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International Journal of Trend in Scientific Research and Development (IJTSRD)
Special Issue on Emerging Trends and Innovations in Web-Based Applications and Technologies
Available Online: www.ijtsrd.com e-ISSN: 2456 – 6470
Smart Attendance Systems: An Evaluation of
FaceAttend and Its Role in Modernizing College Attendance
2
Toshik Rahangdale , Om Pardhi , Prof. Anupam Chaube
1
3
1,2,3 Department of Science and Technology,
1,2 G H Raisoni Institute of Engineering and Technology, Nagpur, Maharashtra, India
3 G H Raisoni College of Engineering and Management, Nagpur, Maharashtra, India
ABSTRACT Attendance tracking is a crucial aspect of academic
The modernization of college attendance systems has administration, influencing student performance, resource
gained momentum with the advent of smart technologies. allocation, and compliance with institutional policies.
Among these, FaceAttend, a facial recognition-based Conventional methods often suffer from issues such as time
attendance solution, has emerged as a promising tool. This consumption, human error, and fraudulent entries. Smart
paper evaluates the functionality, advantages, challenges, attendance systems, leveraging advanced technologies like
and implications of FaceAttend in the context of higher facial recognition, offer a promising solution. FaceAttend, a
education. Through a comprehensive analysis, we explore leading product in this domain, claims to provide seamless,
how this technology aligns with the objectives of efficiency, automated, and accurate attendance tracking.
accuracy, and security while considering ethical and
technical concerns. 2. Overview
FaceAttend is an AI-driven attendance tracking system that
In colleges, universities, organizations, schools, and offices, uses facial recognition to identify and record students'
taking attendance is one of the most important tasks that presence in classrooms. The system employs machine
must be done on a daily basis. learning algorithms, cloud computing, and mobile
integration to provide real-time attendance data. Key
The traditional methods of tracking student attendance in
features of FaceAttend include:
colleges, such as manual roll calls and sign-in sheets, are
becoming increasingly inefficient in the digital age. This Automated Attendance Recording: Eliminates manual
research paper explores the potential of smart attendance processes by capturing students' faces through cameras.
systems, with a focus on FaceAttend, a facial recognition- Real-time Monitoring: Provides instant attendance
based attendance solution. The study evaluates
reports to administrators and faculty.
FaceAttend's features, benefits, challenges, and its overall
impact on modernizing college attendance systems. Integration with Institutional Systems: Seamlessly
connects with learning management systems (LMS) and
KEYWORDS: Attendance, Face Identification, OpenCV, Local student information systems (SIS).
Binary Pattern Histogram (LBPH), Training and Recognition,
Database Security Measures: Ensures data privacy with
encryption and access control.
1. INTRODUCTION 3. Background and Related Work
Attendance management in educational institutions plays a Evolution of Attendance Systems
critical role in monitoring student engagement and ensuring Historically, attendance management relied on manual
compliance with institutional policies. Traditional methods, processes, which were inefficient and error-prone.
such as manual roll calls and swipe cards, are often time- Technological advancements introduced biometric systems,
consuming and prone to inaccuracies. Smart attendance such as fingerprint scanners and RFID-based solutions,
systems, leveraging advanced technologies like facial which improved reliability. Recent developments in artificial
recognition, offer an innovative alternative. intelligence (AI) have facilitated the adoption of facial
recognition systems, which promise hands-free and seamless
FaceAttend, a cutting-edge facial recognition system, attendance tracking.
automates attendance tracking by capturing and analyzing
student images. This paper evaluates the effectiveness of Overview of FaceAttend
FaceAttend in transforming attendance management, FaceAttend utilizes AI-powered facial recognition algorithms
addressing its technological framework, operational benefits, to identify students in real-time. Integrated with institutional
and potential drawbacks. databases, it verifies student identities against pre-registered
images and records attendance instantly. Key features
Face recognition is defined as a biometric method in which
include high accuracy rates, scalability, and compatibility
identification of an individual is performed by comparing with existing management systems.
real-time capture image with stored images in the database
of that person.
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