A review paper on Attendance Tracking System using Cloud Computing

Year : 2024 | Volume :11 | Issue : 02 | Page : –
By

Abhishek Sharma

Divyanshi Choudhary

Ashish Kumar Prajapati

Aditya Mishra

Ankit Kumar

Farhan Khan

  1. Assistant Professor Department of Computer Science and engineering, Poornima College of Engineering, Jaipur, Rajasthan India
  2. Student Department of Computer Science and engineering, Poornima College of Engineering, Jaipur Rajasthan India
  3. Student Department of Computer Science and engineering, Poornima College of Engineering, Jaipur Rajasthan India
  4. Student Department of Computer Science and engineering, Poornima College of Engineering, Jaipur Rajasthan India
  5. Student Department of Computer Science and engineering, Poornima College of Engineering, Jaipur Rajasthan India
  6. Student Department of Computer Science and engineering, Poornima College of Engineering, Jaipur Rajasthan India

Abstract

Attendance monitoring systems are critical in educational institutions and organizations for maintaining accurate records of student or staff attendance. In contrast, traditional methods frequently rely on manual processes, which are not only time-consuming but also susceptible to errors. To overcome these issues, this research article suggests an innovative Attendance Tracking System based on Cloud Computing and Artificial Intelligence (AI). The technology uses powerful AI algorithms for facial recognition, allowing for automated attendance tracking without the need for user involvement. Using cloud computing infrastructure, the system effectively saves and processes attendance data, ensuring scalability and access. The proposed system’s key features include real-time attendance tracking, easy integration with current infrastructure, and strong security measures to secure sensitive data. Furthermore, the system includes complete reporting capabilities, allowing administrators to monitor attendance trends and find areas for improvement. This Attendance Tracking System provides a dependable and effective solution for attendance tracking by combining AI and clou d computing technologies, with the ability to increase productivity, streamline administrative procedures, and reduce mistakes. An attendance tracking system is an essential tool for organizations to monitor and manage the presence of their employees, students, or members. Traditionally, attendance tracking has been a manual process involving paper logs or standalone software solutions.
However, with the rise of cloud computing, these systems have become more efficient, scalable, and accessible. A cloud-based attendance tracking system utilizes internet and cloud services to offer a seamless and robust solution for managing attendance.

Keywords: Attendance Monitoring, Cloud Computing, Artificial Intelligence, Facial Recognition, Automated Tracking

[This article belongs to Recent Trends in Parallel Computing(rtpc)]

How to cite this article: Abhishek Sharma, Divyanshi Choudhary, Ashish Kumar Prajapati, Aditya Mishra, Ankit Kumar, Farhan Khan. A review paper on Attendance Tracking System using Cloud Computing. Recent Trends in Parallel Computing. 2024; 11(02):-.
How to cite this URL: Abhishek Sharma, Divyanshi Choudhary, Ashish Kumar Prajapati, Aditya Mishra, Ankit Kumar, Farhan Khan. A review paper on Attendance Tracking System using Cloud Computing. Recent Trends in Parallel Computing. 2024; 11(02):-. Available from: https://journals.stmjournals.com/rtpc/article=2024/view=0

References

[1]. Smitha PS. Afshin Dept. of Computer Science and Engineering, Yenepoya Institute of Technology, Moodbidri. India International Journal of Engineering Research & Technology (IJERT). 2020 May;9(05).

[2]. Mary IM, Goldwin RJ, Mathivarshini TP, Nandhini NM. Detecting Hostellers Using Face Recognition. In2022 International Conference on Data Science, Agents & Artificial Intelligence (ICDSAAI) 2022 Dec 8 (Vol. 1, pp. 1-5). IEEE.

[3]. Chintalapati S, Raghunadh MV. Illumination, expression and occlusion invariant pose-adaptive face recognition system for real-time applications. arXiv preprint arXiv:1403.1362. 2014 Mar 6.

