دورية أكاديمية
Identifying Queenlessness in Honeybee Hives from Audio Signals Using Machine Learning
العنوان: | Identifying Queenlessness in Honeybee Hives from Audio Signals Using Machine Learning |
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المؤلفون: | Stenford Ruvinga, Gordon Hunter, Olga Duran, Jean-Christophe Nebel |
المصدر: | Electronics, Vol 12, Iss 7, p 1627 (2023) |
بيانات النشر: | MDPI AG |
سنة النشر: | 2023 |
المجموعة: | Directory of Open Access Journals: DOAJ Articles |
مصطلحات موضوعية: | honeybees, queen bee, bee colony, audio signal, CNN, LSTM, Electronics, TK7800-8360 |
الوصف: | Honeybees are vital to both the agricultural industry and the wider ecological system, most importantly for their role as major pollinators of flowering plants, many of which are food crops. Honeybee colonies are dependent on having a healthy queen for their long-term survival since the queen bee is the only reproductive female in the colony. Thus, as the death or loss of the queen is of great negative impact for the well-being of a honeybee colony, beekeepers need to be aware if a queen has died in any of their hives so that appropriate remedial action can be taken. In this paper, we describe our approaches to using acoustic signals recorded in beehives and machine learning algorithms to identify whether beehives do or do not contain a healthy queen. Our results are extremely positive and should help beekeepers decide whether intervention is needed to preserve the colony in each of their hives. |
نوع الوثيقة: | article in journal/newspaper |
اللغة: | English |
تدمد: | 2079-9292 |
العلاقة: | https://www.mdpi.com/2079-9292/12/7/1627Test; https://doaj.org/toc/2079-9292Test; https://doaj.org/article/84d4456ac6da4cb8bf6801ad763fb966Test |
DOI: | 10.3390/electronics12071627 |
الإتاحة: | https://doi.org/10.3390/electronics12071627Test https://doaj.org/article/84d4456ac6da4cb8bf6801ad763fb966Test |
رقم الانضمام: | edsbas.73353C7 |
قاعدة البيانات: | BASE |
تدمد: | 20799292 |
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DOI: | 10.3390/electronics12071627 |