Salta al menu principale di navigazione Salta al contenuto principale Salta al piè di pagina del sito

Articles

V. 16 N. 1 (2026)

Climate Change and the Role of Using Artificial Intelligence Applications in Apiculture

DOI
https://doi.org/10.3280/riss2026oa21557
Inviata
dicembre 4, 2025
Pubblicato
2026-06-19

Abstract

Wild and commercially significant plants are pollinated by honeybees. Currently, apiculture is suffering from the negative consequences of climate change, including extreme weather conditions and increasing temperature averages. Climate change can affect floral sources of honey bees, increase the frequency of parasites and diseases, and interfere with pollination cycles; thus, climate change poses a serious danger to apiculture and consequently beekeeping industry and global food production. Utilising cutting-edge technologies like artificial intelligence (AI) applications are crucial for reducing the negative effects of climate change on honey production and bee populations. AI can play a crucial role in apiculture by helping beekeepers to monitor and manage their hives more efficiently. This study employed a review-based approach to determine how AI can be employed in the beekeeping sector. The results suggests that combination of AI, ML and IoT can be used to evaluate environmental data, such as weather patterns, flowering seasons and satellite images interpretation. That can optimise beekeeping methods by forecasting the ideal periods for hive inspections, honey harvesting, and other tasks. This can increase the overall productivity of the hives and help bee keepers to make better decisions for the sustainability of their apiaries.

