SBIR Phase II: Low-Power, Wireless Crop Quality Sensors for Grain Quality Preservation and Storage Automation

这一小企业创新研究（SBIR）第二阶段项目的更广泛影响/商业潜力是减少由于毒素和虫害造成的收获后损失，同时增加农民的回报。 在美国，由于毒素、昆虫和水分管理不善，每年损失30亿至50亿美元的作物价值，而这些损失本可以通过在产品储存期间引入负担得起且易于使用的监测技术来预防。 此外，生产农业中二氧化碳水平的上升造成了全球温室气体排放量的14%。 该项目将验证低功耗无线传感器的可行性，该传感器可以检测谷物储存条件。 该项目还将使粮食市场的买家能够确保他们购买的粮食实际上来自实施可持续做法的田地。 这项技术将有助于验证在整个供应链中跟踪谷物的可行性，以围绕可持续性验证的谷物创建信任和新的商业模式。 该小型企业创新研究（SBIR）第二阶段项目旨在推进物联网自动化和无线传感器应用于生产农业和采后供应链。 由于时间负担和缺乏决策所需的信息，农业生产的某些手工流程非常费力。 其中一个过程是监测农场仓库、商业仓库和驳船中的谷物资产，尽管这对全球粮食供应的安全很重要。 该技术专注于感知损失和损坏风险，并将数据连接并转化为自动化机会。 目前存在基于电缆的监控解决方案，但由于物理安装限制、电力/电力限制和投资成本，采用受到限制。 该项目将验证低功耗无线传感器的可行性，这些传感器可以检测谷物状况并持续整个收获后周期（18个月）。 这种设备将为跟踪整个农业价值链中的谷物质量创造机会，推动其目前在农场谷物箱中的使用。 通过表征和测试智能内核传感器，该项目将提供谷物供应链中跟踪机制的商业模型应用。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。

The broader impact/commercial potential of this Small Business Innovation Research (SBIR) Phase II project is to reduce postharvest loss due to toxins and insect damage while increasing the returns for farmers. In the US, an annual $3-5 billion dollars of crop value is lost due to toxin, insect and moisture mismanagement that could have been prevented through the introduction of affordable and accessible monitoring technology during product storage. Additionally, rising carbon dioxide levels in production agriculture create 14% of global greenhouse gas emissions. This project will validate the feasibility of low-power, wireless sensors that can detect grain storage conditions. The project will also enable buyers in the grain marketplace to ensure that the grain they are purchasing is, in fact, from fields where sustainable practices are implemented. This technology will help validate the feasibility of tracking grain across the supply chain to create trust and new business models around sustainability-verified grain. This Small Business Innovation Research (SBIR) Phase II project seeks to advance internet of things automation and wireless sensor applications as applied to production agriculture and the postharvest supply chain. There are certain manual processes of farm production that are strenuous due to time burdens and the lack of information available to make decisions. One such process is monitoring grain assets in farm bins, commercial storage, and barges, though this is important for the safety of the global food supply. This technology is focused on sensing for loss and spoilage risks and connecting and turning the data into automation opportunities. Cable-based monitoring solutions currently exist, but adoption is restricted due to physical installation limitations, electricity/power constraints, and investment costs. This project will validate the feasibility of low-power, wireless sensors that can detect grain conditions and last a full postharvest cycle (18 months). Such a device will create opportunities to track grain qualities across the agriculture value chain, advancing its current use in on-farm grain bins. By characterizing and testing smart kernel sensors this project will provide business model applications of tracking mechanisms in the grain supply chain.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.