SBIR Phase II: Infrared Image Analysis to Assess Beehive Health for Crop Pollination

这一小型企业创新研究(SBIR)第二阶段项目的更广泛影响通过改善蜜蜂健康来保障国内食品供应。蜜蜂为美国国内三分之一的食物供应授粉，为美国经济贡献了超过150亿美元。尽管美国的蜜蜂数量处于20年来的最高水平，但维持蜜蜂存活的成本处于历史最高水平。该项目降低了商业养蜂人的劳动力成本，使他们能够将更多的时间用于修复显示出健康状况不佳和感染迹象的蜂箱。该产品可用于优化蜂箱位置，允许种植者使用最少的蜂箱授粉。随着种植者对蜂箱需求的减少，全国各地为农作物授粉的蜂箱数量将会减少，从而产生更强大的商业蜜蜂种群。这个拟议的项目扩展了第一阶段开发的研究，将产品从第一个版本成长为可扩展产品，其中包括预测模型改进、额外的数据收集、移动应用程序开发和额外的田间测试。第二阶段拨款的一个主要组成部分将是提高蜂巢强度模型的准确性和性能。在第二阶段，额外的数据收集将是重要的，以改进模型，使其在更广泛的环境条件下表现良好。到第二阶段结束时，软件的完全自动化使产品能够在任何时候使用。第二阶段工作的一个主要组成部分将是开发一个基于网络的移动应用程序，该应用程序可以使用智能手机摄像头附件拍摄红外照片，自动将图像上传到数据库，并提供对图像的实时分析。该项目是利用红外图像在作物授粉领域的一项突破，可用于改善许多垂直领域的热力学洞察。该奖项反映了NSF的法定使命，并通过使用基金会的智力优势和更广泛的影响审查标准进行评估，被认为值得支持。

The broader impact of this Small Business Innovation Research (SBIR) Phase II project safeguards domestic food supply by improving honeybee health. Honeybees pollinate 1/3 of domestic food supply and contribute more than $15 billion to the U.S. economy. Although honeybee populations are at a 20-year high in the U.S., the cost to keep them alive is at its historical peak. This project reduces labor costs for commercial beekeepers, allowing them to devote more time to restoring hives that show signs of poor health and infestation. The product can be used to optimize hive placement, allowing growers to pollinate using the smallest number of hives. As growers' demand for hives decreases, the number of hives shipped across the country to pollinate crops will be reduced, resulting in a more robust stock of commercial honeybees.This proposed project expands on research developed in Phase I to grow the product from its first version into a scalable product, which includes predictive model improvements, additional data collection, mobile app development and additional field testing. A major component of the Phase II grant will be improving accuracy and performance of the hive strength model. Additional data collection will be important in Phase II to improve the model to perform well in a wider range of ambient conditions. By the end of Phase II, full automation of the software allows for the product to be used at all times. A major component of the Phase II work will be the development of a web-based mobile application that can take infrared pictures using smartphone camera attachments, upload images automatically to a database, and provide real time analytics on the images. This project is a breakthrough in the crop pollination space using infrared imagery that can be adapted to improve thermodynamic insights across many verticals.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.