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

PIC Microcontroller and PC based Multi Sensors Artificial Intelligent Technique for Gas Identification

by S.n.divekar, S.n.pawar
journal cover thumbnail

International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 121 - Number 14
Year of Publication: 2015
Authors: S.n.divekar, S.n.pawar
10.5120/21611-4836

S.n.divekar, S.n.pawar . PIC Microcontroller and PC based Multi Sensors Artificial Intelligent Technique for Gas Identification. International Journal of Computer Applications. 121, 14 ( July 2015), 34-38. DOI=10.5120/21611-4836

@article{ 10.5120/21611-4836,
author = { S.n.divekar, S.n.pawar },
title = { PIC Microcontroller and PC based Multi Sensors Artificial Intelligent Technique for Gas Identification },
journal = { International Journal of Computer Applications },
issue_date = { July 2015 },
volume = { 121 },
number = { 14 },
month = { July },
year = { 2015 },
issn = { 0975-8887 },
pages = { 34-38 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume121/number14/21611-4836/ },
doi = { 10.5120/21611-4836 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T23:08:27.160010+05:30
%A S.n.divekar
%A S.n.pawar
%T PIC Microcontroller and PC based Multi Sensors Artificial Intelligent Technique for Gas Identification
%J International Journal of Computer Applications
%@ 0975-8887
%V 121
%N 14
%P 34-38
%D 2015
%I Foundation of Computer Science (FCS), NY, USA
Abstract

PIC microcontroller & PC based gas sensing system is presented in this project. The analysis presented here depends on thin film metal oxide gas sensors TGS 822, TGS 813, TGS 2600, MQ6 and MQ7. The differences in the steady state performance among their sensors are used for improving their selectivity and sensitivity, while the combination of gas sensors permits success in gas classification problems. In the presented approach the gas sensors are embedded into a chamber with a heating system. Different types of gases are used, such as, Methane, Carbon monoxide and LPG to pass through this chamber with different concentrations, different operating temperatures and different load resistances. Sets of data collected to detect the gas sensitivity for each sensor depending on the output voltage in relation to temperatures, concentration of gases and variable resistances for each sensor. In this project, novel approach, based on the ANN technique, used for the gas identification. The identification is done directly from the data driven from the microcontroller by using ANN trained model. The results of the ANN are shown to provide gas identification according to variation in different parameters, such as gas concentrations, variation in sensor's resistance and output voltage of sensor at different temperatures and to indicate that the selection of different gases is possible, based on microcontroller, which improves sensitivity and selectivity with high accuracy and reliability.

