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

• Autorzy: Polyniak Yu. , Fedasyuk D. , Marusenkova Tetyana
• 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.

Słowa kluczowe

EN

Acoustic Signal; Signal Recognition; Dynamic Time Warping; Fast Fourier Transform; Automated Bee Colony Monitoring

• Wydawca: Polish Academy of Sciences, Branch in Lublin
• Czasopismo: ECONTECHMOD : An International Quarterly Journal on Economics of Technology and Modelling Processes
• Rocznik: 2019
• Tom: Vol. 8, No 4
• Strony: 19--27
• Opis fizyczny: Bibliogr. 10 poz., rys.

Twórcy

autor

Polyniak Yu.

• Lviv Polytechnic National University, Lviv, Ukraine

autor

Fedasyuk D.

• Lviv Polytechnic National University, Lviv, Ukraine

autor

Marusenkova Tetyana

• 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.