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: FARMSENSE INC.
• 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
• 起止时间: 2023-08-01 至 2024-05-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=2233676&HistoricalAwards=false
• 关键词: SBIR; Phase; Automatic; Digital; Classification

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.

这个小型企业创新研究（SBIR）第一阶段项目的更广泛的影响/商业潜力将是创建一个端到端的数字蚊子监测平台，可以支持病媒控制区的重要工作。有效的病媒控制对于减少西尼罗河、东部马脑炎和寨卡等疾病的传播至关重要。目前，蚊子监测通常使用机械诱捕器进行，这需要大量劳动力才能生存。该项目将大大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，同时减少劳动力成本和必须使用的杀虫剂数量。减少杀虫剂的用量对整个社会有进一步的积极好处：它将减少污染和益蜂的群体崩溃失调。除了区域范围的监测之外，该项目中创建的硬件/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，该解决方案可用于测量新的引诱剂或驱避剂的有效性。这个小型企业创新研究（SBIR）第一阶段项目将研究改进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，以支持灭蚊工作。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因为它们整天都开着。由于该团队是在真实的时间感测昆虫，他们有独特的能力，启动气缸和风扇/光采样昆虫到达的分布。这个奖项反映了NSF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。