Call for Paper - March 2023 Edition
IJCA solicits original research papers for the March 2023 Edition. Last date of manuscript submission is February 20, 2023. Read More

A Novel Fire Detection System using Image Processing and Artificial Intelligence Techniques

Print
PDF
IJCA Proceedings on Emerging Technology Trends on Advanced Engineering Research - 2012
© 2013 by IJCA Journal
ICETT - Number 2
Year of Publication: 2013
Authors:
R. Divya
D. Mageshwari

R Divya and D Mageshwari. Article: A Novel Fire Detection System using Image Processing and Artificial Intelligence Techniques. IJCA Proceedings on Emerging Technology Trends on Advanced Engineering Research - 2012 ICETT(2):15-18, January 2013. Full text available. BibTeX

@article{key:article,
	author = {R. Divya and D. Mageshwari},
	title = {Article: A Novel Fire Detection System using Image Processing and Artificial Intelligence Techniques},
	journal = {IJCA Proceedings on Emerging Technology Trends on Advanced Engineering Research - 2012},
	year = {2013},
	volume = {ICETT},
	number = {2},
	pages = {15-18},
	month = {January},
	note = {Full text available}
}

Abstract

Fire is a terrifying weapon, with nearly unlimited destructive power. Fire accidents are a major cause of human suffering and material loss and the one that perhaps are predicted the least accurately. Most existing work in fire occurrence prediction focuses on prediction of wildfires in forests and those caused by volcanic eruptions. Surprisingly prediction of fire occurrence in residential and official buildings has not been fully explored because the factors that influence fires are too many. The idea behind this research is to provide an alert to fire stations in the event of fire in hospitals, official and commercial buildings by the use of Image processing and Artificial Intelligence techniques that might significantly reduce the death toll and loss of property caused by fire accidents. The Digital snapshots of the building can be taken (1,600 x 1,200 pixels at 1MB image per second) continuously using Closed circuit digital photography (CCDP) and these snapshots are then automatically sent to the server for storage as timed and dated JPEG files. The digital images are converted from RGB to XYZ color space and then segmented by utilizing anisotropic diffusion to identify the presence of fires. Subsequently, Radial Basis Function Neural Network is trained with the color space values of the segmented fire regions and is employed in the design of this novel system. The proposed intelligent system will thus aid in alerting the fire stations with the help of a Global System for Mobile Communications in event of any fire to take immediate actions before fire spreads quickly and causes traumatizing loss.

References

  • SAARC Disaster Management Centre, New Delhi.
  • ENVIS Centre on Human Settlements, New Delhi ,"Monograph On Fire Hazard", http://www. spaenvis. nic. in/pdfs/monographs/fire-hazard. pdf
  • Louis Giglio, Jacques Descloitres, Christopher O. Justice, Yoram J. Kaufman, "An Enhanced Contextual Fire Detection Algorithm for MODIS", Remote Sensing of Environment, vol. 87, pp. 73–282, 2003.
  • K. Angayarkkani,N. Radhakrishnan,"Efficient Forest Fire Detection System: A Spatial Data Mining and Image Processing Based Approach",IJCSNS International Journal of Computer Science and Network Security, VOL. 9 No. 3, March 2009.
  • Joydeb Roy Choudhury, Tribeni Prasad Banerjee, Swagatam Das, Ajith Abraham and Václav Snášel, "Fuzzy Rule Based Intelligent Security and Fire Detector System",Computational Intelligence in Security for Information Systems Advances in Intelligent and Soft Computing, 2009, Volume 63/2009, 45-51, DOI: 10. 1007/978-3-642-04091-7_6 .
  • Adrian Ford and Alan Roberts, "Color Space Conversions", Technical Report, August 11, 1998.
  • Marko Tkal?i?, Jurij F. Tasi?,"Color spaces - perceptual, historical and applicational background" Faculty of Electrical Engineering, University of Ljubljana.
  • Daehee Kim, Ho Yo-Sung and B. S. Manjunath "Color Image Segmentation Using Anisotropic Diffusion and Agglomerative Hierarchical Clustering", Advances in Multimedia Information Processing — PCM 2002, Volume 2532/2002, 118-121, DOI: 10. 1007/3-540-36228-2_94
  • Girish kumar JHA,"Artificial neural networks ",Indian Agricultural Research Institute.
  • J. Park I. W. Sandberg,"Universal Approximation using Radial-Basis-Function Networks", Department of Electrical and Computer Engineering, University of Texas
  • S. Josephine Selvarani,"Online Health Monitoring System Using Zigbee", Department Of Electronics and Communications, Karunya University, Coimbatore.
  • Elliott D. Light Et Al,"System And Method For Establishing A Call Between A Calling Party And A Called Party Over A Wired Network".
  • Nitika, Simpel Jindal," Multimessaging System Using Gsm Modem".
  • Malik Sikandar Hayat Khiyal, Aihab Khan, Erum Shehzadi ,"SMS Based Wireless Home Appliance Control System (HACS) for Automating Appliances and Security", Department Of Software Engineering, Fatima Jinnah Women University, Rawalpindi, Pakistan.