CFP last date
20 January 2025
Call for Paper
February Edition
IJCA solicits high quality original research papers for the upcoming February edition of the journal. The last date of research paper submission is 20 January 2025

Submit your paper
Know more
The week's pick
Responsive image
SFLA-Based Line Balancing and Task Optimization in Master-Slave Controlled Hanger Transportation Systems for Garment Production

Duc Hoang Nguyen
Random Articles
Reseach Article

RFID Based Exam Hall Maintenance System

Published on None 2011 by Parvathy A, Venkata Rohit Raj, Venumadhav, Manikanta
journal_cover_thumbnail

Artificial Intelligence Techniques - Novel Approaches & Practical Applications
Foundation of Computer Science USA
AIT - Number 4
None 2011
Authors: Parvathy A, Venkata Rohit Raj, Venumadhav, Manikanta
f112d734-3313-4083-95b3-159cb5dff8d4

Parvathy A, Venkata Rohit Raj, Venumadhav, Manikanta . RFID Based Exam Hall Maintenance System. Artificial Intelligence Techniques - Novel Approaches & Practical Applications. AIT, 4 (None 2011), 31-37.

@article{
author = { Parvathy A, Venkata Rohit Raj, Venumadhav, Manikanta },
title = { RFID Based Exam Hall Maintenance System },
journal = { Artificial Intelligence Techniques - Novel Approaches & Practical Applications },
issue_date = { None 2011 },
volume = { AIT },
number = { 4 },
month = { None },
year = { 2011 },
issn = 0975-8887,
pages = { 31-37 },
numpages = 7,
url = { /specialissues/ait/number4/2847-228/ },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Special Issue Article
%1 Artificial Intelligence Techniques - Novel Approaches & Practical Applications
%A Parvathy A
%A Venkata Rohit Raj
%A Venumadhav
%A Manikanta
%T RFID Based Exam Hall Maintenance System
%J Artificial Intelligence Techniques - Novel Approaches & Practical Applications
%@ 0975-8887
%V AIT
%N 4
%P 31-37
%D 2011
%I International Journal of Computer Applications
Abstract

Seating Arrangement of students during examinations is distributed. Students face difficulties as they have to scrounge for their examination hall numbers and seating arrangement while they are wits end. An innovation which could aid the students in finding their exam halls and seats would be welcoming and very rewarding. This paper “RFID BASED EXAM HALL MAINTENANCE SYSTEM”, presents a modernized method of examination hall management. It is possible for a student to identify the particular exam hall from any other hall, when they swipe RFID card in a card reader located there. This helps them to identify the floor or get directions to their respective halls without delays. The card reader is provided at the entrance of the building, if the students enters wrongly a buzzer alarm sets off, otherwise the room number is displayed on the LCD, connected to controller.

References
  1. Han, J., Kamber, M. 2001: Data mining: Concepts and Techniques. Morgan Kaufmann Publishers, San Francisco.
  2. Fayyad U.,Piatetsky-Shapiro G., Smyth P., and Uthrusamy R 9Eds.) 1996: Advances in Knowledge Discovery and Data Mining. AAAI press, Menlo Park, CA, ISBN:0-262-56097-6, pages:611.
  3. Takeaki Uno, Masashi Kiyomi, Hiroki Arimura: LCM ver 2. Efficient mining algorithms for Frequent/ closed/ maximal itemsets.
  4. Agrawal R. and Srikant R. 1994: Fast algorithms for mining association rules in large databases. In Proc. 20th VLDB, pages 478-499.
  5. Sarasere A.,Omiecinsky E., and Navathe S. 1995 : An efficient algorithm for mining association rules in large databases. In Proc. 21st VLDB, pages 432-444.
  6. Toivonen H. L 1996: Sampling large databases for association mining rules. In Proc. 22nd VLDB, pages 134-145.
  7. Hanbing Liu and Baisheng Wang 2007: An association rule mining algorithm based on a Boolean matrix. Data Science Journal, Volume 6, Supplement, 9.
  8. Shivanandam, S. N., Sumathi, S., Deepa, S. N.: “Introduction to Neural Network using MATLAB 6.0. TATA Mc.Graw Hill.”
  9. R. Ramachandran 1998: Optoelectronic Implemenration of Neural Networks. Use of Optics in Computing. RESONANCE.
  10. I. Saxena, P. Moerland, E. Fiesler, A.R. Pourzand, and N. Collings: An optical Thresholding Perceptron with Soft Optical Threshold.
  11. Tenanbaum M., Augenstein M.J., Langsam Y.: “Data Structures using C and C++ : Prentice-Hall India, Edition 2.”
  12. Pujari A.K.: “Data Mining:Techniques: Universities Press.”
  13. Mos, Evert C.: Optical Neural Network based on Laser Diode Longitudinal Modes.
  14. D. Bhatnagar, K.R. Pardasani. 2008: Mining Patterns Using Optical Neural networks: In Proc. International Conference on BUSINESS DATA MINING.
  15. D. Bhatnagar, A. K. Saxena 2011: An Optical Neural Network Model for mining Frequent Itemsets in Large Databases, Indian Journal of Computer Science and Engineering, Vol 2, No. 2, pages 212-217.
  16. I. Saxena, E. Fiesler: An adaptive Multilayer Optical Neural Network Design, IDIAP TR-94-04.
  17. R. Rojas 1996: Neural Networks. Springer-Verlag, Berlin.
  18. M. T. Hagan, H. B. Demuth, M. H. Beale: Neural Network Design
  19. E. Horward, Michel, Abdul A. S. Awwal: Analysis and Evaluation of Electro-Optic Artificial Neural Network Performance in the Presence of Non-Ideal Components.
  20. Nikolay N. Evtihiev, Rostislav S. Starikov, Boris N. Onyky, Vadim V. perepelitsa, Igor B. Scherbakov 1994: Experimetal investigation of the performance of the optical two-layer neural network, SPIE Vol. 2430 Optical Neural Networks, pages 189-197.
  21. Damien Woods, Thomas J. Naughton 2009: Optical Computing.
Index Terms

Computer Science
Information Sciences

Keywords

RFID AT89S52 Microcontroller