ICIEMS 2015

International Conference on Information Engineering, Management and Security 2015

 


ICIEMS 2015 Kokula Krishna Hari K
Publication Meta Value
Short Title ICIEMS 2015
Publisher ASDF, India
ISBN 13 978-81-929742-7-9
ISBN 10 81-929742-7-8
Language English
Type Hard Bound - Printed Book
Copyrights ICIEMS Organizers / DCRC, London, UK
Editor-in-Chief Kokula Krishna Hari K
Conference Dates 13 - 14, August 2015
Venue Country IITM-RP, Chennai, India
Submitted Papers 410
Acceptance Rate 4.11%
Website www.iciems.in

Paper 005


Forest Fire Prediction and Alert System Using Big Data Technology

Forest Fire Prediction and Alert System Using Big Data Technology

T Rajasekaran1, J Sruthi2, S Revathi2, N Raveena2

1Assistant Professor, KPR Institute of Engineering and Technology, 2Department of Computer Sciene and Engineering, KPR Institute of Engineering and Technology

Abstract

In this paper we discuss about the forest fire prediction and alert system using big data technology. Forest fire is considered as one of the major natural disaster. Our method is to collect and analyze the data from wireless sensor using hadoop tool to predict the forest fire before it occurs. Here we use machine learning tool called as Mahout which is used for clustering and filtering the datasets and it can be able to predict the valid output. By using GSM we can give alert message to people so that they can relocate to a safety place immediately, when fire occurs. Signal and Infrare image processing is used to monitor the signals and images of the entire forest for every 30 min and those data will be stored in datasets, by using those data we can be able to predict the forest fire in advance.

Author's Profile

T Rajasekaran : Profile

J Sruthi : Profile

S Revathi : Profile

N Raveena : Profile

Cite this Article as Follows

T Rajasekaran, J Sruthi, S Revathi, N Raveena. "Forest Fire Prediction and Alert System Using Big Data Technology." International Conference on Information Engineering, Management and Security (2015): 23-26. Print.