Forest Fire Detection Using Wireless Multimedia Sensor Networks and Image Compression

Q3 Engineering
F. Bouakkaz, Wided Ali, M. Derdour
{"title":"Forest Fire Detection Using Wireless Multimedia Sensor Networks and Image Compression","authors":"F. Bouakkaz, Wided Ali, M. Derdour","doi":"10.18280/I2M.200108","DOIUrl":null,"url":null,"abstract":"Recently, the issue of multimedia sensors received considerable critical attention, that led to the apparition of Wireless Multimedia Sensor Networks (WMSNs) WMSN that different from wireless sensor networks (WSN) by using multimedia sensors that can process video, audio, image data besides scalar data and send it to station base (SB). Multimedia data have a big volume bigger than scalar data and need more resources and consumed more energy. The ideal solution to solve the problems of WMSN (big volume, energy consumption) is data compression. Forest plays a critical role in our daily life we can summarize the importance of forests in human life. Among the most dangerous events the forest fires that happen because of natural or Man-made. Many methods used to detect forest fires the newest are: wireless multimedia sensor networks. Our system of detecting forest fire has been developed using a wireless multimedia senor network with two types of sensors (scalar, images). In the first phase when the scalar sensors detected a high temperature its announced alarm to activate the image sensors. In the second phase for detecting fire the image sensors, we used image processing tools. When the zone of fire in the image captured was detected the phase of compression started using the down sampling method. the final phase is transmission data to the station base using the grid chain transmission protocol technique, which allows a critical optimization of energy consumption. So, maximizing network life. The competence of the proposed system is achieved by minimizing size of image transmitted with grid chain routing protocol.","PeriodicalId":38637,"journal":{"name":"Instrumentation Mesure Metrologie","volume":" ","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2021-02-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"7","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Instrumentation Mesure Metrologie","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.18280/I2M.200108","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"Engineering","Score":null,"Total":0}
引用次数: 7

Abstract

Recently, the issue of multimedia sensors received considerable critical attention, that led to the apparition of Wireless Multimedia Sensor Networks (WMSNs) WMSN that different from wireless sensor networks (WSN) by using multimedia sensors that can process video, audio, image data besides scalar data and send it to station base (SB). Multimedia data have a big volume bigger than scalar data and need more resources and consumed more energy. The ideal solution to solve the problems of WMSN (big volume, energy consumption) is data compression. Forest plays a critical role in our daily life we can summarize the importance of forests in human life. Among the most dangerous events the forest fires that happen because of natural or Man-made. Many methods used to detect forest fires the newest are: wireless multimedia sensor networks. Our system of detecting forest fire has been developed using a wireless multimedia senor network with two types of sensors (scalar, images). In the first phase when the scalar sensors detected a high temperature its announced alarm to activate the image sensors. In the second phase for detecting fire the image sensors, we used image processing tools. When the zone of fire in the image captured was detected the phase of compression started using the down sampling method. the final phase is transmission data to the station base using the grid chain transmission protocol technique, which allows a critical optimization of energy consumption. So, maximizing network life. The competence of the proposed system is achieved by minimizing size of image transmitted with grid chain routing protocol.
基于无线多媒体传感器网络和图像压缩的森林火灾探测
近年来,多媒体传感器问题引起了人们的广泛关注,并导致了无线多媒体传感器网络(WMSN)的出现。WMSN不同于无线传感器网络(WSN),它使用多媒体传感器处理除标量数据外的视频、音频、图像数据并将其发送到基站(SB)。多媒体数据的容量比标量数据大,需要更多的资源,消耗更多的能量。解决WMSN数据量大、能耗大的理想方案是数据压缩。森林在我们的日常生活中起着至关重要的作用,我们可以总结森林在人类生活中的重要性。在最危险的事件中,由于自然或人为原因而发生的森林火灾。目前用于森林火灾探测的最新方法有:无线多媒体传感器网络。我们开发的森林火灾探测系统采用无线多媒体传感器网络,其中包含两种类型的传感器(标量、图像)。在第一阶段,当标量传感器检测到高温时,它会发出警报来激活图像传感器。在第二阶段,我们使用图像处理工具对图像传感器进行检测。当检测到图像中的火焰区域后,使用下采样方法开始压缩阶段。最后一个阶段是使用电网链传输协议技术将数据传输到基站,这允许对能耗进行关键的优化。因此,最大化网络寿命。该系统通过最小化网格链路由协议传输的图像大小来提高系统的性能。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
求助全文
约1分钟内获得全文 求助全文
来源期刊
Instrumentation Mesure Metrologie
Instrumentation Mesure Metrologie Engineering-Engineering (miscellaneous)
CiteScore
1.70
自引率
0.00%
发文量
25
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
联系我们:info@booksci.cn Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。 Copyright © 2023 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术官方微信