As a guest user you are not logged in or recognized by your IP address. You have
access to the Front Matter, Abstracts, Author Index, Subject Index and the full
text of Open Access publications.
Prediction of Honeybee Swarms Using Audio Signals and Convolutional Neural Networks
Stenford Ruvinga, Gordon Hunter, Jean-Christophe Nebel, Olga Duran
Honeybees are of vital importance to both agriculture and ecology. Unfortunately, their populations have been in serious decline over recent years. Swarms from hives are both of great importance to wider success of a colony and of major significance to beekeepers. In this paper, we contribute to the challenge of predicting when a swarm is going to occur. We have employed a Convolutional Neural Network (CNN) approach applied to audio data recorded from hives. Our initial results are extremely encouraging, since they allow us to distinguish hives which are preparing to swarm from those which are not with high levels of accuracy.
IOS Press c/o Accucoms US, Inc.
For North America Sales and Customer Service
West Point Commons
Suite 201
Lansdale PA 19446
Tel.: +1 866 855 8967
Fax: +1 215 660 5042
[email protected]
(Journals only)
This website uses cookies
We use cookies to provide you with the best possible experience. They also allow us to analyze user behavior in order to constantly improve the website for you. Info about the
privacy policy
of IOS Press.
This website uses cookies
We use cookies to provide you with the best possible experience. They also allow us to analyze user behavior in order to constantly improve the website for you. Info about the
privacy policy
of IOS Press.
