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Title: An algorithm of the wildfire classification by its acoustic emission spectrum using Wireless Sensor Networks
Authors: Khamukhin, Aleksandr Anatolievich
Demin, Anton Yurievich
Sonkin, Dmitry Mikhailovich
Bertoldo, S.
Perona, G.
Kretova, V.
Keywords: алгоритмы; классификация; лесные пожары; акустическая эмиссия; беспроводные сенсорные сети; вычислительные системы
Issue Date: 2017
Publisher: IOP Publishing
Citation: An algorithm of the wildfire classification by its acoustic emission spectrum using Wireless Sensor Networks / A. A. Khamukhin [et al.] // Journal of Physics: Conference Series. — 2017. — Vol. 803 : Information Technologies in Business and Industry (ITBI2016) : International Conference, 21–26 September 2016, Tomsk, Russian Federation : [proceedings]. — [012067, 6 p.].
Abstract: Crown fires are extremely dangerous as the speed of their distribution is dozen times higher compared to surface fires. Therefore, it is important to classify the fire type as early as possible. A method for forest fires classification exploits their computed acoustic emission spectrum compared with a set of samples of the typical fire acoustic emission spectrum stored in the database. This method implies acquisition acoustic data using Wireless Sensors Networks (WSNs) and their analysis in a central processing and a control center. The paper deals with an algorithm which can be directly implemented on a sensor network node that will allow reducing considerably the network traffic and increasing its efficiency. It is hereby suggested to use the sum of the squares ratio, with regard to amplitudes of low and high frequencies of the wildfire acoustic emission spectrum, as the indicator of a forest fire type. It is shown that the value of the crown fires indicator is several times higher than that of the surface ones. This allows classifying the fire types (crown, surface) in a short time interval and transmitting a fire type indicator code alongside with an alarm signal through the network.
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