References
  1. Imon Morsi, "A Microcontroller Based on Multi Sensors Data Fusion and Artificial Intelligent Technique for Gas Identification" The 33rd Annual Conference of the IEEE Industrial Electronics Society (IECON)
  2. Santiago Marco, Arturo Ortega, Antonio Pardo, and Josep Samitier, "Gas Identification with tin Oxide sensor Array and self- Organizing, Maps: Adaptive correction of sensor drifts. IEEE Transactions on Instrumentation and Measurements. Vol. 47, No. 1, February 1998.
  3. Jan Zakrzewski, Wieslaw Domanski, Petros chaitas, and Theodore laopoulos, "Improving Sensitivity and Selectivity of Gas Sensors by Temperature Variation", IEEE Transactions on Instrumentation and Measurement, Vol. 55 No. 1. February 2006.
  4. Sofiane Brahim - Belhouari, Amine Bermak, Minghua Shi, Philip C. H, Chan "Fast and Robust gas Identification system using an Integrated Gas Sensor technology and Gaussion Mixture Models", IEEE Sensors Journal, Vol 5, No 6, December 2005.
  5. P. Chaitas, W. Domanski, Th. Laopoulus, J. Zakrzewski "Gas Identification Method by Microcontroller-based Analysis of Two-dimensional Sensors Behavior" IMTC - Instrumentation and Measurement Technology Conference, May 2004.
  6. T. Becker, S. Muhlberger, C. Bosch-v. Braunmuhl, G. Muller, A. Meches, and W. Benecke, "Gas Mixture Analysis Using Silicon Micro-Reactor Systems", Journal of Micro electromechnical systems, Vol, 9, No. 4, December 2000. .
  7. J. B. GUPTA, "Electronic and Electrical measurements and Instrumentation", S. K. Kataria and sons, 2002.
  8. J. Wesley Hines, "Fuzzy and Neural Approaches in Engineering". John Wiley & sons, INC, 1997.
  9. Timothy J. Ross, "Fuzzy logic with Engineering Applications", McGraw-Hill, Inc, 1995
  10. http://www. figarosensor. com/gaslist. html
  11. https://www. sparkfun. com/categories/146
  12. S. Brahdgim Belhouari, A. Bermak, G. Wei, P. C. H. Chan, "Gas Identification Algorithms for micro electronic Gas sensor" IMIC - Instrumentation and Measurement Technology Conference, 2004.
  13. Hanusz Smulko, "The Measurement setup for Gas detection by Resistance Fluctuations of Gas Sensor" IMTC - Instrumentation and Measurement Technology Conference, April 2006.
  14. Muhammad Ali Mazidi, "PIC Microcontroller and Embedded System", Pearson Publication, First Edition, 2008.
  15. Chuck Hellebuyck, "Beginners Guide to Embedded C programming", Create space Publishing Platform, first Edition, 2008.
  16. http://www. microchip. com/downloads/en/DeviceDoc/39582C. pdf
  17. http://www. analog. com/media//technical-documentation/data-sheets/AD5246. pdf
  18. http://in. mathworks. com/help/matlab/matlab_external/getting-started-with-serial-i-o. html.
  19. https://electrosome. com/interfacing-lcd-with-pic-microcontroller-hi-tech-c/
  20. http://embedjournal. com/interfacing-lcd-module-part-1/
  21. Carlos Gershenson "Artificial Neural Network for beginners" In tech Publication, 2008.
  22. Jure Zupan " Introduction to Artificial Neural Network Methods: what they are and how to use them" Acta chimica slovenica conference, 1994.
  23. Andy P. Dedecker, Peter L. M. , Goethals, Wim Gabriels, Niels De Pauw, "Optimization of Artificial Neural Network(ANN) model design for prediction of macro invertebrates in the Zwalm river basin" Science Direct Ecological Modeling Journal, 2004(161-173).
  24. Howard Demuth, Mark Beale "Neural Network tool box" Mathwork user guide Version 4, July 2002.
  25. Mark Hudson Beale, Martin T. Hagan, Howard Demuth "Neural Network Tool Box" Mathwork user guide version 8. 2, March 2014.
  26. Dr. Ali Assi, "Engineering Education and research using MATLAB" In Tech Publication, October 2011.
  27. Primoz Potocnik "Neural Network: Matlab Examples" Neural Network course(practical Examples), 2012.
  28. Anuradha Chug, Ankita Sawhney "The Comparative study of software maintenance forecasting analysis based on backpropagation (NFTOOL & NTSTOOL) and adaptive nuero fuzzy interface system ANFIS" International journal of Advancement in Research Technology, Vol. 2, Issue 5, 2013 (312-319).
  29. Rudra Pratap, "Getting Started with MATLAB", Oxford University Press, Version 7. 8, 2010.
  30. Sang-Hoon Lee, Yan-fangli, Vikram Kapila, "Development of a MATLAB based GUI environment for PIC microcontroller Projects", American Society for Engineering Education Annual Conference, 2004.
  31. Amod Kumar, "GUI based Device Controller using MATLAB", IJSER International Journal, Vol-4, Issue-6, June 2013.
Index Terms

Computer Science
Information Sciences

Keywords

Gas detection ANN intelligent sensing Gas sensors.

Powered by PhDFocusTM