A citizen science platform to sample beehive sounds for monitoring ANSP

被引：0

作者：

Yu, Baizhong ^{[1
,2
]}

Huang, Xinqiu ^{[3
]}

Sharif, Muhammad Zahid ^{[1
,2
]}

Di, Nayan ^{[1
,2
]}

Liu, Fanglin ^{[1
,2
]}

机构：

[1] Chinese Acad Sci, Anhui Inst Opt & Fine Mech, Hefei Inst Phys Sci, Hefei 230031, Peoples R China

[2] Univ Sci & Technol China, Hefei 230027, Peoples R China

[3] Yunnan Acad Agr Sci, Sericulture & Apiculture Res Inst, Mengzi 661100, Peoples R China

来源：

JOURNAL OF ENVIRONMENTAL MANAGEMENT | 2025年 / 375卷

关键词：

Beehive sound; Citizen science; Agricultural nonpoint source pollution; Machine learning; POLLUTION; HONEYBEES; HEALTH;

D O I：

10.1016/j.jenvman.2025.124247

中图分类号：

X [环境科学、安全科学];

学科分类号：

08 ; 0830 ;

摘要：

Honey bees usually produce particular sound when they are exposed to air pollution. Based on this principle, we create a citizen science platform to monitor Agricultural Nonpoint Source Pollution (ANSP) based on beehive sounds. Here we show the basic functions of the platform, and illustrate its workflow: sampling and uploading data by beekeepers, automated detection of target compounds from beehive sound recordings, and the outcome of which can be analysed with respect to the motivating management objective. With such a comprehensive platform for moving from raw data collection to analysis, ANSP monitoring programs will be greatly improved in to systematically characterize ecological processes and inform management decisions. Future endeavors will concentrate on fostering collaboration between public participants and scientists to facilitate automated detection of target compounds.

引用

页数：9

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