Riferimenti bibliografici

  1. Abou-Shaara, H. F., Staron, M., & Staroňová, D. (2020). Potential applications of nanotechnology in apiculture. Entomology and Applied Science Letters, 7(4), 1-8.
  2. Ali, M. A., Abdellah, I. M., & Eletmany, M. R. (2023). Climate change impacts on honeybee spread and activity: A scientific review. Chelonian Research Foundation, 18(2), 531-554.
  3. Almeida, E. A., Bossert, S., Danforth, B. N., Porto, D. S., Freitas, F. V., Davis, C. C., Murray, E. A., Blaimer, B. B., Spasojevic, T., & Ströher, P. R. (2023). The evolutionary history of bees in time and space. Current Biology, 33(16), 3409-3422.
  4. Anuar, N. H. K., Yunus, M. A. M., Kasuan, N., Baharuddin, M. A., Ibrahim, S., & Sahlan, S. (2023). Technological Adoption and Challenges in Beekeeping: A Review, 80-85.
  5. Aryal, S., Thapa, R., & Jung, C. (2015). An overview of Beekeeping Economy and Its Constraints in Nepal. Journal of Apiculture, 30, 135-142.
  6. Astuti, P. K., Hegedűs, B., Oleksa, A., Bagi, Z., & Kusza, S. (2024a). Buzzing with Intelligence: Current Issues in Apiculture and the Role of Artificial Intelligence (AI) to Tackle It. Insects, 15(6), 418.
  7. Astuti, P. K., Hegedűs, B., Oleksa, A., Bagi, Z., & Kusza, S. (2024b). Buzzing with Intelligence: Current Issues in Apiculture and the Role of Artificial Intelligence (AI) to Tackle It. Insects, 15(6), 418.
  8. Burma, Z. A. (2023). Digital transformation in beekeeping to carrying beehives into the future. International Journal of Nature and Life Sciences, 7(2), 89-99.
  9. Crane, E. (1999). The world history of beekeeping and honey hunting. Routledge.
  10. De Nart, D., Costa, C., Di Prisco, G., & Carpana, E. (2022). Image recognition using convolutional neural networks for classification of honey bee subspecies. Apidologie, 53(1), 5.
  11. De Simone, A., Barbisan, L., Turvani, G., & Riente, F. (2024). Advancing Beekeeping: IoT and TinyML for Queen Bee Monitoring Using Audio Signals. IEEE Transactions on Instrumentation and Measurement.
  12. Degenfellner, J., & Templ, M. (2024). Modeling bee hive dynamics: Assessing colony health using hive weight and environmental parameters. Computers and Electronics in Agriculture, 218, 108742.
  13. Delena, M. F., & Kayamo, S. E. (2024). Beekeeping opportunities, challenges and technology adoption in Gedeo Zone, Southern Ethiopia. Journal of Apicultural Research, 63(3), 456-461.
  14. Doinea, M., Trandafir, I., Toma, C.-V., Popa, M., & Zamfiroiu, A. (2024). IoT Embedded Smart Monitoring System with Edge Machine Learning for Beehive Management. International Journal of Computers Communications & Control, 19(4).
  15. Dsouza, A., & Hegde, S. (2023). HiveLink, an IoT based Smart Bee Hive Monitoring System. arXiv Preprint arXiv, 2309.12054.
  16. Eliades, N.-G. H., Aravanopoulos, F. A., & Christou, A. (2018). Mediterranean Islands Hosting Marginal and Peripheral Forest Tree Populations: The Case of Pinus brutia Ten. In Cyprus. Forests. -- https://api.semanticscholar.org/CorpusID:52108725.
  17. Eroğlu, Ö., & Yüksel, S. (2020). Historical development and current status of beekeeping in Turkey and the World. Atlas Journal, 6(27), 345-354.
  18. Gonzalez, V. H., Cobos, M. E., Jaramillo, J., & Ospina, R. (2021). Climate change will reduce the potential distribution ranges of Colombia’s most valuable pollinators. Perspectives in Ecology and Conservation, 19(2), 195-206.
  19. Grammalidis, N., Stergioulas, A., Avramidis, A., Karystinakis, K., Partozis, A., Topaloudis, A., Kalantzi, G., Tananaki, C., Kanelis, D., & Liolios, V. (2023). A smart beekeeping platform based on remote sensing and artificial intelligence. 12786, 92-99.
  20. Guyo, S. H., & Legesse, S. A. (n.d.). On Beekeeping activities, opportunities, challenges and marketing in Ethiopia. -- https://api.semanticscholar.org/CorpusID:237277878.
  21. Hadjur, H., Ammar, D., & Lefèvre, L. (2022). Toward an intelligent and efficient beehive: A survey of precision beekeeping systems and services. Computers and Electronics in Agriculture, 192, 106604.
  22. Hong, W., Xu, B., Chi, X., Cui, X., Yan, Y., & Li, T. (2020). Long-Term and Extensive Monitoring for Bee Colonies Based on Internet of Things. IEEE Internet of Things Journal, 7, 7148-7155.
  23. Jahan, M. M. S., Rahman, M. S., Haque, M. P., & Saikat, M. M. H. (2021). Problems and Prospects of Apiculture in Bangladesh: A Review. Fundamental and Applied Agriculture. -- https://api.semanticscholar.org/CorpusID:243487499.
  24. Kandemir, I., Meixner, M. D., Ozkan, A., & Sheppard, W. S. (2006). Genetic characterization of honey bee (Apis mellifera cypria) populations in northern Cyprus. Apidologie, 37(5), 547-555.
  25. Kaňovská, L. (2024). The Use of Products with a Monitoring System for Remote Bee Detection in Beekeeping in Czechia. Agris On-Line Papers in Economics & Informatics, 16(1).
  26. Kösoğlu, M., Tunca, R. İ., Yücel, B., Balkanska, R., & Yildirir, Z. T. (2021). Arıcılıkta Sürdürülebilirlik Mümkün Mü?. MAS Journal of Applied Sciences, 6(3), 610-623.
  27. Kritsky, G. (2017). Beekeeping from antiquity through the middle ages. Annual Review of Entomology, 62(1), 249-264.
  28. Kuboja, N. M., Isinika, A., & Kilima, F. (2021). Adoption and impacts of improved beehive technologies in the miombo woodland of Tanzania. African Journal of Science, Technology, Innovation and Development, 13(2), 157-166.
