An algorithm of the wildfire classification by its acoustic emission spectrum using Wireless Sensor Networks

Bibliographic Details
Parent link:Journal of Physics: Conference Series
Vol. 803 : Information Technologies in Business and Industry (ITBI2016).— 2017.— [012067, 6 p.]
Corporate Author: Национальный исследовательский Томский политехнический университет (ТПУ) Институт кибернетики (ИК)
Other Authors: Khamukhin A. A. Aleksandr Anatolievich, Demin A. Yu. Anton Yurievich, Sonkin D. M. Dmitry Mikhailovich, Bertoldo S., Perona G., Kretova V.
Summary:Title screen
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.
Published: 2017
Subjects:
Online Access:http://dx.doi.org/10.1088/1742-6596/803/1/012067
http://earchive.tpu.ru/handle/11683/38152
Format: Electronic Book Chapter
KOHA link:https://koha.lib.tpu.ru/cgi-bin/koha/opac-detail.pl?biblionumber=654350

MARC

LEADER 00000naa2a2200000 4500
001 654350
005 20231220154410.0
035 |a (RuTPU)RU\TPU\network\19944 
035 |a RU\TPU\network\19942 
090 |a 654350 
100 |a 20170425a2017 k y0engy50 ba 
101 0 |a eng 
105 |a y z 100zy 
135 |a drcn ---uucaa 
181 0 |a i  
182 0 |a b 
200 1 |a An algorithm of the wildfire classification by its acoustic emission spectrum using Wireless Sensor Networks  |f A. A. Khamukhin [et al.] 
203 |a Text  |c electronic 
300 |a Title screen 
320 |a [References: 10 tit.] 
330 |a 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. 
461 0 |0 (RuTPU)RU\TPU\network\3526  |t Journal of Physics: Conference Series 
463 0 |0 (RuTPU)RU\TPU\network\19875  |t Vol. 803 : Information Technologies in Business and Industry (ITBI2016)  |o International Conference, 21–26 September 2016, Tomsk, Russian Federation  |o [proceedings]  |f National Research Tomsk Polytechnic University (TPU) ; eds. N. V. Martyushev ; V. S. Avramchuk ; V. A. Faerman  |v [012067, 6 p.]  |d 2017 
610 1 |a электронный ресурс 
610 1 |a труды учёных ТПУ 
610 1 |a алгоритмы 
610 1 |a классификация 
610 1 |a лесные пожары 
610 1 |a акустическая эмиссия 
610 1 |a беспроводные сенсорные сети 
610 1 |a вычислительные системы 
701 1 |a Khamukhin  |b A. A.  |c specialist in the field of Informatics and computer engineering  |c Associate Professor of Tomsk Polytechnic University, candidate of technical sciences  |f 1954-  |g Aleksandr Anatolievich  |3 (RuTPU)RU\TPU\pers\33694  |9 17325 
701 1 |a Demin  |b A. Yu.  |c specialist in the field of Informatics and computer engineering  |c Associate Professor of Tomsk Polytechnic University, candidate of technical sciences  |f 1973-  |g Anton Yurievich  |3 (RuTPU)RU\TPU\pers\33696  |9 17327 
701 1 |a Sonkin  |b D. M.  |c specialist in the field of informatics and computer engineering  |c Associate Professor of Tomsk Polytechnic University, candidate of technical sciences  |f 1986-  |g Dmitry Mikhailovich  |3 (RuTPU)RU\TPU\pers\34614 
701 1 |a Bertoldo  |b S. 
701 1 |a Perona  |b G. 
701 1 |a Kretova  |b V. 
712 0 2 |a Национальный исследовательский Томский политехнический университет (ТПУ)  |b Институт кибернетики (ИК)  |3 (RuTPU)RU\TPU\col\18397 
801 2 |a RU  |b 63413507  |c 20170428  |g RCR 
856 4 |u http://dx.doi.org/10.1088/1742-6596/803/1/012067 
856 4 |u http://earchive.tpu.ru/handle/11683/38152 
942 |c BK