Honeybees are one of the most important pollinating species in agriculture. Every three out of four crops have honeybee as their sole pollinator. Since 2006 there has been a drastic decrease in the bee population which is attributed to Colony Collapse Disorder(CCD). The bee colonies fail/ die without giving any traditional health symptoms which otherwise could help in alerting the Beekeepers in advance about their situation.
Electronic Beehive Monitoring System has various sensors embedded in it to extract video, audio and temperature data that could provide critical information on colony behavior and health without invasive beehive inspections. Previously, significant patterns and information have been extracted by processing the video/image data, but no work has been done using audio data. This research inaugurates and takes the first step towards the use of audio data in the Electronic Beehive Monitoring System (BeePi) by enabling a path towards the automatic classification of audio samples in different classes and categories within it. The experimental results give an initial support to the claim that monitoring of bee buzzing signals from the hive is feasible, it can be a good indicator to estimate hive health and can help to differentiate normal behavior against any deviation for honeybees.
| Identifer | oai:union.ndltd.org:UTAHS/oai:digitalcommons.usu.edu:etd-8156 |
| Date | 01 May 2018 |
| Creators | Amlathe, Prakhar |
| Publisher | DigitalCommons@USU |
| Source Sets | Utah State University |
| Detected Language | English |
| Type | text |
| Format | application/pdf |
| Source | All Graduate Theses and Dissertations |
| Rights | Copyright for this work is held by the author. Transmission or reproduction of materials protected by copyright beyond that allowed by fair use requires the written permission of the copyright owners. Works not in the public domain cannot be commercially exploited without permission of the copyright owner. Responsibility for any use rests exclusively with the user. For more information contact digitalcommons@usu.edu. |
Page generated in 0.0021 seconds