A citizen science platform to sample beehive sounds for monitoring ANSP

文献类型： 外文期刊

第一作者： Yu, Baizhong

作者： Yu, Baizhong;Sharif, Muhammad Zahid;Di, Nayan;Liu, Fanglin;Yu, Baizhong;Sharif, Muhammad Zahid;Di, Nayan;Liu, Fanglin;Huang, Xinqiu

作者机构：

关键词： Beehive sound; Citizen science; Agricultural nonpoint source pollution; Machine learning

期刊名称：JOURNAL OF ENVIRONMENTAL MANAGEMENT （ 影响因子：8.4； 五年影响因子：8.6 ）

ISSN： 0301-4797

年卷期： 2025 年 375 卷

页码：

收录情况： SCI

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.

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