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Environmental Scrutinizing System based on Soft Computing Technique

by Dinesh Kumar Saini, Jabar H Yousif
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International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 62 - Number 13
Year of Publication: 2013
Authors: Dinesh Kumar Saini, Jabar H Yousif
10.5120/10143-4952

Dinesh Kumar Saini, Jabar H Yousif . Environmental Scrutinizing System based on Soft Computing Technique. International Journal of Computer Applications. 62, 13 ( January 2013), 45-50. DOI=10.5120/10143-4952

@article{ 10.5120/10143-4952,
author = { Dinesh Kumar Saini, Jabar H Yousif },
title = { Environmental Scrutinizing System based on Soft Computing Technique },
journal = { International Journal of Computer Applications },
issue_date = { January 2013 },
volume = { 62 },
number = { 13 },
month = { January },
year = { 2013 },
issn = { 0975-8887 },
pages = { 45-50 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume62/number13/10143-4952/ },
doi = { 10.5120/10143-4952 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T21:11:43.939577+05:30
%A Dinesh Kumar Saini
%A Jabar H Yousif
%T Environmental Scrutinizing System based on Soft Computing Technique
%J International Journal of Computer Applications
%@ 0975-8887
%V 62
%N 13
%P 45-50
%D 2013
%I Foundation of Computer Science (FCS), NY, USA
Abstract

Artificial intelligent techniques are very much needed to design the environmental monitoring systems. These systems must be smart enough so that all the decisions taken by the system must be accurate. Soft Computing (SC) it is a set of computational methods that attempt to determine satisfactory approximate solutions to find a model for real-world problems. It based on various techniques such as Artificial Neural Networks, Fuzzy Logic and Genetic Algorithms. The aim of this paper is to implement a soft computing technique which is artificial neural network based on Self-Organizing Feature Map (SOFM). SOFM model for monitoring and collecting of the data are real-time and static datasets acquired through pollution monitoring sensors and stations. In the environmental monitoring systems the ultimate requirement is to establish controls for the sensor based data acquisition systems and need interactive and dynamic reporting services. SOFM techniques are used for data analysis and processing. The processed data is used for control system which even feeds to the alarming systems.

