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
- R Karthika, Maria Toms, S R Aadrash, P U Prabath, InsightAI: Bridging Natural Language and Data Analytics , International Journal on Emerging Research Areas: Vol. 4 No. 1 (2024): IJERA
- Melvin Tom Varghese, Joseph V S, Kevin Chacko, Johns Benny, Tintu Alphonsa Thomas, Crop Recommendation System using Machine Learning and IoT , International Journal on Emerging Research Areas: Vol. 4 No. 1 (2024): IJERA
- Fabeela Ali Rawther, Akhil P Dominic, Alan James, Christy Chacko, Elena Maria Varghese, Early Detection of Attention Deficiency Using ML , International Journal on Emerging Research Areas: Vol. 3 No. 1 (2023): IJERA
- Jefrin Siby Mathew, Joyal Joseph, Roshik George, Tinu Rose Thottungal , Honey Joseph, Multiple Disease Detection using Machine Learning , International Journal on Emerging Research Areas: Vol. 3 No. 1 (2023): IJERA
- Arya Raj S, R Gopika Krishnan, Drishya Das, Rohith R, Jocelyn Ann Joseph, Personality Profiling Using CV Analysis , International Journal on Emerging Research Areas: Vol. 4 No. 1 (2024): IJERA
- Dr. Indu John, Gauri Santhosh, Jesna Susan Reji, Abdul Musawir, Glady Prince, Detection of Autism Spectrum Disorder in Toddlers using Machine Learning , International Journal on Emerging Research Areas: Vol. 4 No. 1 (2024): IJERA
- Kaveri S, Pooja Satheesh, Kesiya Susan John, Reubel K Wilson, Dr. Jacob John, Predictive Maintenance of Machines Using IoT and Machine Learning , International Journal on Emerging Research Areas: Vol. 4 No. 2 (2024): IJERA
- Betzy Babu Thoppil, Anugrah Premachandran, Annapoorna M, Ashwin Mathew Zachariah, Bala Susan Jacob, Advanced Sensor-Based Landslide and Earthquake Detection and Alert System Utilizing Machine Learning and Computer Vision Technologies , International Journal on Emerging Research Areas: Vol. 4 No. 2 (2024): IJERA
- Khalid Hareef, Neenu, M N Sulthana , Nesmi Siddique, Number Plate Detection in Fog and Haze , International Journal on Emerging Research Areas: Vol. 3 No. 1 (2023): IJERA
- Jyothis Joseph, Angeetha Raju, Aparna Santhosh, Ashitha Jenish, K S Minu, Survey on Fake Profile Detection in Social Media , International Journal on Emerging Research Areas: Vol. 3 No. 1 (2023): IJERA
You may also start an advanced similarity search for this article.