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Sensors 2016, 16(6), 893; doi:10.3390/s16060893

Efficient Forest Fire Detection Index for Application in Unmanned Aerial Systems (UASs)

Research Center on Software Technologies and Multimedia Systems for Sustainability (CITSEM), Universidad Politécnica de Madrid, Alan Turing St., Madrid 28031, Spain
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Academic Editor: Ingolf Willms
Received: 31 March 2016 / Revised: 31 May 2016 / Accepted: 13 June 2016 / Published: 16 June 2016
(This article belongs to the Special Issue Sensors for Fire Detection)
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Abstract

This article proposes a novel method for detecting forest fires, through the use of a new color index, called the Forest Fire Detection Index (FFDI), developed by the authors. The index is based on methods for vegetation classification and has been adapted to detect the tonalities of flames and smoke; the latter could be included adaptively into the Regions of Interest (RoIs) with the help of a variable factor. Multiple tests have been performed upon database imagery and present promising results: a detection precision of 96.82% has been achieved for image sizes of 960 × 540 pixels at a processing time of 0.0447 seconds. This achievement would lead to a performance of 22 f/s, for smaller images, while up to 54 f/s could be reached by maintaining a similar detection precision. Additional tests have been performed on fires in their early stages, achieving a precision rate of p = 96.62%. The method could be used in real-time in Unmanned Aerial Systems (UASs), with the aim of monitoring a wider area than through fixed surveillance systems. Thus, it would result in more cost-effective outcomes than conventional systems implemented in helicopters or satellites. UASs could also reach inaccessible locations without jeopardizing people’s safety. On-going work includes implementation into a commercially available drone. View Full-Text
Keywords: forest fire detection; color index; mobile surveillance; UAS; UAV; drone; real-time; cost-efficient forest fire detection; color index; mobile surveillance; UAS; UAV; drone; real-time; cost-efficient
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This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. (CC BY 4.0).

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MDPI and ACS Style

Cruz, H.; Eckert, M.; Meneses, J.; Martínez, J.-F. Efficient Forest Fire Detection Index for Application in Unmanned Aerial Systems (UASs). Sensors 2016, 16, 893.

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