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The System of Remote Monitoring of Microclimate Parameters of Bee Colonies

Treść / Zawartość
Identyfikatory
Warianty tytułu
Języki publikacji
EN
Abstrakty
EN
Accurate and timely measures to preserve the native populations of the wild honey bees need a study on the influence of housing conditions and environmental factors on the quality, productivity and viability of bee colonies. The authors have developed a system for remote monitoring of microclimate parameters of wild bee colonies based on the latest LoRaWAN technology. For studying the monitoring system based on the selected data transmission technology, data collection and transmission devices are implemented in two variants – based on ready-made monoblock devices (Variant 1) and composite devices (Variant 2) based on the Atmega328P microcontroller and photovoltaic power supply system with digital temperature and humidity sensors. Field tests of an experimental remote monitoring system were carried out in actual working conditions without power supply and communication systems. The tests involved 15 monoblock ready-made RAK7204 devices (Variant 1) and nine composite devices (Variant 2) based on the Atmega328P microcontroller. After the tests, Variant 1 was excluded from further use in research due to mass failure. Variant 2 passed the tests and participated in further research. The parameters of the power supply system of measuring devices and gateways are analyzed. The results of year-round monitoring of microclimate parameters of bee colonies were obtained. The study results prove the efficiency of the monitoring system based on LoRaWAN technology with the Atmega328P microcontroller devices and its operation comfort. During the study, it was recorded that the outer air temperature dropped to -36 °C. During the same period, the internal temperature significantly exceeded the air temperature. Besides, the highest temperature in wild hives during the winter months reaches +15 °C and +35.5 °C in the summer months. The temperature difference recorded in winter between the air inside wild hives and outer air reaches Δ30 °С.
Rocznik
Strony
264--273
Opis fizyczny
Bibliogr. 25 poz., rys., tab.
Twórcy
  • Federal State Budgetary Educational Establishment of Higher Education, Bashkir State Agrarian University, Ufa, 450001, Russian Federation
  • Federal State Budgetary Educational Establishment of Higher Education, Bashkir State Agrarian University, Ufa, 450001, Russian Federation
  • Federal State Budgetary Educational Establishment of Higher Education, Bashkir State Agrarian University, Ufa, 450001, Russian Federation
  • Federal State Budgetary Educational Establishment of Higher Education, Bashkir State Agrarian University, Ufa, 450001, Russian Federation
  • Federal State Budgetary Educational Establishment of Higher Education, Bashkir State Agrarian University, Ufa, 450001, Russian Federation
Bibliografia
  • 1. Braga A.R., Freitas B.M., Gomes D.G., Bezerra A.D., Cazier J.A. 2021. Forecasting sudden drops of temperature in pre-overwintering honeybee colonies. Biosyst. Eng., 209, 315–321.
  • 2. Braga A.R., Gomes D.G., Rogers R., Hassler E.E., Freitas B.M., Cazier J.A. 2020. A method for mining combined data from in-hive sensors, weather and apiary inspections to forecast the health status of honey bee colonies. Comput. Electron. Agric., 169, 105161.
  • 3. Cicioğlu M., Çalhan A. 2021. Smart agriculture with internet of things in cornfields. Comput. Electr. Eng., 90, 106982.
  • 4. Debauche O., El Moulat M., Mahmoudi S., Boukraa S., Manneback P., Lebeau F. 2018. Web monitoring of bee health for researchers and beekeepers based on the internet of things. Procedia Comput. Sci., 130, 991–998.
  • 5. Edwards-Murphy F., Magno M., Whelan P.M., O’Halloran J., Popovici E.M. 2016. b+ WSN: Smart beehive with preliminary decision tree analysis for agriculture and honey bee health monitoring. Comput. Electron. Agric.. 124, 211–219.
  • 6. Flores J.M., Gil-Lebrero S., Gámiz V., Rodríguez M.I., Ortiz M.A., Quiles F.J. 2019. Effect of the climate change on honey bee colonies in a temperate Mediterranean zone assessed through remote hive weight monitoring system in conjunction with exhaustive colonies assessment. Sci. Total Environ., 653, 1111–1119.
  • 7. Guo S., Yang R., Shen W., Liu Y., Guo S. 2022. DC-AC hybrid rapid heating method for lithium-ion batteries at high state of charge operated from low temperatures. Energy, 238, 121809.
  • 8. Henry E., Adamchuk V., Stanhope T., Buddle C., Rindlaub N. 2019. Precision apiculture: Development of a wireless sensor network for honeybee hives. Comput. Electron. Agric., 156, 138–144.
