| Paper ID | F-3-3.3 |
| Paper Title |
An Acoustic Signal Processing System for Identification of Queen-less Beehives |
| Authors |
Rui Peng, Iman Ardekani, Hamid Sharifzadeh, Unitec Institute of Technology, New Zealand |
| Session |
F-3-3: Signal Processing Systems for AI |
| Time | Thursday, 10 December, 17:30 - 19:30 |
| Presentation Time: | Thursday, 10 December, 18:00 - 18:15 Check your Time Zone |
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All times are in New Zealand Time (UTC +13) |
| Topic |
Signal Processing Systems: Design and Implementation (SPS): |
| Abstract |
This paper proposes a machine learning system for identification of queen-less beehives by using audio signal enhancement methods and neural networks. In the proposed system, noisy audio signals captured from beehives are enhanced by using a Wiener filter; Improved Mel-frequency Cepstrum Coefficient (IMFCC) of the enhanced signals are then extracted and fed to a neural network. The result shows that the application of the proposed filter can improve the classification accuracy by at least 12%. The classification accuracy depends on the SNR of the input audio signal. |