论文标题
开发和测试新型自动化昆虫捕获模块,用于采样和转移
Development and Testing of a Novel Automated Insect Capture Module for Sample Collection and Transfer
论文作者
论文摘要
迫切需要在疾病监测中进行有效的工具,以帮助建模和预测疾病的传播。昆虫传播疾病的传播引起了公共卫生官员和整个医学与研究社区的严重关注。在这种传播的建模中,我们面对(1)我们能够在容易发生疾病的环境中采样昆虫向量的频率,(2)(2)设置和检索陷阱等监视设备(如陷阱)以及(3)分析昆虫样品的返回时间以及确定是否存在感染性疾病的返回时间。为了帮助解决这些瓶颈,我们在本文中介绍了新型自动化昆虫捕获模块(ICM)或陷阱的设计,制造和测试,旨在提高通过空中机器人从环境中收集的样品的转移速率。 ICM具有紫外线吸引剂,被动捕获机构,可以打开并关闭以获取昆虫的面板,以及用于自动操作和数据记录的小型板载计算机。同时,ICM设计为可访问;它是小规模,轻巧且低成本的,可以与市售的空中机器人集成。室内和室外实验验证了ICM在昆虫捕获和安全运输方面的可行性。该设备可以通过利用自动机器人技术来帮助医学和研究社区,使我们更近一步地实现完全自主和可扩展的流行病学。
There exists an urgent need for efficient tools in disease surveillance to help model and predict the spread of disease. The transmission of insect-borne diseases poses a serious concern to public health officials and the medical and research community at large. In the modeling of this spread, we face bottlenecks in (1) the frequency at which we are able to sample insect vectors in environments that are prone to propagating disease, (2) manual labor needed to set up and retrieve surveillance devices like traps, and (3) the return time in analyzing insect samples and determining if an infectious disease is spreading in a region. To help address these bottlenecks, we present in this paper the design, fabrication, and testing of a novel automated insect capture module (ICM) or trap that aims to improve the rate of transferring samples collected from the environment via aerial robots. The ICM features an ultraviolet light attractant, passive capture mechanism, panels which can open and close for access to insects, and a small onboard computer for automated operation and data logging. At the same time, the ICM is designed to be accessible; it is small-scale, lightweight and low-cost, and can be integrated with commercially available aerial robots. Indoor and outdoor experimentation validates ICM's feasibility in insect capturing and safe transportation. The device can help bring us one step closer toward achieving fully autonomous and scalable epidemiology by leveraging autonomous robots technology to aid the medical and research community.