Smart Attend Insights
Abstract
SmartAttend Insights automates attendance tracking with the use of deep learning algorithms and cutting-edge face
detection technology. In addition to offering real-time information
and warning students when attendance drops below 75%, it also
promotes communication by texting parents and tutors about
absence lists. In order to meet attendance goals, students can
estimate the number of class days required, and reminders
help to guarantee that institutional policies are followed. In
order to create study groups that include a mix of students
from different academic backgrounds, deep learning algorithms
also evaluate academic performance. This promotes collaborative
learning environments. This ground-breaking solution improves
performance, accountability, and engagement for the benefit of
parents, teachers, students, and institutions.
Index Terms—Facial recognition technology, attendance tracking, deep learning, Automated attendance tracking, Student
engagement
Keywords:
deep learning, facial recognition, automated attendancePublished
Issue
Section
License
Copyright (c) 2024 International Journal on Emerging Research Areas

This work is licensed under a Creative Commons Attribution 4.0 International License.
All published work in this journal is licensed under the Creative Commons Attribution 4.0 International License (CC BY 4.0). This license permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
How to Cite
Similar Articles
- Alan K George, Arpita Mary Mathew, Asin Mary Jacob, Elizabeth Antony, Shiney Thomas, Lung Cancer Subtype Classification Using Deep Learning Models , International Journal on Emerging Research Areas: Vol. 5 No. 1 (2025): IJERA
- Arun Robin, Tijo Thomas Titus, Ms. Minu Cherian, Improved Handwritten Digit Recognition Using Deep Learning Technique , International Journal on Emerging Research Areas: Vol. 3 No. 2 (2023): IJERA
- Lis Jose , Achyuth P Murali, Christin Joseph Shaji, Christy Kunjumon Peter , Multiple Detection and Diagnosis of Skin Diseases using CNN , International Journal on Emerging Research Areas: Vol. 4 No. 1 (2024): IJERA
- Anna N Kurian, Aravind R Nair, Athira Pradeep, Ben V Sajeesh, Traffic Violation Detection Using Machine Learning: A Comprehensive Study , International Journal on Emerging Research Areas: Vol. 5 No. 1 (2025): IJERA
- Jincy Lukose, Anita Ann Joseph, Meenakshy BR , Nevin Siby, Rosaine P Lal , ENHANCED PNEUMONIA DETECTION IN CHEST X-RAYS USING ATTENTION AND FNMS , International Journal on Emerging Research Areas: Vol. 5 No. 1 (2025): IJERA
- Evelyn Susan Jacob, Joel John, Raynell Rajeev, Steve Alex , Syam Gopi , Malware Classification using Image Analysis , International Journal on Emerging Research Areas: Vol. 5 No. 1 (2025): IJERA
- Raihana Rasaldeen, Stefi Marshal Fernandez, Irin Rose Jaison, Ria Mariam , A Comparative Study of AI Models and AI-Based Approaches for Evaluating Subjective Answers in Exams , International Journal on Emerging Research Areas: Vol. 5 No. 1 (2025): IJERA
- Shiney Thomas, Elsa George, Alphonsa Francis, Anna Job, Ann Maria James, Wildlife Detection And Recognition Using YOLO V8 , International Journal on Emerging Research Areas: Vol. 4 No. 2 (2024): IJERA
- Ansamol Varghese, Anandhu Anoj, Angel Thomas, Deepta K Sunny, Emil Thomas, TrueNews-AI Powered Detection of Manipulated Text and Images , International Journal on Emerging Research Areas: Vol. 5 No. 1 (2025): IJERA
- George P Kurias, Gokul Krishna AU, Jifith Joseph, Sharunmon R, Linsa Mathew, A Review of Methodologies for Detecting Missing and Wanted People Using Machine Learning and Video Surveillance , International Journal on Emerging Research Areas: Vol. 4 No. 2 (2024): IJERA
You may also start an advanced similarity search for this article.
