| 000 | 03897naa2a2200469 4500 | ||
|---|---|---|---|
| 001 | 654350 | ||
| 005 | 20231030041257.0 | ||
| 035 | _a(RuTPU)RU\TPU\network\19944 | ||
| 035 | _aRU\TPU\network\19942 | ||
| 090 | _a654350 | ||
| 100 | _a20170425a2017 k y0engy50 ba | ||
| 101 | 0 | _aeng | |
| 105 | _ay z 100zy | ||
| 135 | _adrcn ---uucaa | ||
| 181 | 0 | _ai | |
| 182 | 0 | _ab | |
| 200 | 1 |
_aAn algorithm of the wildfire classification by its acoustic emission spectrum using Wireless Sensor Networks _fA. A. Khamukhin [et al.] |
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| 203 |
_aText _celectronic |
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| 300 | _aTitle screen | ||
| 320 | _a[References: 10 tit.] | ||
| 330 | _aCrown 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 _tJournal of Physics: Conference Series |
|
| 463 | 0 |
_0(RuTPU)RU\TPU\network\19875 _tVol. 803 : Information Technologies in Business and Industry (ITBI2016) _oInternational Conference, 21–26 September 2016, Tomsk, Russian Federation _o[proceedings] _fNational Research Tomsk Polytechnic University (TPU) ; eds. N. V. Martyushev ; V. S. Avramchuk ; V. A. Faerman _v[012067, 6 p.] _d2017 |
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| 610 | 1 | _aэлектронный ресурс | |
| 610 | 1 | _aтруды учёных ТПУ | |
| 610 | 1 | _aалгоритмы | |
| 610 | 1 | _aклассификация | |
| 610 | 1 | _aлесные пожары | |
| 610 | 1 | _aакустическая эмиссия | |
| 610 | 1 | _aбеспроводные сенсорные сети | |
| 610 | 1 | _aвычислительные системы | |
| 701 | 1 |
_aKhamukhin _bA. A. _cspecialist in the field of Informatics and computer engineering _cAssociate Professor of Tomsk Polytechnic University, candidate of technical sciences _f1954- _gAleksandr Anatolievich _2stltpush _3(RuTPU)RU\TPU\pers\33694 |
|
| 701 | 1 |
_aDemin _bA. Yu. _cspecialist in the field of Informatics and computer engineering _cAssociate Professor of Tomsk Polytechnic University, candidate of technical sciences _f1973- _gAnton Yurievich _2stltpush _3(RuTPU)RU\TPU\pers\33696 |
|
| 701 | 1 |
_aSonkin _bD. M. _cspecialist in the field of informatics and computer engineering _cAssociate Professor of Tomsk Polytechnic University, candidate of technical sciences _f1986- _gDmitry Mikhailovich _2stltpush _3(RuTPU)RU\TPU\pers\34614 |
|
| 701 | 1 |
_aBertoldo _bS. |
|
| 701 | 1 |
_aPerona _bG. |
|
| 701 | 1 |
_aKretova _bV. |
|
| 712 | 0 | 2 |
_aНациональный исследовательский Томский политехнический университет (ТПУ) _bИнститут кибернетики (ИК) _2stltpush _3(RuTPU)RU\TPU\col\18397 |
| 801 | 2 |
_aRU _b63413507 _c20170428 _gRCR |
|
| 856 | 4 | _uhttp://dx.doi.org/10.1088/1742-6596/803/1/012067 | |
| 856 | 4 | _uhttp://earchive.tpu.ru/handle/11683/38152 | |
| 942 | _cBK | ||