  • 9. Khisamov R., Yanbaev Y., Yumaguzhin F., Farkhutdinov R., Ishbulatov M., Onuchin M., Mustafi R., Rakhmatullin Z., Talipov E. 2019. Nectariferous potential and cadastral evaluation of honey resources of the wildlife Altyin Solok Reserve created for the conservation and reproduction of the Burzian population of the Apis Mellifera Mellifera L. Bulg. J. Agric. Sci., 25(2), 140–149.
  • 10. Kridi D.S., de Carvalho C.G.N., Gomes D.G. 2016. Application of wireless sensor networks for beehive monitoring and in-hive thermal patterns detection. Comput. Electron. Agric., 127, 221–235.
  • 11. Kviesis A., Zacepins A. 2015. System architectures for real-time bee colony temperature monitoring. Procedia Comput. Sci., 43, 86–94.
  • 12. Nambisan P., Saha P., Khanra M. 2021. Real-time optimal fast charging of Li-ion batteries with varying temperature and charging behaviour constraints. J. Energy Storage, 41, 102918.
  • 13. Neethirajan S., Tuteja S.K., Huang S.T., Kelton D. 2017. Recent advancement in biosensors technology for animal and livestock health management. Biosens. Bioelectron., 98, 398–407.
  • 14. Nigussie E., Olwal T., Musumba G., Tegegne T., Lemma A., Mekuria F. 2020. IoT-based irrigation management for smallholder farmers in rural subSaharan Africa. Procedia Comput. Sci., 177, 86–93.
  • 15. Rak. 2021. IoT Made Easy. https://store.rakwireless.com
  • 16. Sánchez V., Gil S., Flores J.M., Quiles F.J., Ortiz M.A., Luna J.J. 2015. Implementation of an electronic system to monitor the thermoregulatory capacity of honeybee colonies in hives with open-screened bottom boards. Comput. Electron. Agric. 119, 209–216.
  • 17. Savilov S.V., Strokova N.E., Ivanov A.S., Arkhipova E.A., Desyatov A.V., Hui X., Aldoshin S.M., Lunin V.V. 2015. Nanoscale carbon materials from hydrocarbons pyrolysis: Structure, chemical behavior, utilisation for non-aqueous supercapacitors. Mater. Res. Bull., 69, 13–19.
  • 18. Sultanova R.R., Gabitov I.I., Yanbaev Y.A., Yumaguzhin F.G., Martynova M.V., Chudov I.V., Tuktarov V.R. 2019. Forest melliferous resources as a sustainable development factor of beekeeping. Isr. J. Ecol. Evol., 65(3–4), 77–84.
  • 19. Tao W., Zhao L., Wang G., Liang R. 2021. Review of the internet of things communication technologies in smart agriculture and challenges. Comput. Electron. Agric., 189, 106352.
  • 20. Valishin D.E., Leontiev D.S., Muhortova E.I. 2020. Prospects for applying LoRaWAN communication technology in portable weather stations for agriculture. In: The current state, traditions and innovative technologies in the development of agriculture: proceedings of the International Scientific and Practical Conference. LLC “BGC”, Ufa, 16–21.
  • 21. Valishin D.E., Mukhortova E.I., Shavaliev I.F. 2020. Comparative analysis and directions of improvement of portable weather stations for agriculture. In: Actual problems of energy supply of enterprises: materials of the IV All-Russian Scientific and Practical Conference within the framework of the Russian Energy Forum and the XXV Anniversary International Exhibition “Energy of the Urals”. Bashkir Exhibition Company LLC, Ufa, 10–15.
  • 22. Venkatramulu S., Phridviraj M.S.B., Srinivas C., Rao V.C.S., 2021. Implementation of Grafana as open source visualization and query processingplatform for data scientists and researchers. Mater. Today in press.
  • 23. Vuran M.C., Salam A., Wong R., Irmak S. 2018. Internet of underground things in precision agriculture: Architecture and technology aspects. Ad Hoc Netw., 81, 160–173.
  • 24. Zacepins A., Brusbardis V., Meitalovs J., Stalidzans E. 2015. Challenges in the development of Precision Beekeeping. Biosyst. Eng., 130, 60–71.
  • 25. Zacepins A., Kviesis A., Stalidzans E., Liepniece M., Meitalovs J. 2016. Remote detection of the swarming of honey bee colonies by single-point temperature monitoring. Biosyst. Eng., 148, 76–80.
Typ dokumentu
Bibliografia
Identyfikator YADDA
bwmeta1.element.baztech-e386275e-8b56-4d94-b394-6fba12a5224d
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