References
  1. Acken, A. H. , Lewis, R. : Final Particulate Matter National Ambient Air Quality Standards. ENRLS update 4(15) (2006).
  2. Akyol, D. E. (2004). Applications of neural networks to heuristic scheduling algorithms. Computers and Industrial Engineering, 46, 679-696. http://www. sciencedirect. com/science/article/pii/S036083520400066X.
  3. Abdul-Wahab S. A. , 2005. Monitoring of Air Pollution in the Atmosphere Around Oman Liquid Natural Gas (OLNG) Plant. Journal of Environmental Science and Health, Part A: Toxic/Hazardous Substances and Environmental Engineering. Vol. 40, No. 3, pp. 559-570.
  4. Bonissone, P (2002). Hybrid Soft Computing for Classification and Prediction Applications. Conferencia Invitada. 1st International Conference on Computing in an Imperfect World (Soft-Ware 2002), Belfast. DOI: 10. 1007/3-540-46019-5_28. http://en. wikipedia. org/wiki/Cyclone_Gonu
  5. Fayyad, U. : Mining Database: Towards Algorithms for Knowledge Discovery. IEEE Techn. Bulletin Data Engineering 21(1), 1998.
  6. Galhardas, H. ; Florescu, D. ; Shasha, D. ; Simon, E. : AJAX: An Extensible Data Cleaning Tool. Proc. ACM SIGMOD Conf. , p. 590, 2000.
  7. Garcia, A. ; Silva, V. ; Lucena, C. ; Milidiú, R. An Aspect-Based Approach for Developing Multi-Agent Object-Oriented Systems. Simpósio Brasileiro de Engenharia de Software, Rio de Janeiro, Brazil, October 2001.
  8. Giorgio Corani,"Air quality prediction in Milan:feed-forward neural networks, pruned neural networks and lazy learning" ,Ecological Modelling Volume 185, Issues 2-4, 10 July 2005, Pages 513-529
  9. Jabar H. Yousif, "INFORMATION TECHNOLOGY DEVELOPMENT", LAP LAMBERT Academic Publishing, Germany ISBN 9783844316704, 2011.
  10. Jabar H. Yousif, Dinesh Kumar Saini and Hassan S. Uraibi, "ARTIFICIAL INTELLIGENCE IN E-LEANING-PEDAGOGICAL AND COGNITIVE ASPECTS", Journal of Lecture Notes in Engineering and Computer Science,Vol:2191 , Issue:1 pp:997-1002 , 2011.
  11. Li Huang; Hai Jin; Pingpeng Yuan; Fan Chu; , "Duplicate Records Cleansing with Length Filtering and Dynamic Weighting," Semantics, Knowledge and Grid, 2008. SKG '08. Fourth International Conference on , vol. , no. , pp. 95-102, 3-5 Dec. 2008 URL: http://ieeexplore. ieee. org/stamp/stamp. jsp?tp=&arnumber=4725901&isnumber=4725879.
  12. DK Saini "Testing polymorphism in object oriented systems for improving software quality ACM SIGSOFT Software Engineering Notes 34 (2), 1-5, 2009.
  13. Mark Richards, Moustafa Ghanem, Michelle Osmond, Yike Guo, John Hassard. 2006. Grid based analysis of air pollution data. Ecological Modelling. Elsevier Journal. Volume 194, Issues 1–3, pp. 274–286.
  14. Ministry of Environment and Claimant affairs, Department of Monitoring Air pollution and Noise. Sultanate of Oman.
  15. Quass, D. : A Framework for Research in Data Cleaning. Unpublished Manuscript. Brigham Young Univ. , 1999.
  16. LS Prakash, DK Saini, NS Kutti "Integrating EduLearn learning content management system (LCMS) with cooperating learning object repositories (LORs) in a peer to peer (P2P) architectural framework" ACM SIGSOFT Software Engineering Notes 34 (3), 1-7, 2009.
  17. Rehman, M. ; Esichaikul, V. ; , "Duplicate Record Detection for Database Cleansing," Machine Vision, 2009. ICMV '09. Second International Conference on , vol. , no. , pp. 333-338,28-30Dec. 2009. URL: http://ieeexplore. ieee. org/stamp/stamp. jsp?tp=&arnumber=5381140&isnumber=5380895.
  18. Sousa, S. I. V. , Martins, F. G. , Pereira, M. C. , Alvim-Ferraz, M. C. M. , Ribeiro, H. ,Oliveira, M. , Abreu, I. : Influence of atmospheric ozone, PM10 and meteorological factors on the concentration of airborne pollen and fungal spores. Atmospheric Environment 42, 7452–7464 (2008)
  19. DK Saini "A mathematical model for the effect of malicious object on computer network immune system "Applied Mathematical Modelling 35 (8), 3777-3787, 2010.
  20. Teuvo Kohonen, "Self-Organizing Maps" (3rd edition) Springer, ISBN 3540679219 , 2001
  21. Zadeh, L. A. (2001). Applied Soft Computing. Applied Soft Computing 1, 1–2.
  22. Zvi Boger ,"Artificial Neural Networks Modeling to Reduce Industrial Air Pollution", Applications of Soft Computing :Advances in Soft Computing, SpringerLink, Volume 58, pp63-71, 2009.
  23. Wenjian Wang, Zongben Xu, Jane Weizhen Lu, (2003) "Three improved neural network models for air quality forecasting", Engineering Computations, Vol. 20 ISS: 2, pp. 192 – 210.
  24. WM Omar, DK Saini, M Hasan "Credibility of Digital Content in a Healthcare Collaborative Community" Software Tools and Algorithms for Biological Systems, 717-724, 2011.
  25. W. Ingemar, Christina K. R. , Maria S. Fedrik L. "Electronic tongues for environmental monitoring based on sensor arrays and pattern recognition: a review" Analytica Chemica Acta, Vol. 426, issue 12, Jan 2011, PP-217-226.
  26. DK Saini "Security Concerns of Object Oriented Software Architectures" International Journal of Computer Applications 40 (11), 41-48, 2012.
  27. Dinesh Kumar Saini, Lakshmi Sunil Prakash, "Engineering Education: Innovative Practices and Future Trends" (AICERA), 2012 IEEE International Conference.
Index Terms

Computer Science
Information Sciences

Keywords

Environmental modeling EMS air pollution environmental sensors Self-Organizing feature Map

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