Smart Attendance System Research Articles

An Innovation in the Development of a Mobile Radio Model for a Dual-Band Transceiver in Wireless Cellular Communication

A modern telephone can only be used if it is a dual-band transceiver. Also, an indispensable condition is the availability of Internet access. Modern cell phones can only be used for their intended purpose: making calls. Due to the fact that the operating system is preinstalled on devices, the list of possibilities for gadgets could be expanded almost indefinitely. So you can even do a full-fledged dual-band transceiver from a cell phone. In this paper, an innovation in the development of mobile radio models dual-band transceivers in wireless cellular communication is proposed. For the dual-band transceiver in the phone to work, you need an Internet connection. Progress in the development of technologies for mobile networks does not stand still, and with each new standard and technology for mobile networks, new opportunities for using the network open up for end subscribers. It is based on packet voice data transmission called push-to-talk.

Low-Cost Active Monitoring of Attendance using Passive RFID Technology

In this paper, a smart attendance system for students attending schools 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 using it for grading and evaluation purposes. After careful study, passive RFID technology is selected to be used by the proposed system for its reasonable cost. The main components of the system are an RFID tag, an RFID reader, Visual Studio (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.

Smart Attendance System using QR Code

In this era of technology smartphones play a big role in our everyday existence. Nowadays smartphones can solve most of the problem very quickly and easily. It has made existence of absolutely everyone clean and much less hard with specific social app, commercial enterprise app, problem solving app, app for training and marketing and marketing and advertising etc. Followed with the resource of the use of the technology the paper purposed a system so one can cope with a problem for recording the attendance. In higher training institutions, student participation withinside the classroom is straight away related to their instructional performance. However, the majority of student attendance registration is still conventionally accomplished, it's tedious and time-consuming, in particular for those publications that comprise massive numbers of college students. Over the years, attendance manage has been done manually at most of the universities. To overcome the manual attendance issues, we proposed and carried out a smart attendance system with the aim to encourage the capability use of the Quick Response (QR) code as a future attendance manage system, to tune and file student attendance in lectures and carrying activities for all relevant publications, as an aim of this paper.

QR Code Attendance System with SMS Notification

Abstract: The attendance maintenance system is the major performance evaluation of the student. In recent periods, the student attendance is maintained in the system manually and updated in the particular college server. Several attendance systems have been proposed based on manual presence. This is a highly important problem. The administration requires careful follow-up, taking care of it and not being lenient. The previous systems are inefficient in term of processing time and low in accuracy. Smart Attendance System using QR Code with SMS Notification will be developed for helping lecturers to manage student attendance. To ensure the student attends in the classroom, QR code contained the time information was generated and displayed at lecturer presentation. The student only needed to scan the displayed QR code and face using ESP32 CAM. The code was then sent to the server for attendance process.

Development of a smart attendance system using near field communication (SMAT-NFC)

Development of a smart attendance system using near field communication (SMAT-NFC)

Development of a smart attendance system using near field communication (SMAT-NFC)

Taking attendance for classes has become more challenging, especially at institutions, due to the growing students population. Typically, the teacher calls names and writes them down. This approach has a number of drawbacks because when recording their attendance, students are diverted from the presentation and may register for absent classmates. The smart attendance solution suggested in this study allows students to tap their student identity (ID) card on a near field communication (NFC) reader, streamlining the attendance procedure by using near field communication (NFC) technology. The technique is affordable, effective, and simple to keep up. Automating student attendance saves time and alleviates anxiety. The average time for the NFC system to take a student's attendance is 3.5 seconds, compared to 16 seconds for the conventional method. The inaccuracy associated with recording attendance is reduced by 31% thanks to NFC technology. The numerical results of the NFC-based scheme are compared with the traditional scheme and observed that the proposed scheme outperforms the conventional scheme.

Utilizing beacon technology for the development of a smart attendance system

Tracking students’ attendance is part of academic cycles, however, academic staff members become overwhelmed by applying traditional methods for recording this. The dominant method of recording attendance is traditional methods such as calling students’ names and passing attendance sheets. These methods raise some concerns such as being time-consuming, spreading Coronavirus by sharing the attendance sheet, and other issues. The introduced and implemented solutions in the literature are rather expensive, time-consuming, lack accuracy, or require a long process to record the attendance. In this project, we aim to investigate the use of Bluetooth Low Energy (BLE) beacons at the main campus of Tabuk University to build a smart attendance system called the UTSA system. This system will help to overcome the raised concerns of applying the traditional methods for recording student attendance. Three interactive HTML prototypes were developed and examined using a heuristic evaluation methodology. The third proposed prototype, the instructor web-based system, was the most pleasing prototype by most evaluators compared to the two prototypes of the mobile app. All of the evaluators agreed that the current attendance system at Tabuk University is time-consuming and vulnerable to human errors during the transference of attendees from the attendance sheets to the online attendance system. The proposed system of this work provides an accurate and affordable method for signing in the students' attendance as it is going to be done using two steps for recording the attendance: Students mobile attendance broadcasting and academic staff verification process using the proposed app. Moreover, no additional equipment needs to be installed to apply the proposed solution as it used the students and the academic staff members mobile phones.

