MACHINE LEARNING AND BLOCKCHAIN-BASED REAL-TIME FACIAL RECOGNITION ATTENDANCE SYSTEM

Main Article Content

Dr. V. NAGAGOPIRAJU
DIVVELA MANI DEEPAK
MUNGAMURI VENKATA VINAY
ELCHURI ARUN KUMAR
KUKKALA SUPRIYA

Abstract

In a vast majority of fields, the use of facial recognition for authentication is expanding. In this information age, authentication has become vital, and the need for faster and more secure methods of user authentication has been on the rise. The introduction of image processing technologies such as OpenCV has increased society’s reliance on face recognition. Using blockchain, information could be stored in blocks throughout the blockchain network. Blockchain is an extremely secure means for storing and protecting data from intruders. It is a highly disruptive technology that has the ability to alter every plane of society. This paper intends to implement opensource computer vision (OpenCV) to construct a facial detection model that will be employed in a blockchain-secured Attendance Monitoring System. It will not only automate the attendance procedure but also give the system unassailable security. This system will take a live video feed from a camera using OpenCV and identify the faces of students and record their attendance along with the entry time. The data will be kept in a distributed way over the blockchain network that will be accessible to everyone, but data cannot be manipulated.

Downloads

Download data is not yet available.

Metrics

Metrics Loading ...

Article Details

How to Cite
NAGAGOPIRAJU, D. V. ., DEEPAK, D. M., VINAY, M. V. ., KUMAR, E. A., & SUPRIYA, K. . (2024). MACHINE LEARNING AND BLOCKCHAIN-BASED REAL-TIME FACIAL RECOGNITION ATTENDANCE SYSTEM. Turkish Journal of Computer and Mathematics Education (TURCOMAT), 15(1), 133–137. https://doi.org/10.61841/turcomat.v15i1.14554
Section
Research Articles

References

Md. Shakil and RabindraNath Nandi, “Attendance Management System for Industrial Worker using

FingerPrintScanner”, in Global Journal of Computer Science and Technology Graphics and Vision,Feb 2018.

Siddharth Rajput, Archana Singh, Smiti Khurana, Tushar Bansal, SanyuktaShreshtha,”Blockchain Technology

and Cryptocurrenices”,06 February 2019.

H.H. Soliman, et al,“A comparative performance evaluation of intrusion detection techniques for hierarchical

wireless sensor networks”, Egyptian Informatics Journal (2012) 13 Jan 2020.

Naman Gupta, Purushottam Sharma, Vikas Deep, Vinod Kumar Shukla, ”Automated Attendance System Using

OpenCV”, June 4-5, 2020.

Hasna Ardina,I Gusti Bagus Baskara Nugraha,”Design of A Blockchainbased Employee Attendance System”,19

Nov 2019

Jingyao Tu, Zhenhua Duan(B), Cong Tian(B), Nan Zhang(B), and Ying Wu ,”A Blockchain Implementation of

an Attendance Management System”,09 February 2019.

Naman Gupta,Purushottam Sharma,Vikas Deep,Vinod Kumar Shukla,”Automated Attendance System Using

OpenCV”,June 4-5, 2020.

LIXIANG LI1, XIAOHUI MU1, SIYING LI ,HAIPENG PENG”A Review of Face Recognition”,Technology”21

July 2020.

Setia Budi, Oscar Karnalim, Erico D. Handoyo, Sulaeman Santoso, Hapnes Toba,Huyen Nguyen†, Vishv Malhotra

”IBAtS -” Image Based Attendance System: A Low Cost Solution to Record Student Attendance in a Classroom”, 10

December 2018.

Muthunagai, Muruganandhan, Rajasekaran.P,”Classroom Attendance Monitoring Using CCTV”,10 July 2020.

Kaneez Bhatti, Laraib Mughal, Faheem Khuhawar, Sheeraz Memon, ”Smart Attendance Management System

Using Face Recognition”, 31 July 2019.

Sudhir Bussa, Ananya Mani, Shruti Bharuka, Sakshi Kaushik, ”Smart Attendance System using OpenCV based

on Facial Recognition”, 11 March 2020.

Samridhi Dev, Tushar Patnaik, ”Student Attendance System using Face Recognition”, 10-12 September 2020.

A Arjun Raj, Mahammed Shoheb, K Arvind, K S Chethan, ”Face Recognition Based Smart Attendance System”,

-19 June 2020.

Kolipaka Preethi, Swathy Vodithala, ”Automated Smart Attendance System Using Face Recognition”, 06-08

May 2021.