The university is a learning hub where people are engaged in the communication of knowledge (students, faculty). Other resources such as libraries, computer labs, and halls of study are some of the critical resources that universities provide. At times, these facilities are indispensable for students to accomplish their academic goals, while at the same time, their management requires care to ensure that they run to their optimal capacity. The attendance tracking system can greatly assist university administrators in obtaining a firm picture of the demand for the facility as well as at the same time the resources allocated to such facility. In this project background, the need for an innovative attendance tracking system for use in university study facilities and how the captured attendance data can help measurement of the usage of the facility will be explored.
In the past, they have relied on manual attendance tracking using sign-in sheets. Though these methods do sometimes offer some basic knowledge regarding facility usage they are consequently inaccurate, time-consuming, and inefficient. However, manual tracking methods can also be quite challenging in finding patterns of how a facility is used and how such information can be used to make informed resource allocation decisions. Thus a better and more accurate system for keeping track of attendance in the facilities is required.
An attendance tracking system can be an innovative and accurate way to give university administrators a comprehensive and exact view of facility usage that can be used to make data-driven decisions regarding facility utilization. It can provide administrators with the data needed to make more effective and informed decisions as regards facility usage and patterns as well as peak usage times.
This project instead, has the problem statement of designing and implementing an innovative attendance tracking system for university campus study facilities that is capable of delivering detailed, accurate data on facility usage for various ways of tracking attendance. The attendance tracking system will provide administrators with the ability to make data-driven decisions on resourcing allocation and that the resource allocation is efficient and effective for supporting the needs of students and faculty.
In most cases, facility administrators are not aware of how study areas, books, and computer labs are used. It can lead to the underutilization or overburdening of resources inefficient resource allocation and a lack of resources to use for users. Secondly, without accurate data on facility usage, administrators have no basis for decisions on the allocation of resources, making traffic in and out less efficient and ineffective.
The project's goal is to create reliable, efficient, convenient sign-in and out-of-study facilities, which also allow the university to monitor usage and provide equal access to everyone. When the system is put in place, students and faculty will be able to know what the accurate usage of the facility is and this will help them have a better time in management.
The project will concern designing and building the attendance tracking system for the university libraries as well as study rooms. The system will be designed to be usable and easily incorporated into the university systems that already exist. The attendance data will be collected using the QR codes data collection method which is one of the data collection techniques that includes barcodes, face-recognition, RFID, or biometrics. QR code is a great emerging technology that can be applied to many problems. The chosen technology is relatively fast, less costly, and easy to implement.
This application utilizes QR-code technology and object detection to efficiently track student attendance in university study facilities. Below is a detailed explanation of how the system works.
The system generates unique QR codes for each student containing essential details such as the student’s reference number (or index number). These details can be entered manually through the application interface. Once generated, the QR code can either be emailed to the student or printed for easy scanning during clock-in and clock-out. The QR code is reusable for multiple attendance checks, eliminating the need for frequent re-generation.
The system administrator connects to active cameras available on the computer running the application. The system updates and syncs the list of available cameras to ensure proper functionality. Once updated, the administrator selects a camera for scanning QR codes. Image processing techniques and object detection are employed to scan and decode the QR code accurately.
Upon scanning the QR code, the system decodes it to extract the student’s reference number or index number. The system then contacts an online API to retrieve the student's full details. The retrieved data is saved locally to optimize performance and reduce reliance on the API during future scans. Attendance is automatically recorded as soon as the student’s details are retrieved, accompanied by an audible beep indicating the attendance has been logged. The beep’s frequency and duration are configurable.
To further automate the system, the administrator can set clock-in and clock-out times to switch at regular intervals. This eliminates manual intervention, streamlining the process for both administrators and students.
In cases where QR codes need to be generated for hundreds of students, the system allows administrators to upload a CSV file containing student data. This bulk upload feature enables the automatic generation of QR codes for large batches of students, saving time and effort.
Below are sample rest endpoints needed by the application to retrieve the student details for the first time. No matter the format of the endpoints they should always end with a reference as this is been replaced with the actual reference number of the student.
{ "details": "https://app-commons.onrender.com/student/record/reference", "image": "http://localhost/api/v1/student/image/reference", "endpoint": "RESTAPI" }
The details endpoint should return a JSON of the format below.
{ "firstname": "John", "othername": "Michael", "lastname": "Doe", "reference": "REF12345", "index": "INDEX001", "nationality": "American", "college": "Engineering", "category": "Undergraduate", "gender": "Male", "disabled": "No", "department": "Computer Science", "faculty": "Science and Technology", "validity": "2024-12-31" }
The image endpoint should return a JSON of the format below.
{ "image": "https://via.placeholder.com/150", }
Where the application files are kept
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There are no models linked
There are no datasets linked
