E-viri
-
Zhu, Yi; Abdollahi, Mahsa; Maucourt, Segolene; Coallier, Nico; Guimaraes, Heitor R.; Giovenazzo, Pierre; Falk, Tiago H.
2023 IEEE International Workshop on Metrology for Agriculture and Forestry (MetroAgriFor), 2023-Nov.-6Conference Proceeding
Winter mortality is one of the main causes of beehive loss. However, very limited tools can be used by beekeepers to identify the high-risk colonies at an early stage. In this study, we propose a multi-modal sensor (audio, humidity, temperature) based system to predict the beehive winter survivability. More specifically, we first propose a multi-modal feature set, which is shown to be highly correlated with winter survival rate, and develop a machine learning model to further detect the hives that are less likely to survive the winter. Our top-performing model achieves an AUC-ROC score of 0.730 based on one-year-long data collected from 45 hives located in two different apiaries in Canada. Our findings show the feasibility of capturing high-risk hives at the early stage using multi-modal sensor data. Furthermore, we highlight the importance of bee audio in measuring survivability over other more widely-used modalities. Future study will focus on improving the generalizability of the prediction model.
Vnos na polico
Trajna povezava
- URL:
Faktor vpliva
Dostop do baze podatkov JCR je dovoljen samo uporabnikom iz Slovenije. Vaš trenutni IP-naslov ni na seznamu dovoljenih za dostop, zato je potrebna avtentikacija z ustreznim računom AAI.
Leto | Faktor vpliva | Izdaja | Kategorija | Razvrstitev | ||||
---|---|---|---|---|---|---|---|---|
JCR | SNIP | JCR | SNIP | JCR | SNIP | JCR | SNIP |
Baze podatkov, v katerih je revija indeksirana
Ime baze podatkov | Področje | Leto |
---|
Povezave do osebnih bibliografij avtorjev | Povezave do podatkov o raziskovalcih v sistemu SICRIS |
---|
Vir: Osebne bibliografije
in: SICRIS
To gradivo vam je dostopno v celotnem besedilu. Če kljub temu želite naročiti gradivo, kliknite gumb Nadaljuj.