SBIR Phase II: AI-based automated, portable, and high-throughput platform for early identification and characterization of potentially harmful microorganisms in aquaculture

SBIR 第二阶段：基于人工智能的自动化、便携式和高通量平台，用于水产养殖中潜在有害微生物的早期识别和表征

• 批准号: 2052393
• 负责人: Maxim Batalin
• 金额: $ 100万
• 依托单位: LUCENDI, INC.
• 依托单位国家: 美国
• 项目类别: Cooperative Agreement
• 财政年份: 2021
• 资助国家: 美国
• 起止时间: 2021-09-01 至 2025-08-31
• 项目状态: 未结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=2052393&HistoricalAwards=false
• 关键词: SBIR; Phase; II; AI; based

The broader impact/commercial potential of this Small Business Innovation Research (SBIR) Phase II project is the development of a cost-effective, high-performance platform to monitor and characterize plankton and other microorganisms in water. Some of these aquatic microorganisms may be harmful or even fatal resulting in significant public health concerns and economic consequences, such as billions lost annually in the aquaculture industry due to harmful algal blooms and sea lice. The current state of the art in monitoring technology includes laborious and expensive manual sample collections and evaluation. In contrast, the proposed platform may enable low-cost, portable and fast monitoring, as well as automated characterization of harmful aquatic microorganisms. Furthermore, this platform will enable a much wider application of the technology to other markets such as marine biology science and STEM education, general monitoring of particles and pathogens at the water treatment facilities, and production algae monitoring. The proposed technology is envisioned to have a significant societal impact and commercial potential.This project may result in a versatile, cost-effective, and high-throughput aquatic microobjects monitoring instrument. The instrument will have a wide spectrum of applications and initial focus on aquaculture market. The technology will initially focus on early identification of specific microorganisms, such as sea lice and harmful algae as they are detrimental to the wellbeing of aquaculture animals. This demonstration will provide high quality data at an affordable price to ensure confidence and credibility to aquaculture farmers, marine scientists, and other users interested in aquatic microobjects characterization. To accomplish this plan, several operating regimes will be implemented enabling the device to switch from high-resolution (monitoring harmful algae) to high-throughput (identifying sea lice). An autofluorescent camera module will be developed to further assist with differentiating microorganisms. Next, an innovative neural network framework will be developed and tested for identification of different types of sea lice and harmful algae. Finally, the system will be integrated into an environmentally protected enclosure and rigorously tested in laboratory, as well as in-field in realistic conditions. At the end of the Phase II program a prototype will be completed that will be designed in coordination with aquaculture partners and prospective users.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.

这个小企业创新研究（SBIR）第二阶段项目的更广泛的影响/商业潜力是开发一个具有成本效益的高性能平台，以监测和表征水中的浮游生物和其他微生物。这些水生微生物中的一些可能是有害的，甚至是致命的，从而导致重大的公共卫生问题和经济后果，例如由于有害的藻华和海虱，水产养殖业每年损失数十亿美元。监测技术的当前状态包括费力且昂贵的手动样品收集和评估。相比之下，拟议的平台可以实现低成本，便携式和快速监测，以及有害水生微生物的自动化表征。此外，该平台将使该技术更广泛地应用于其他市场，如海洋生物科学和STEM教育，水处理设施的颗粒和病原体的一般监测以及生产藻类监测。该技术具有巨大的社会影响和商业潜力，有望成为一种多功能、高性价比、高通量的水生微物体监测仪器。 该工具将有广泛的应用范围，最初的重点是水产养殖市场。该技术最初将侧重于早期识别特定微生物，如海虱和有害藻类，因为它们对水产养殖动物的健康有害。该演示将以可承受的价格提供高质量的数据，以确保水产养殖户，海洋科学家和其他对水生微物体表征感兴趣的用户的信心和可信度。为了实现这一计划，将实施几种操作制度，使该设备能够从高分辨率（监测有害藻类）切换到高通量（识别海虱）。 将开发一种自动荧光相机模块，以进一步帮助区分微生物。接下来，将开发和测试一个创新的神经网络框架，用于识别不同类型的海虱和有害藻类。最后，该系统将被集成到一个环境保护的外壳中，并在实验室和实际条件下进行严格的测试。在第二阶段计划结束时，将与水产养殖合作伙伴和潜在用户协调设计完成一个原型。该奖项反映了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。