利用无线传感器网络进行森林火灾探测

IF 0.5 Q4 ENGINEERING, ELECTRICAL & ELECTRONIC
Premsai Dasari, Gundam Krishna Jayanth Reddy, Abhishek Gudipalli
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引用次数: 19

摘要

森林有不同类型的植被,如草本植物、乔木、灌木和不同种类的动物。不管怎样,这些可再生资源对人类是非常重要的。森林火灾是森林中最常见的危害,它严重破坏了森林财富、生物多样性和自然栖息地。早期发现和预防措施对于保护森林免受火灾是必要的。为了实现早期发现,有两种最常用的传统人员监测方法。一种是直接通过人工观察,另一种是通过远程视频监控。通过远距离观察的方式,可以通过自动化检测的方式实现监视。本文提出的火灾自动报警探测系统由烟雾和火灾两个传感器组成。这些传感器可以探测到可测量物理量的变化,有助于及早发现森林火灾。该火灾探测系统的一个主要特点是,每当探测到火灾时,通过GSM模块远程提醒用户。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Forest fire detection using wireless sensor networks
Abstract A forest has different types of vegetation like herbs, trees, shrubs and different species of animals. In one way or other, these renewable resources are very essential to mankind. Forest fires are the most common hazards in forests which lead to serious destruction of forest wealth, bio-diversity and natural habitat. Early detection and preventive measures are necessary to protect forests from fires. In order to achieve early detection, there are two most used traditional methods of human surveillance. One is directly through human observation and the other is through distant video surveillance. Doing the observation through distant mode, one can achieve surveillance through automation approach of detection. Automated fire alert detection system proposed in this paper comprises of two sensors, namely smoke and fire. These sensors detect change in a measurable physical quantity and help in the early detection of a forest fire. A key feature of this fire detection system is to alert the user remotely by using a GSM module, whenever a fire is detected.
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来源期刊
CiteScore
2.70
自引率
8.30%
发文量
15
审稿时长
8 weeks
期刊介绍: nternational Journal on Smart Sensing and Intelligent Systems (S2IS) is a rapid and high-quality international forum wherein academics, researchers and practitioners may publish their high-quality, original, and state-of-the-art papers describing theoretical aspects, system architectures, analysis and design techniques, and implementation experiences in intelligent sensing technologies. The journal publishes articles reporting substantive results on a wide range of smart sensing approaches applied to variety of domain problems, including but not limited to: Ambient Intelligence and Smart Environment Analysis, Evaluation, and Test of Smart Sensors Intelligent Management of Sensors Fundamentals of Smart Sensing Principles and Mechanisms Materials and its Applications for Smart Sensors Smart Sensing Applications, Hardware, Software, Systems, and Technologies Smart Sensors in Multidisciplinary Domains and Problems Smart Sensors in Science and Engineering Smart Sensors in Social Science and Humanity
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