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Real-Time Fire and Smoke Detection for Open Space Surveillance

Published on October 2015 by Rahul D. Dhotkar, R. V. Mante, and P. N. Chatur
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International Conference on Advancements in Engineering and Technology (ICAET 2015)
Foundation of Computer Science USA
ICQUEST2015 - Number 8
October 2015
Authors: Rahul D. Dhotkar, R. V. Mante, and P. N. Chatur
cea7566a-9378-4bd0-8319-28bed7987ddc

Rahul D. Dhotkar, R. V. Mante, and P. N. Chatur . Real-Time Fire and Smoke Detection for Open Space Surveillance. International Conference on Advancements in Engineering and Technology (ICAET 2015). ICQUEST2015, 8 (October 2015), 14-17.

@article{
author = { Rahul D. Dhotkar, R. V. Mante, and P. N. Chatur },
title = { Real-Time Fire and Smoke Detection for Open Space Surveillance },
journal = { International Conference on Advancements in Engineering and Technology (ICAET 2015) },
issue_date = { October 2015 },
volume = { ICQUEST2015 },
number = { 8 },
month = { October },
year = { 2015 },
issn = 0975-8887,
pages = { 14-17 },
numpages = 4,
url = { /proceedings/icquest2015/number8/23030-2907/ },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Proceeding Article
%1 International Conference on Advancements in Engineering and Technology (ICAET 2015)
%A Rahul D. Dhotkar
%A R. V. Mante
%A and P. N. Chatur
%T Real-Time Fire and Smoke Detection for Open Space Surveillance
%J International Conference on Advancements in Engineering and Technology (ICAET 2015)
%@ 0975-8887
%V ICQUEST2015
%N 8
%P 14-17
%D 2015
%I International Journal of Computer Applications
Abstract

Artificial neural network is use for analyzing and training the sensed data which gathered by different channels. In this paper we use different combinations of techniques to detect smoke and flame detection algorithms in a video. The past sensed data cannot respond quickly and fire and smoke may not capture quickly. The region partitioning technique is proposed, which will increase the accuracy and also reduce test data so that rather than using a whole frame in a video it uses on part of that frame. The flame characteristics are used for normalization data we are processing. The use of neural network in combination with image processing can improve the accuracy and also help to predict the data. In improvement the wrong alarm problem is decreased. The double band method is use to detect fire. The region which we are analyzing for detecting fire and smoke is calculated directly so that it can reduce computational time.

References
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Index Terms

Computer Science
Information Sciences

Keywords

Artificial Neural Network Flame Detection Imageprocessing.