Journal Article

FZJ-2015-04463

http://join2-wiki.gsi.de/foswiki/pub/Main/Artwork/join2_logo100x88.png Towards Improved Airborne Fire Detection Systems Using Beetle Inspired Infrared Detection and Fire Searching Strategies

Bousack, H. (Corresponding Author)FZJ* ; Kahl, T. ; Schmitz, A. ; Schmitz, H.

2015
MDPI Basel

This record in other databases:    

Please use a persistent id in citations: http://hdl.handle.net/2128/8936  doi:10.3390/mi6060718

Abstract: Every year forest fires cause severe financial losses in many countries of the world. Additionally, lives of humans as well as of countless animals are often lost. Due to global warming, the problem of wildfires is getting out of control; hence, the burning of thousands of hectares is obviously increasing. Most important, therefore, is the early detection of an emerging fire before its intensity becomes too high. More than ever, a need for early warning systems capable of detecting small fires from distances as large as possible exists. A look to nature shows that pyrophilous “fire beetles” of the genus Melanophila can be regarded as natural airborne fire detection systems because their larvae can only develop in the wood of fire-killed trees. There is evidence that Melanophila beetles can detect large fires from distances of more than 100 km by visual and infrared cues. In a biomimetic approach, a concept has been developed to use the surveying strategy of the “fire beetles” for the reliable detection of a smoke plume of a fire from large distances by means of a basal infrared emission zone. Future infrared sensors necessary for this ability are also inspired by the natural infrared receptors of Melanophila beetles.

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Contributing Institute(s):

1. Bioelektronik (PGI-8)
2. JARA-FIT (JARA-FIT)

Research Program(s):

1. 523 - Controlling Configuration-Based Phenomena (POF3-523) (POF3-523)

Appears in the scientific report 2015

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Database coverage:
; ; ; Current Contents - Engineering, Computing and Technology ; IF < 5 ; JCR ; Science Citation Index Expanded ; Thomson Reuters Master Journal List ; Web of Science Core Collection

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