[4]. Tirlotkar P, Chitrakathi K, Rohit Jadhav R, Khamkar A, Mishra M. Smart Attendance System Using Image Processing. International Journal Of Engineering Research & Technology (IJERT) ICIATE–. 2017;5(01):2017.

[5]. Kar N, Debbarma MK, Saha A, Pal DR. Study of implementing automated attendance system using face recognition technique. International Journal of computer and communication engineering. 2012 Jul 1;1(2):100-3.

[6]   Yang S, Song Y, Ren H, Huang X. An automated student attendance tracking system based on voiceprint and location. In2016 11th International Conference on Computer Science & Education (ICCSE) 2016 Aug 23 (pp. 214-219). IEEE.

[7]  Parhi M, Roul A, Ghosh B, Pati A. Ioats: An intelligent online attendance tracking system based on facial recognition and edge computing. International Journal of Intelligent Systems and Applications in Engineering. 2022 May 27;10(2):252-9.

[8]. Chiang TW, Yang CY, Chiou GJ, Lin FY, Lin YN, Shen VR, Juang TT, Lin CY. Development and evaluation of an attendance tracking system using smartphones with GPS and NFC. Applied Artificial Intelligence. 2022 Dec 31;36(1):2083796.

[9]. Singh A, Bhatt S, Gupta A. Automated attendance system with face recognition. International Journal of Engineering Applied Sciences and Technology. 2021;5:12.

[10].  Krisha CS, Sumanth N, Prasad CR. RFID based student monitoring and attendance tracking system. In2013 Fourth International Conference on Computing, Communications and Networking Technologies (ICCCNT) 2013 Jul 4 (pp. 1-5). IEEE.

[11]. Sultana S, Enayet A, Mouri IJ. A smart, location based time and attendance tracking system using android application. International Journal of Computer Science, Engineering and Information Technology (IJCSEIT). 2015 Feb;5(1):1-5.

[12]. Nadhan AS, Tukkoji C, Shyamala B, Dayanand Lal N, Sanjeev Kumar AN, Mohan Gowda V, Adhoni ZA, Endaweke M. Smart attendance monitoring technology for industry 4.0. Journal of Nanomaterials. 2022;2022(1):4899768.

[13]. Bhattacharya S, Nainala GS, Das P, Routray A. Smart attendance monitoring system (SAMS): a face recognition based attendance system for classroom environment. In2018 IEEE 18th international conference on advanced learning technologies (ICALT) 2018 Jul 9 (pp. 358-360). IEEE..

[14]. Ding C, Wang K, Wang P, Tao D. Multi-task learning with coarse priors for robust part-aware person re-identification. IEEE Transactions on Pattern Analysis and Machine Intelligence. 2020 Sep 18;44(3):1474-88.

[15]. Cao F, Wang M, Wang K. The classroom attendance management system of face recognition based on LBS. In2018 5th International Conference on Education, Management, Arts, Economics and Social Science (ICEMAESS 2018) 2018 Nov (pp. 955-960). Atlantis Press.

[16] Younas M, Jawawi DN, Mahmood AK, Ahmad MN, Sarwar MU, Idris MY. Agile software development using cloud computing: A case study. IEEE Access. 2019 Dec 25;8:4475-84.

[17] Yang H, Han X. Face recognition attendance system based on real-time video processing. IEEE Access. 2020 Jul 10;8:159143-50.

[18] Palanivel K. Emerging technologies to smart education. Int. J. Comput. Trends Technol. 2020;68(2):5-16.

[19] Sharma A, Singh UK. Investigation of Cloud Computing Security Issues & Challenges. In3rd International Conference on Integrated Intelligent Computing Communication & Security (ICIIC 2021) 2021 Sep 13 (pp. 445-453). Atlantis Press.

[20] Shah NU, Naeem SB, Bhatti R. Emerging Trends of data management and data analytical practices in academic libraries: A theoretical lens. Journal of Information and Computational Science. 2020 Apr;10(4):545-56.


Regular Issue Subscription Review Article
Volume 11
Issue 02
Received May 6, 2024
Accepted June 25, 2024
Published July 9, 2024

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