基于无人飞行器的入侵飞虫自主追踪系统

IF 7.7 1区 农林科学 Q1 AGRICULTURE, MULTIDISCIPLINARY Computers and Electronics in Agriculture Pub Date : 2024-11-22 DOI:10.1016/j.compag.2024.109616
Jeonghyeon Pak , Bosung Kim , Chanyoung Ju , Hyoung Il Son
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引用次数: 0

摘要

亚洲大黄蜂或黄腿大黄蜂(Vespa velutina nigrithorax)是蜜蜂(Apis mellifera L.)的一种全球性天敌,由于气候变化迅速而变得广泛传播。在此,我们提出了一种定位系统,通过将无人驾驶飞行器与三坐标系统相结合,跟踪带有无线电标签的大黄蜂并发现大黄蜂蜂巢。利用大黄蜂的归巢本能,我们将实验系统地分为行为实验、地面实况实验和定位实验。根据实验结果,我们成功地发现了所测试的五只大黄蜂中的两只的蜂巢。此外,通过对实验结果的综合分析,我们对大黄蜂的飞行模式和行为有了更深入的了解。这项研究成果证明了将无人飞行器与无线电遥测技术整合在一起进行精确目标跟踪和生态系统管理的有效性,为减轻入侵物种对蜜蜂种群的影响提供了一种强有力的工具。
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Unmanned Aerial Vehicle-based Autonomous Tracking System for Invasive Flying Insects
The Asian hornet or yellow-legged hornet, Vespa velutina nigrithorax, is a global predator of honeybees (Apis mellifera L.) that has become widespread owing to rapid climate change. Herein, we propose a localization system for tracking radio-tagged hornets and discovering hornet hives by combining unmanned aerial vehicles with a trilateration system. By leveraging the homing instinct of hornets, we systematically structured our experiments as a behavioral experiment, ground-truth experiment, and localization experiment. According to the experimental results, we successfully discovered the hives of two of the five hornets tested. Additionally, a comprehensive analysis of the experimental outcomes provided insights into hornet flight patterns and behaviors. The results of this research demonstrate the efficacy of integrating UAVs with radio telemetry for precision object tracking and ecosystem management, offering a robust tool for mitigating the impacts of invasive species on honeybee populations.
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来源期刊
Computers and Electronics in Agriculture
Computers and Electronics in Agriculture 工程技术-计算机:跨学科应用
CiteScore
15.30
自引率
14.50%
发文量
800
审稿时长
62 days
期刊介绍: Computers and Electronics in Agriculture provides international coverage of advancements in computer hardware, software, electronic instrumentation, and control systems applied to agricultural challenges. Encompassing agronomy, horticulture, forestry, aquaculture, and animal farming, the journal publishes original papers, reviews, and applications notes. It explores the use of computers and electronics in plant or animal agricultural production, covering topics like agricultural soils, water, pests, controlled environments, and waste. The scope extends to on-farm post-harvest operations and relevant technologies, including artificial intelligence, sensors, machine vision, robotics, networking, and simulation modeling. Its companion journal, Smart Agricultural Technology, continues the focus on smart applications in production agriculture.
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