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SBIR Phase I: Automatic, Digital Classification and Counting of Mosquitos to Allow More Effective Vector Control

SBIR Phase I: Automatic, Digital Classification and Counting of Mosquitos to Allow More Effective Vector Control
SBIR 第一阶段:对蚊子进行自动数字分类和计数,以实现更有效的病媒控制
批准号:
2233676
负责人:
Shailendra Singh
金额:
$27.5万
依托单位:
依托单位国家:
美国
项目类别:
Standard Grant
财政年份:
2023
资助国家:
美国
项目状态:
已结题
起止时间:
2023-08-01 至 2024-05-31

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中文摘要
翻译
这项小企业创新研究(SBIR)第一阶段项目的更广泛影响/商业潜力将是创建一个端到端的数字蚊子监测平台,以支持病媒控制地区的重要工作。有效的病媒控制对于减少西尼罗河、东马脑炎和寨卡等疾病的传播至关重要。目前,蚊子监测通常是使用机械陷阱进行的,这需要大量的劳动力才能存活。该项目将显著提高昆虫监测的质量和便利性,从而更有效地控制蚊子。这一努力将改善灭蚊工作,同时减少人工成本和必须使用的杀虫剂数量。减少农药用量对整个社会有进一步的积极好处:它将减少污染和有益蜜蜂的蜂群衰竭失调。除了区域范围的监测之外,这个项目中创建的硬件/算法/表示/数据模型将对研究蚊子传播疾病的科学家有用。例如,这些溶液可以用来测量一种新的引诱剂或驱虫剂的有效性。这个小企业创新研究(SBIR)第一阶段项目将研究提高最先进的蚊子分类和计数技术,目标是建立一个平台,允许廉价、实时的昆虫监测,以支持蚊子抑制工作。虽然数字传感器有可能消除人工计数昆虫的负担,但目前病媒控制技术人员仍然必须经常访问陷阱以更换二氧化碳(CO2)气瓶(诱饵)和电池。二氧化碳和电池消耗如此之快的原因是它们整天都是开着的。因为这个团队是实时感知昆虫的,所以他们有独特的能力来驱动气瓶和风扇/灯来采样昆虫到达的分布。该团队还可以优化节约资源和蚊子密度测量精度之间的权衡。该奖项反映了美国国家科学基金会的法定使命,并通过使用基金会的知识价值和更广泛的影响审查标准进行评估,被认为值得支持。
英文摘要
The broader impact/commercial potential of this Small Business Innovation Research (SBIR) Phase I project will be the creation of an end-to-end platform for digital mosquito surveillance that can support the vital work of vector control districts. Effective vector control is essential to reducing the spread of diseases including West Nile, Eastern Equine Encephalitis and Zika. Currently, mosquito surveillance is typically done using mechanical traps, which require significant labor to survive. The project will significantly improve the quality and ease of insect surveillance, thus allowing more effective mosquito control. This effort will improve mosquito suppression efforts, while reducing labor costs and the volume of pesticides that must be used. Reducing the volume of pesticides has further positive benefits to society at large: it will reduce pollution and colony collapse disorder in beneficial bees. Beyond area-wide surveillance, the hardware/ algorithms/ representations/ data-models created in this project will be useful to scientists that study mosquito-vectored diseases. For example, the solutions can be used to measure the effectiveness of a new attractant or repellent.This Small Business Innovation Research (SBIR) Phase I project will investigate techniques to improve state-of-the-art mosquito classification and counting, with the goal of producing a platform that allows inexpensive, real-time, insect surveillance to support mosquito suppression efforts. Although digital sensors have the potential to remove the burden of manually counting the insects, currently the vector control technicians must still visit the traps frequently to change the carbon dioxide (CO2) gas cylinders (the lure) and the batteries. The reason why both CO2 and batteries deplete so rapidly is because they are left on all day. Because the team is sensing insects in real time, they have the unique ability to actuate the gas cylinders and fan/light to sample the distribution of insect arrivals. The team can also optimize the trade-off between conserving resources and the precision of measurement of mosquito density.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.
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