Data compression for audio-based smart beekeeping
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Other Title
Authors
Shi, Guangyu
Song, Lei
Ardekani, Iman
Song, Lei
Ardekani, Iman
Author ORCID Profiles (clickable)
Degree
Grantor
Date
2025-06-30
Supervisors
Type
Conference Contribution - Paper in Published Proceedings
Ngā Upoko Tukutuku (Māori subject headings)
Keyword
New Zealand
beehive monitoring
honeybees (Apis mellifera)
MP3 (Audio coding standard)
FLAC (Audio coding standard)
data compression (Computer science)
audio data processing systems
apiculture industry
AI in agriculture
beehive monitoring
honeybees (Apis mellifera)
MP3 (Audio coding standard)
FLAC (Audio coding standard)
data compression (Computer science)
audio data processing systems
apiculture industry
AI in agriculture
ANZSRC Field of Research Code (2020)
Citation
Shi, G., Song, L., & Ardekani, I. (2025). Data compression for audio-based smart beekeeping. 3rd International Conference on Smart Sustainable Development (SSD 2025) https://doi.org/10.2991/978-94-6463-720-5_10
Abstract
This research addresses the challenges of audio data compression in beehive monitoring by exploring the feasibility and effectiveness of the Free Lossless Audio Codec. The study demonstrates that Free Lossless Audio Codec compression reduces resource consumption without compromising critical acoustic features or AI performance. The methodology integrates Free Lossless Audio Codec compression, feature extraction using Mel-Frequency Cepstral Coefficients to capture relevant acoustic characteristics, and machine learning models, specifically Support Vector Machines, to classify and analyze hive conditions. The results demonstrated that Free Lossless Audio Codec outperformed MPEG-1 Audio Layer 3 and uncompressed Waveform Audio File formats in maintaining the efficiency of audio signals and the integrity of critical acoustic features. Key metrics such as classifier accuracy, compression ratio, processing speed, and transmission speed were evaluated using data from multiple sources. These findings position Free Lossless Audio Codec as a highly effective solution for resource-efficient and reliable beehive monitoring systems.
Publisher
Atlantis Press - now part of Springer Nature
Permanent link
Link to ePress publication
DOI
https://doi.org/10.2991/978-94-6463-720-5_10
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Authors
Copyright notice
CC BY-NC Attribution-NonCommercial 4.0 International