Attendance Alerts – Timely Notifications for Late Arrivals

Abstract

The Attendance Alert system is an advanced attendance management solution designed to streamline and enhance the efficiency and educational institutions. Leveraging facial recognition technology, this system automates the process of identifying students and recording their attendance, eliminating the need for manual entry and reducing human error. At its core lies a sophisticated facial recognition algorithm that analyses images captured by a camera to recognize and verify student identities. Additionally, the Attendance Alert system incorporates an email notification feature, which proactively communicates a student's attendance status directly to them, fostering a line of communication between the institution and students. The system prioritizes simplicity and ease of use. It requires minimal hardware setup, consisting of a standard camera and a device capable of running the facial recognition software. The software itself is built using widely accessible programming languages and libraries, making it cost-effective and easily maintainable. Furthermore, the system offers the capability to generate customized reports for analyzing attendance trends and patterns. These reports provide valuable insights for administrators and educators, informing decisions related to curriculum planning, student engagement, and resource allocation. The Attendance Alert system is a modern, reliable, and user-friendly solution that streamlines the attendance management process in educational settings. Its integration of facial recognition technology, automated reporting tools, and attendance status notification positions it as a valuable asset for any institution seeking to improve its attendance tracking methods

Authors and Affiliations

K Gopala Reddy, S Bhanu Tejaswini, B Ramanjaneyulu, P Arun Sai, S Vijaya Lakshmi

Keywords

Related Articles

Extracting Audio Summaries using ML Techniques

In a world with an ever-expanding array of audio content, ranging from podcasts and lectures to conference calls and interviews, the ability to efficiently extract key information from these recordings has become paramou...

Detecting Botnet Victims using ML

Botnets are one of the most devasting cybersecurity threats to modern organizations. A botnet is a distributed network of compromised devices that is leveraged to perform various activities related to malicious operation...

Benefits and Difficulties of Student-Generative Artificial Intelligence Collaboration in Programming Learning: An Empirical Case Study

Conversational generative artificial intelligence Gen AI is sometimes viewed as a two-edged sword that could result in learning that is only superficial. We created and implemented a programming course that emphasizes st...

Custom Learning Management System for an Institution

This paper explains how a custom Learning Management System (LMS) can improve the learning and teaching experience in educational institutions. An LMS is an online platform where students and teachers can connect, share...

Predicting the Recurrence of Gastric Cancer using Machine Learning

Gastric cancer, also known as stomach cancer, is a type of cancer that originates in the cells lining the stomach. The stomach is a vital organ in the digestive system, responsible for breaking down food and aiding in th...

Download PDF file
  • EP ID EP747899
  • DOI https://doi.org/10.46501/IJMTST1009020
  • Views 64
  • Downloads 0

How To Cite

K Gopala Reddy, S Bhanu Tejaswini, B Ramanjaneyulu, P Arun Sai, S Vijaya Lakshmi (2024). Attendance Alerts – Timely Notifications for Late Arrivals. International Journal for Modern Trends in Science and Technology, 10(9), -. https://www.europub.co.uk/articles/-A-747899