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Identification of Bee Colony Acoustic Signals using the Dynamic Time Warping Algorithm

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Języki publikacji
EN
Abstrakty
EN
The work deals with automated recognition of the current state of a bee colony, for continuous monitoring of processes running in a bee hive is of key importance in beekeeping. The dynamic time warping algorithm is considered as a method of analyzing acoustic signals produced by a bee colony. Upon such an analysis one can make inferences about the current state of the colony. We have developed a software module for audio-signal identification, which is to be used as a part of an automated bee colony monitoring system, and a software tool for verification of the module. We evaluated the efficacy of the algorithm, the probability of bee colony states correctly recognized using acoustic signals produced by the colony and consumed computational resources by the example of a queen bee’s sounds recorded during swarming. The dependencies of the signal processing time and the successful pattern recognition probabilities on the frame sample rate and frame size are presented.
Twórcy
autor
  • Lviv Polytechnic National University, Lviv, Ukraine
autor
  • Lviv Polytechnic National University, Lviv, Ukraine
  • Lviv Polytechnic National University, Lviv, Ukraine
Bibliografia
  • 1.Woods E.F. 1957. Means for Detecting and Indicating the Activities of Bees and Conditions in Beehives. 2,806,082. U.S. Patent. 1957 Sep 10.
  • 2.Ferrari, S., Silva, M., Guarino, M., Berckmans, D. 2008. Monitoring of swarming sounds in bee hives for early detection of the swarming period. Comput. Electron. Agric. 64(1), 72–77.
  • 3.Gil-Lebrero, S., Quiles-Latorre, F., Ortiz-López, M., Sánchez-Ruiz, V., Gámiz-López, V., Luna-Rodríguez, J. 2017. Honey bee colonies remote monitoring system. Sensors 17(1), 55. doi:10.3390/s17010055.
  • 4.Kviesis, A., Zacepins, A., Durgun, M., Tekin, S. 2015. Application of wireless sensor networks in precision apiculture. In Proceedings of the 14th International Scientific Conference Engineering for Rural Development (ERDev), pp. 440–445. Latvia University of Agriculture.
  • 5.Rybochkin A.F., Zakharov I.S. 2004. Computer systems in beekeeping. Kursk State Technical University, Kursk (in Russian).
  • 6.Rybochkin A.F., Zakharov I.S. 2009. System analysis of acoustic signals of a bee colony using code messages. Kursk State Technical University, Kursk (in Russian).
  • 7.Rybochkin A.F. 2004. Monitoring and controlling the vital functions of bee colonies (in Russian)
  • 8.Qandour, A., Ahmad, I., Habibi, D., Leppard, M. 2014. Remote beehive monitoring using acoustic signals. Acoustics Australia 42(3), 204–209. doi:10.1007/s40857-015-0016-5
  • 9.Cejrowski, T., Szymanski, J., Mora, H., Gil. D. 2018. Detection of the bee queen presence using sound analysis. In 10th Asian Conference on Intelligent Information and Database Systems, pp. 297–306. Springer, Heidelberg. doi:10.1007/978-3-319-75420-8_28.
  • 10.Meikle, W., Holst, N. 2014. Application of continuous monitoring of honeybee colonies. Apidologie 46(1), 10–22 https://doi.org/10.1007/s13592-014-0298-x.
Typ dokumentu
Bibliografia
Identyfikator YADDA
bwmeta1.element.baztech-25a05c4b-4e21-4aad-b491-aed4981acc07
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