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I-Corps: Intelligent Hydroponics Growing Platform for Sustainable Agriculture

I-Corps: Intelligent Hydroponics Growing Platform for Sustainable Agriculture
I-Corps:可持续农业的智能水培种植平台
批准号:
2345854
负责人:
Hongbo Zhang
金额:
$5.0万
依托单位国家:
美国
项目类别:
Standard Grant
财政年份:
2024
资助国家:
美国
项目状态:
未结题
起止时间:
2024-02-01 至 2025-01-31

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中文摘要
翻译
I-Corps项目的更广泛影响/商业潜力在于,与土壤生长相比,它有望提高粮食产量和节约用水。该技术的自动化功能也可能有助于解决与传统农业相关的劳动力短缺挑战。传感器数据可以降低害虫控制成本,这是迄今为止与水培农场相关的主要挑战。自动化水培种植方法可以提高农业的可持续性,并支持室内和室外水培生长系统,使农民能够更有效地种植丰富多样的作物。这个I-Corps项目是基于一种非接触式微型激光成像方法来检测精确的水培营养水平。该非接触式传感器检测生长介质反射和散射效率以表征成分。该技术的特点是集成了多个数据源,以实现最优的增长控制决策。传感器数据包括温度、湿度、供水量、光照、植物压力、疾病状况和水位。该数据用于使用深度强化学习方法生成智能植物生长模型。一种不含化学物质的紫外线c (UVC)面板将用于监测害虫控制,这是种植有机作物的关键挑战之一。预计该技术可将人工成本降低40%,将资源(如水、营养和电力)的利用率降低15%。该奖项反映了美国国家科学基金会的法定使命,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。
英文摘要
The broader impact/commercial potential of this I-Corps project is that it is expected to increase food yield and water savings in contrast to soil-based growth. The automation function of the technology may also help resolve the labor shortage challenge associated with traditional farming. Sensor data could reduce pest control costs, which to date has been a major challenge associated with hydroponics farms. Automated hydroponics growing methods could improve the sustainability of agriculture and support both indoor and outdoor hydroponics growth systems, enabling farmers to grow a rich variety of crops more efficiently. This I-Corps project is based on a contactless miniature laser imaging method to detect precise hydroponics nutrient levels. The contactless sensor detects growth media reflection and scattering efficiency to characterize composition. The technology features integration of multiple sources of data for optimal growth control decision-making. Sensor data includes temperature, humidity, supplied water amount, light, plant stress, disease conditions and water level. This data is used to generate a smart plant growth model using a deep reinforcement learning method. A chemical-free, ultraviolet-C (UVC) panel will be used to monitor pest control, one of the key challenges of growing organic crops. It is expected that the technology may reduce labor costs by 40% and the utilization of resources (e.g. water, nutrition and electricity) by 15%.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.
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