  29. Kumar, R., & Kundal, N. (2016). Beekeeping status in Kangra district of Himachal Pradesh. Journal of Entomology and Zoology Studies, 4, 620-622.
  30. Landaverde, R., Rodriguez, M. T., & Parrella, J. A. (2023). Honey production and climate change: Beekeepers’ perceptions, farm adaptation strategies, and information needs. Insects, 14(6), 493.
  31. Leocádio, R. R. V., Segundo, A. K. R., & Pessin, G. (2024). A Brazilian native bee (Tetragonisca angustula) dataset for computer vision. Data in Brief, 55, 110659.
  32. Mrozek, D., Gȯrny, R., Wachowicz, A., & Małysiak-Mrozek, B. (2021). Edge-based detection of varroosis in beehives with iot devices with embedded and tpu-accelerated machine learning. Applied Sciences, 11(22), 11078.
  33. Myronidis, D., Ioannou, K., Fotakis, D. G., & Dörflinger, G. (2018). Streamflow and Hydrological Drought Trend Analysis and Forecasting in Cyprus. Water Resources Management, 32, 1759-1776.
  34. Nacko, S., Hall, M. A., Gloag, R., Lynch, K. E., Spooner-Hart, R. N., Cook, J. M., & Riegler, M. (2023). Heat stress survival and thermal tolerance of Australian stingless bees. Journal of Thermal Biology, 117, 103671.
  35. Ntawuzumunsi, E., Kumaran, S., Sibomana, L., & Mtonga, K. (2023). Design and development of energy efficient algorithm for smart beekeeping device to device communication based on data aggregation techniques. Algorithms, 16(8), 367.
  36. Özsağlam, M. T. (2018). Limited recognition and limited relations: TRNC. Journal of Management and Economics Research, 16(1), 314-328.
  37. Pal, P., Sahu, M., & Juyal, R. (2022). Utilising Iot Technologies to Improve Beekeeping through Remote Hive Monitoring. Journal of Survey in Fisheries Sciences, 367-372.
  38. Pandimurugan, V., Mandviya, R., Gadgil, A., Prakhar, K., & Datar, A. (2021). IoT based Smart Beekeeping Monitoring system for beekeepers in India, 65-70.
  39. Pasupuleti, V. R., Sammugam, L., Ramesh, N., & Gan, S. H. (2017). Honey, propolis, and royal jelly: A comprehensive review of their biological actions and health benefits. Oxidative Medicine and Cellular Longevity, 2017(1), 1259510.
  40. Qaiser, T., Tahir, A., Taj, S., & Ali, M. (2013). Benefit-cost analysis of apiculture enterprise: A case study in district Chakwal, Pakistan. Pakistan Journal of Agricultural Research, 26, 295-298.
  41. Robustillo, M. C., Pérez, C. J., & Parra, M. I. (2022). Predicting internal conditions of beehives using precision beekeeping. Biosystems Engineering, 221, 19-29.
  42. Šarić, B. B., Muça, E. D., Subić, J., Džimrevska, I., & Rašić, S. (2023). Environmental threats to beekeeping in the Western Balkan countries-beekeepers’ perceptions. Environmental Research Communications, 5(6), 065003.
  43. Şenol, C. (2021). Kuzey Kıbrıs Türk Cumhuriyeti’nin Hidrografik Yapısı, Su Sorunu ve Çözüm Önerileri. Journal of Cyprus Studies, 21(45).
  44. Singh, G., & Sharma, M. (2017). Diagnosis and remedial measures of common technological problems in bee keeping. Journal of Krishi Vigyan, 5(2), 27-31.
  45. Sokhai, K., & Mardy, S. (2024). A Review on the Aspect of Beekeeping and Economic Efficiency. International Journal of Integrative Research. -- https://api.semanticscholar.org/CorpusID:268269072.
  46. Spiesman, B. J., Gratton, C., Hatfield, R. G., Hsu, W. H., Jepsen, S., McCornack, B., Patel, K., & Wang, G. (2021). Assessing the potential for deep learning and computer vision to identify bumble bee species from images. Scientific Reports, 11(1), 7580.
  47. Stalidzans, E. (2012). Application of Information Technologies in precision apiculture. -- https://api.semanticscholar.org/CorpusID:51776305.
  48. Teferi, K. (2018). Status of Beekeeping in Ethiopia ‒ A Review. Journal of Dairy & Veterinary Sciences. -- https://api.semanticscholar.org/CorpusID:59593337.
  49. Thu, P. T. K., Hong, Du, N. H., Doan, N., Luu, V. T., Hoang, N. V., Thai, P. H., Ngoc, P. T., Viet, N., Long, Phan, & Hong, T. T. (2020). Audio Beehive Monitoring Based on IoT-AI Techniques: A Survey and Perspective. -- https://api.semanticscholar.org/CorpusID:222361603.
  50. Van Espen, M., Williams, J. H., Alves, F., Hung, Y., de Graaf, D. C., & Verbeke, W. (2023). Beekeeping in Europe facing climate change: A mixed methods study on perceived impacts and the need to adapt according to stakeholders and beekeepers. Science of the Total Environment, 888, 164255.
  51. Varnava, A. I., Roberts, S. P. M., Michez, D., Ascher, J. S., Petanidou, T., Dimitriou, S., Devalez, J., Pittara, M., & Stavrinides, M. C. (2020). The wild bees (Hymenoptera, Apoidea) of the island of Cyprus. ZooKeys, 924, 1-114.
  52. Verbeke, W., Diallo, M. A., van Dooremalen, C., Schoonman, M., Williams, J. H., Van Espen, M., D’Haese, M., & de Graaf, D. C. (2024). European beekeepers’ interest in digital monitoring technology adoption for improved beehive management. Computers and Electronics in Agriculture, 227, 109556.
  53. Zabasta, A., Zhiravetska, A., Kunicina, N., & Kondratjevs, K. (2019). Technical Implementation of IoT Concept for Bee Colony Monitoring. 2019 8th Mediterranean Conference on Embedded Computing (MECO), 1-4.
  54. Zacepins, A., Komasilovs, V., Jelinskis, J., Ozols, N., & Kviesis, A. (2022). Application of the Internet of Things in precision beekeeping in Latvia. Agrofor International Journal, 7(3).
  55. Zacepins, A., Stalidzans, E., & Meitalovs, J. (2012). Application of information technologies in precision apiculture. 7.