SBIR Phase II: Smart Sensor for Precision Agriculture

SBIR第二阶段项目将把学术界使用的创新技术部署到一个具有成本效益的解决方案中，以提高农业实践的精度和效率。设想的产品是普通农民增加产量、减少不必要和不可预测的成本、减少对环境的负面影响并导致餐桌上更高质量的食物的工具。通过将曾经复杂、缓慢、不准确的昆虫识别实践转换为自动化和高度准确的真实的时间，这项技术将成为自动化和数据驱动的工业化浪潮的一部分，改变农业部门。对虫害的快速反应将使农民能够更好地针对他们的反应，最终使农业更加高效和可持续。有效的农业虫害防治对种植者防止主要作物损失至关重要。某些昆虫害虫造成了如此严重的作物损害，这促使种植者投资于昂贵而耗时的措施，以尽量减少害虫的影响。种植者对害虫的反应是时间敏感的;处理应用的时间将直接决定其有效性。所提出的技术是一种创新的基于地面的传感器系统，其沿着实时检测多个空气传播的害虫及其地理位置信息。它具有区分和识别飞行中检测到的不同昆虫种类的能力。对害虫位置的即时了解允许有针对性的喷洒，而不是喷洒整个田地。有针对性的喷洒减少了不必要的喷洒，并促进了更可持续的虫害处理做法。足够准确的低成本传感器最终使种植者提前几步解决问题，引导他们做出更明智的处理决策，例如选择一天中的时间以避免伤害有益的害虫和减轻漂移。该传感器取代并完全自动化了目前用于监测作物田间昆虫活动的方法，效率更高。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。

This SBIR Phase II project will deploy an innovative technology used in academia into a cost-effective solution for better precision and efficiency in agricultural practices. The envisioned product is a tool for ordinary farmers to increase their production and reduce unnecessary and unpredictable costs, reducing negative impacts on the environment and leading to higher quality food on the table. By converting once complicated, slow, inaccurate practices of insect identification to automated and highly accurate and in real time, this technology will be a part of the automation and data driven industrialization wave transforming the agricultural sector. The quick reaction to pest infestation will allow farmers to better target their response, ultimately making farming more efficient and sustainable. Effective pest control in agriculture is imperative for growers to prevent major crop loss. Certain insect pests are responsible for such significant crop damage which provokes growers to invest in expensive and time-consuming measures to minimize pest effects. The reaction of the grower to the pest is time-sensitive; the timing of the treatment application will directly determine its effectiveness. The proposed technology is an innovative ground-based sensor system that detects plurality of airborne pests in real-time along with their geolocation information. It has capabilities for differentiation and identification of different insect species detected in flight. The instantaneous knowledge of the location of the pest allows for a targeted spray rather than spraying an entire field. Targeted sprays reduce unnecessary spraying and promote more sustainable pest treatment practices. The low-cost sensor that is adequately accurate finally places growers a few steps ahead of the problem, leading them to make wiser treatment decisions such as choosing the time of day to avoid harming beneficial pests and for mitigating drift. The sensor replaces and completely automates the current methods for monitoring insect activity in the crop field, with much better efficiency.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.