A Review on Forest Fire Detection Techniques: A Decadal Perspective

Author:

Chowdary Vinay,Kumar Gupta Mukul,Singh Rajesh

Abstract

Forest fire disasters have always been mankind’s constant and inconvenient companion since time immemorial. In the recent past years, managing crisis for example a large scale fire has become a very difficult and challenging task. Things that are common in most of the forest fire that occur at large scale are loss of life (human or animal), loss of vegetation, loss of flora and fauna, and communication failure (if any). Apart from causing a great loss to valuable natural resources of nature forest fire pose a greater risk not only to life of human being but also to the inhabitant’s such as wild life living in the forest. As per National Fire Danger Rating System (NFDRS), if a fire is detected within 6 minutes of its occurrence then it can be easily disposed-off before it turns into a large scale fire. For this a network that can detect fire at a very early stage is required. There are numerous techniques to detect the occurrence of forest fire and this article is dedicated towards reviewing detection techniques present in the literature. This work will give a bird’s eye view of the technologies used in automatic detection of forest fires and reviews almost all the detection techniques available in the literature. To the best of our knowledge this is the first time that almost all the techniques available in the literature are reviewed and considering almost all the parameters.

Publisher

Science Publishing Corporation

Subject

Hardware and Architecture,General Engineering,General Chemical Engineering,Environmental Engineering,Computer Science (miscellaneous),Biotechnology

Cited by 13 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

1. Captivating Verbatim Account of Historical Events in Ana Deaver Smith’s Fires in The Mirror;JOURNAL OF LANGUAGE STUDIES;2024-08-31

2. YOLO-ULNet: Ultralightweight Network for Real-Time Detection of Forest Fire on Embedded Sensing Devices;IEEE Sensors Journal;2024-08-01

3. An open flame and smoke detection dataset for deep learning in remote sensing based fire detection;Geo-spatial Information Science;2024-06-05

4. A Novel Intelligent Online Fire Monitoring Approach for Underground Pipe Galleries;2024 IEEE 13th Data Driven Control and Learning Systems Conference (DDCLS);2024-05-17

5. Multi-Modal AI for Enhanced Forest Fire Early Detection: Scalar and Image Fusion;2024 IEEE International Conference on Advanced Systems and Emergent Technologies (IC_ASET);2024-04-27

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