power BI. The system provides a comprehensive dashboard for HR personnel to visualize and track employee activity effectively. The dashboard includes key aspects such as Attendance Monitoring system works on real-time or historical attendance data can be showcased, letting HR to identifies trends, patterns, and potential attendance problems. Employee Skills & Roles this section presents a clear view of employee skillsets and assigned roles, helping in informed project allocation and resource management accurately. Project Assignments the dashboard keeps track of current project assignments for each employee, empowering HR to understand workload distribution and make adjustments when needed. By utilizing Power BI's data visualization and analysis abilities to the fullest extent, this system augments HR to gain crucial insights into employee activity. This assists in better decision-making in areas like attendance management, project allocation, and resource optimization, ultimately contributes to a more efficient and productive workforce

I-CHECKIN@PKB: The acceptance among Politeknik Kota Bharu staff

I-Checkin@PKB has been utilized at Politeknik Kota Bharu (PKB) for nearly six months, replacing the thumbprint attendance monitoring system. With I-Checkin@PKB, users can eliminate the need to wait in line at the centralized terminal for attendance registration, making it more efficient and hygienic. This system helps avoid potential germ transmission through contact with the same terminal, particularly amidst the challenges posed by Covid-19 and viral fever outbreaks. While the management of PKB has received verbal feedback from users, the actual level of user acceptance regarding I-Checkin@PKB remains unknown. Therefore, this study aims to investigate the acceptance level among I-Checkin@PKB users, focusing on perceived ease of use, perceived usefulness, attention to use, and behavioral intention. The study involved 100 respondents selected through random sampling. Utilizing 12 items with a Cronbach Alpha reliability coefficient of α=0.97, representing the constructs, the results indicated a high level of acceptance among users regarding I-Checkin@PKB, including its ease of use, usefulness, attention, and behavioral intention. Furthermore, the positive perceptions among I-Checkin@PKB users are likely to garner continuous support due to its ability to reduce the risk of human error associated with manual methods, such as paper-based attendance sheets. It is crucial to emphasize that while I-Checkin@PKB systems offer numerous benefits, their successful implementation necessitates clear communication, employee training, and consideration of privacy and security concerns to ensure a positive experience for both employees and the organization.

Design and Implementation of NFC-based Staff Attendance Monitoring System

In today's dynamic work environment, efficient attendance management is crucial for organizational productivity. Traditional attendance systems often involve manual processes, leading to inaccuracies, time inefficiencies, and potential security concerns. This paper proposes an innovative solution—NFC[1] (Near Field Communication) based staff attendance system—to address these challenges. The NFC-based staff attendance system[2][3] leverages the capabilities of NFC[1] technology to streamline the attendance tracking process. Each staff member is provided with an NFC-enabled identification card, eliminating the need for manual sign-ins or cumbersome biometric systems. The NFC cards are easily scanned using NFC readers strategically placed at entry points. The implementation of the NFC-based staff attendance system presents several advantages, including improved efficiency, reduced administrative overhead, and enhanced security.

IOT BASED ATTENDANCE SYSTEM USING FINGERPRINT SENSOR

To provide reliable, time-saving and automatic class attendance system, the concept of Internet of Things (IoT) based class attendance monitoring system using embedded Linux platform is presented in this project . The study is focused on the design and implementation of fingerprint detection and recognition system using Arduino Uno. The system takes fingerprint of students, and analyzes, detects and recognizes fingerprint using sensor .After collecting processing data, the system generates a final attendance record and uploads it in a cloud server. The cloud server has been implemented using python based web framework. The record can be accessed remotely from a user-friendly, web application using the Internet. Finally, the system is also capable of sending an email notification with the final record to the teachers and students in a specific time. Tests and performance analysis were done to verify the efficiency of this system

MACHINE LEARNING AND BLOCKCHAIN-BASED REAL-TIME FACIAL RECOGNITION ATTENDANCE SYSTEM

In a vast majority of fields, the use of facial recognition for authentication is expanding. In this information age, authentication has become vital, and the need for faster and more secure methods of user authentication has been on the rise. The introduction of image processing technologies such as OpenCV has increased society’s reliance on face recognition. Using blockchain, information could be stored in blocks throughout the blockchain network. Blockchain is an extremely secure means for storing and protecting data from intruders. It is a highly disruptive technology that has the ability to alter every plane of society. This paper intends to implement opensource computer vision (OpenCV) to construct a facial detection model that will be employed in a blockchain-secured Attendance Monitoring System. It will not only automate the attendance procedure but also give the system unassailable security. This system will take a live video feed from a camera using OpenCV and identify the faces of students and record their attendance along with the entry time. The data will be kept in a distributed way over the blockchain network that will be accessible to everyone, but data cannot be manipulated.