Human Image Classification and Identification

Abstract: Face Recognition is in recent times used as a chunk of various applications. It is used as a piece of the makes use of images processing applications. The Raspberry Pi 4 is embedded system. It is low cost, a single-board computer used to lessen the complexity of systems in actual time applications. This project is especially based on python. Raspberry pi carries Camera slot Interface (CSI) to interface the raspberry pi camera. Here, Images captured by using the Raspberry Pi camera module are improved so that it will identify the specific region of image. This is used in the real time application of ‘Smart Attendance System’. We have proposed to implement a “Smart attendance system using Face Recognition”. This system makes use of Face recognition package which saves a number of time than conventional method. This system requires Raspberry Pi 4, Open CV, Python etc. The system uses Face Recognition Package. This system compares the image of the test and the training image and decide who is present and absent. If student is absent a message will be sent to their parent’s phone number. Student will be greeted with the voice when he/she come in front of camera by using text to speech mechanism. The system wishes “Happy Birthday” if student’s birthday is there by checking the birth date and current date. Keywords: Open CV, Face Recognition, Raspberry Pi, Face recognition package.

Attendance System Based On Facial Recognition

Abstract: The face is the most important part of a person's identity. This physical characteristic has undergone a major change in methodology. Since the advent of image-processing technology, the goal of recognizing people is the only thing you can accomplish with a face recognition system. After recognizing someone, you can use more detailed processing to identify them. Traditional face recognition systems are not as accurate as you might want them to be. The system described in the present document is intended to deviate from this point of view. Introduce a traditional system to track students' faces and a new, more modern approach to identifying students. Keywords: SMART ATTENDANCE SYSTEM, A.I., FACIAL RECOGNITION, OPENCV, PCA

Automated Smart Attendance System Using Face Recognition

Abstract: In the human body, the face contains many important details, so the face is the most significant factor in identifying a person. There are several main ways to detect the presence of a person. Biometrics for capturing attendance. This is a time consuming process. In this paper, we will use a collection of rules to develop a model that classifies each character's face from the captured images. The HOG algorithm for recording student attendance. HOG (Histogram of Oriented Gradients) is one of the methods used to represent and classify images, is a common and effective method, and was chosen for its robustness against changes in pose and lighting. .. The proposed ASAS (Automated Smart Attendance System) captures images and compares them to the images stored in the databases. The database is updated during student enrollment using an automated process that also includes names and role numbers. Key Terms: HOG, python, ASAS

Smart Attendance System Using AR Marker

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 .

Face Recognition Attendance System

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

A review on smart attendance system with protection

Attendance is an important task in any institution. Manual methods generally waste a lot of time. They are also not the safest and fastest option. In schools and colleges, the most common technique for attendance is calling the students' names, and in industries, the most common method is signing a register which generally needs extra time to do the attendance. A "Smart Attendance System with Protection" is proposed to solve these problems. This project is mainly divided into 3 parts according to its applications which includes, attendance, thermal screening and ultrasonic sensors. For the automatic attendance part, the Local Binary Pattern Histogram (LBPH) method is used for the face recognition of the person. LBPH is considered the most useful technique for face recognition. For the second part of the project, thermal screening, a sensor (MLX90614) is used to take the temperature of the person and check if it is normal or not. In the third part of the project, ultrasonic sensors are used to detect the hands of the person. Under the sanitization section, and after detection, a small pump motor is used to pour the sanitizer into the hands of the person for the sanitization of their hands. Manual records can be easily extracted from the Smart Attendance System when needed. Attendance record manipulation is not possible in the system. The proposed device uses the Raspberry Pi, IRT, Ultrasonic Sensor, Pi Camera, and Pump Motor. An attendance record is generated and stored in excel format.

Face with Mask Detection and Recognition for Smart Attendance System

In this paper we will see the face mask detection and recognition for smart attendance system. In current pandemic situation our proposed system is very useful. We have used here face algorithm technique, python programming and to capture the images open cv is used., open cv2 now comes with a very new face recognizer class for the face recognition and popular computer vision liberaay started by intel in 1999. Open cv released under BSD licence that’s why used in the academic projects. We have used the concept of deep learning framework for the detection of faces. our aim is to present the study of previous attempts at face detection and recognition for smart attendance system by using deep learning .these is rapidly growing technology with its application in various aspects.

