Real-time detection and localization based on acoustic characteristics of bees and wasps

Kunyang Liang; Olivier Laligant; Di Xiao

doi:10.1117/12.3050026

8 November 2024 Real-time detection and localization based on acoustic characteristics of bees and wasps

Kunyang Liang, Olivier Laligant, Di Xiao

Proceedings Volume 13416, Fourth International Conference on Advanced Algorithms and Neural Networks (AANN 2024); 134163S (2024) https://doi.org/10.1117/12.3050026
Event: 2024 4th International Conference on Advanced Algorithms and Neural Networks, 2024, Qingdao, China

Abstract

In recent years, there have been frequent incidents of wasps attacking bees raised by beekeepers, resulting in significant losses. To address this issue, I chose to compare the acoustic characteristics of wasps and bees, thereby constructing a dataset. By using the cosine distance to compare the similarity of similar features we can determine whether the sound is from a wasp or a bee. Additionally, the Time Difference of Arrival (TDOA) algorithm is used for tracking and localization. Through the use of Generalized Cross-Correlation (GCC), noise is mitigated, achieving relatively accurate localization in different Signal-to-Noise Ratio (SNR) conditions.

(2024) Published by SPIE. Downloading of the abstract is permitted for personal use only.

Citation Download Citation

Kunyang Liang, Olivier Laligant, and Di Xiao "Real-time detection and localization based on acoustic characteristics of bees and wasps", Proc. SPIE 13416, Fourth International Conference on Advanced Algorithms and Neural Networks (AANN 2024), 134163S (8 November 2024); https://doi.org/10.1117/12.3050026

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