Geospatial Attendance Tracking: Leveraging Location Based Technology

The increasing popularity of expert system applications is undeniable. Computer technology evolution has significantly impacted various domains, including environmental security.Onenotable advancement is the elimination of manual attendance procedures, which were not only time-consuming but also prone to providing inaccurate results. The introduction of automated time and attendance monitoring systems has brought numerous benefits to organizations. These systems reduce reliance on pen-and-paper-based manual attendance tracking. In alignment with this shift, we have introduced an attendance system based on location, utilizing global positioning (GPS) technology. This system operates through a mobile application on smartphones, leveraging the GPS capability to determine the device's location. The location data serves as a key component in the time and attendance tracking process, eliminating the need for traditional manual methods. To achieve this, we employ the Geospatial technique, determining whether the student's location falls within the designated Geospatial locality. Our innovative project extends beyond attendance tracking and introduces a Child Tracking System within a dedicated application. This feature empowers parents to monitor their child's cell phone activities comprehensively. Parents can oversee incoming and outgoing calls, text messages, and multimedia messages. Additionally, they can track their children's whereabouts in real-time using GPS functionality and access a historical record of their locations. To enhance parental control, the system allows setting alerts for instances when children venture outside approved geographical ones

Facial Recognition Attendance Monitoring System using Deep Learning Techniques

The Facial Recognition Attendance Monitoring System employing Deep Learning Techniques represents a cutting-edge application of artificial intelligence in educational and corporate environments. The implementation of a Facial Recognition System can aid in identifying or verifying a person's identity from a digital image. Accurate attendance records are vital to classroom evaluation. However, manual attendance tracking can result in errors, missed students, or duplicate entries. The adoption of the Face Recognition-based attendance system could help eliminate these shortcomings. This innovative approach involves utilizing a camera to capture input images, detecting faces using algorithms such as Haarcascade, Eigen values, support vector machines, or the Fisher face algorithm, verifying the faces against a database of student profiles, and marking attendance in an Excel sheet. The use of OpenCV, an open-source computer vision library, ensures the efficient

Automated Attendance Monitoring System for Cattle through CCTV.

Automated Attendance Monitoring System for Cattle through CCTV.

Network Based Smart Attendance System for Students

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.

Facial Recognition Attendance Monitoring System using Deep Learning Techniques

The Facial Recognition Attendance Monitoring System employing Deep Learning Techniques represents a cutting-edge application of artificial intelligence in educational and corporate environments. The implementation of a Facial Recognition System can aid in identifying or verifying a person's identity from a digital image. Accurate attendance records are vital to classroom evaluation. However, manual attendance tracking can result in errors, missed students, or duplicate entries. The adoption of the Face Recognition-based attendance system could help eliminate these shortcomings. This innovative approach involves utilizing a camera to capture input images, detecting faces using algorithms such as Haarcascade, Eigen values, support vector machines, or the Fisher face algorithm, verifying the faces against a database of student profiles, and marking attendance in an Excel sheet. The use of OpenCV, an open-source computer vision library, ensures the efficient functioning of the system.

Web-based smart attendance monitoring system using QR code and GSM module for SMS notificatio

The study was designed and developed to address certain problems and concerns of the school administration and parents of students attending Ciriaco Mariano Elementary School. The system was used to provide the school an innovative way to record attendance of students, provide parents with real time updates regarding the entry and exit of their children in the school premises, and be able to monitor students by generating attendance reports. The Web-based Smart Attendance Monitoring System using QR code and GSM module for SMS notification was developed through the implementation of the Iterative System Development Life Cycle Model. This iterative model ensures that the web-based system conformed to the all of the requirements from the CMES and of the requirements set by the ISO 25010 criteria. To assess the quality of the developed web-based system, the researcher adapted the ISO 25010 Software Quality Standard as evaluation tool. Two sets of questionnaires were developed and were given to respondents who were selected using purposive sampling. The first set of questionnaires were given to IT experts to assess the technical qualities of the system which includes functional suitability, performance efficiency, compatibility, usability, reliability, security, maintainability, and portability. The second set of questionnaires were given to the school principal, teachers, and parents to assess the web-based system quality on selected criteria which includes functional suitability, performance efficiency, and usability. The Web-based Smart Attendance Monitoring System using QR code and GSM module for SMS notification was successfully developed using the iterative SDLC model and found conformed to the ISO 25010 software quality standards as implied by the results from the evaluation of IT experts, school principal, teachers, and parents.

Attendance Management System using Face Recognition

The main purpose of this project is to build a face recognition-based attendance monitoring system for educational institution to enhance and upgrade the current attendance system into more efficient and effective as compared to before. The current old system has a lot of ambiguity that caused inaccurate and inefficient of attendance taking. Many problems arise when the authority is unable to enforce the regulation that exist in the old system. The technology working behind will be the face recognition system. The human face is one of the natural traits that can uniquely identify an individual. Therefore, it is used to trace identity as the possibilities for a face to deviate or being duplicated is low. In this project, face databases will be created to pump data into the recognizer algorithm. Then, during the attendance taking session, faces will be compared against the database to seek for identity. When an individual is identified, its attendance will be taken down automatically saving necessary information into a excel sheet. At the end of the day, the excel sheet containing attendance information regarding all individuals are mailed to the respective faculty.

THE EFFECTS OF REIMPLEMENTING A BIOMETRIC ATTENDANCE MONITORING SYSTEM IN THE ELECTRONICS ENGINEERING DEPARTMENT AT DON HONORIO VENTURA STATE UNIVERSITY

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.