Real Time Implementation of Face Recognition based Smart Attendance System

This research work addresses the issue of incorporating an automatic attendance system to the frame of an institution using face detection and recognition techniques. The proposed system aims at reducing computational time with available hardware to yield more efficient results. The proposed model utilizes Histogram Oriented Gradients and facial encodings derived from facial landmarks. It also addresses the problems related to accuracy of facial recognition and the resource requirement for quick, real-time facial recognition by applying multi-processing. The improvement in performance in terms of accuracy across two different methods, and the improvement in terms of time requirement for the same method using different strategies have also been documented for demonstration. The designed system demonstrates the effectiveness of task parallelization with a minimum amount of hardware desiderata. The system has been designed to an optimum self-sustaining ecosystem which can efficiently operate on its own accord and compute comprehensible feedback without the requirement of any third-party human interference. A Graphical User Interface has been incorporated into the system for maximum user comprehensibility

Smart Attendance System for Covid-19

Due to the breakdown of COVID-19 pandemic also known as Serious Acute Respiratory Syndrome Corona virus-2 is an infectious disease that is released from an infected sick person. This spreads quickly through close contact with anyone infected. Institutions suffer a great deal from practically closed globally if the current situation is not going to change. Deep Learning has proven its effectiveness in recognition and classification through image processing. The research study uses deep learning techniques in distinguishing facial recognition and recognize if the person is having issues in the body temperature , respiration and pulse rate or not. The dataset collected and achieved an accuracy rate of 96% as to the performance of the trained model. The system develops a Raspberry Pi-based real-time face- patient monitoring and recognition that alarms and captures the facial image if the person detected and send the location to the nearly hospital. This study is beneficial in combating the spread of the virus and avoiding contact with the virus.

KOMBINASI SISTEM BERBASIS WEB DAN ANDROID SEBAGAI APLIKASI PRESENSI KEGIATAN MENGGUNAKAN QR CODE

Registration and list of attendees are an important factor to be done in formal and informal activities. The purpose is to know the attendees’ personal data and presence. Registration and presence using the manual method such as form filling in a piece of paper produce problem, among them is over excess of paper and time consuming presence activity. Therefore, a new efficient and effective system that take advantage of Android Smartphone and Quick Response Code (QR Code) as Smart Attendance System is needed. The use of Android and QR Code technology simplify registration and presence process so that the proses would be much faster and efficient. The design of QR Code presence application based on Android is using System Development Life Cycle (SDLC) Waterfall model and designed using Use Case Diagram and Entity Relationship Diagram. The presence application is made using combination of two platform, that is Android and web. On the Android Smartphone there are scanner and administrator profile. Whilst at the web platform contain participant, event, and admin database. The existence of the design and Smart Attendance system implementation, registration and list of attendees process will be faster, efficient, and used as on of the smart system to support the smart city is expected.

Integrated Smart Attendance System for English Learning Care

Integrated Smart Attendance System for English Learning Care

Smart Attendance: An Automated Attendance Management System Using Machine Learning Techniques

The Smart Attendance system is a machine learning-based system that aims to improve the management and tracking of student attendance. It can be utilized in educational institutions to keep track of their students' attendance. The system uses radio frequency identification tags to record information in real time, which helps the system to provide updated and accurate records. The system uses machine learning techniques to analyze the data collected by it to identify trends and patterns in student attendance. This method can then be used to identify individuals who are habitually late or have high absenteeism rates. It can help educators implement effective measures to improve student attendance. The performance of various machine learning algorithms was evaluated in this study. The four algorithms were randomly forest, decision tree, SVM, and naive bayes. They were tested against conditions such as students who frequently skip certain classes, habitual latecomers, and individuals with high absenteeism rates. The results of the study revealed that the SVM and random forest algorithms performed well and had the highest accuracy rates. These findings show that these algorithms can help educators identify patterns in student behavior and implement effective measures to boost attendance. The Smart Attendance system has demonstrated the potential of artificial intelligence to help improve the management of student attendance in educational institutions. Through the use of machine learning and RFID tags, the system can provide up-to date and accurate records, as well as insights into the behavior of students. This information can then be utilized to implement effective measures to reduce absenteeism and improve student outcomes.

Student Attendance Manager Using Beacons and Deep Learning

An efficient method for attendance management system is always been a challenging task for any organization varying from schools and colleges. This paper discusses about the attendance management system (AMS) and it's challenges. The paper proposes a student attendance system for schools and colleges using Beacon technology and Deep Learning techniques. The aim of this device is too savvy smart attendance system which includes the removal of issues like intermediary participation (for example proxy attendance for a student by another student). This is accomplished by obtaining live feeds from a fisheye camera at the beginning of each hour, which would be processed by a Convolutional Neural Network in the back end to enable students to choose their heads in the picture provided to them in their interface when they are in beacon proximity. Teachers interface will receive this same picture at the end of each hour to solve any discrepancy after which the data will be stored in a database. Hence, providing a foolproof system and efficient attendance tool.