SBIR Phase I: Deep Learning Hydroponic Forecasting System for Precision Farming
SBIR Phase I: Deep Learning Hydroponic Forecasting System for Precision Farming
批准号:
1913616
负责人:
Graham Smith
金额:
$22.31万
依托单位:
依托单位国家:
美国
项目类别:
Standard Grant
财政年份:
2019
资助国家:
美国
项目状态:
已结题
起止时间:
2019-07-01 至 2020-03-31
中文摘要
这一小型企业创新研究(SBIR)项目的更广泛影响/商业潜力是,通过降低水培农业的准入门槛,将城市农业作为一种可行的新产业引入小企业。传统的水培农业需要复杂的系统,其中各种变量必须由熟练的操作员监测和控制,以应对整个植物生命周期的变化,并且必须注意精确地控制这些变量。这种对受过技术教育的农民进行严格管理的需要限制了城市水培农业的广泛采用。该项目将产生一个全自动化的精准农业平台,管理城市农业作业的全部范围。该平台利用水培种植区的趋势来预测系统变量和作物生长的变化,并自动和智能地调整关键参数,以优化资源使用和最大限度地提高产量。由于精密剂量计不需要广泛的农业专业知识,它将使小规模农民、餐馆老板和私人消费者能够接触到水培农业。一旦非工业经营有可能建立水培,城市农场就可以将新鲜有机农产品的来源置于食品沙漠的中心,而不需要依赖转基因生物、除草剂或杀虫剂。这个SBIR第一阶段项目建议开发一个水培耕作控制平台,该平台可以智能地预测作物生长,预测重要的系统变量,包括pH值和电导率,并根据预测调整环境参数,精确调整种植区域,以最大限度地提高作物产量,同时最大限度地减少资源浪费。在美国,超过十分之一的家庭在没有足够的营养或依赖加工食品的情况下生活,导致了整个城市环境中粮食不安全和肥胖的双重危机。由于它们不像传统农业那样需要广泛的土地和水,水培作业可以在城市环境中扎根,那里获得新鲜、营养丰富的农产品受到限制。该项目将针对水培农业的两个方面:作物产量和系统参数,这两个方面对开发精确农具至关重要。通过分析植物生长趋势,该平台将为有关资源使用的决策提供信息,允许种植者调整系统参数,以促进最成功的作物。最终平台将直接解决城市地区食物沙漠的问题,提供一种在当地种植新鲜农产品的方法,降低标准农业操作的生产成本,并优化水培系统的作物产量。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。
英文摘要
The broader impact/commercial potential of this Small Business Innovation Research (SBIR) project is the introduction of urban farming as a viable new industry for small businesses by driving down the barrier of entry to hydroponic farming. Conventional hydroponic farming necessitates complex systems in which a variety of variables must be monitored and controlled by a skilled operator in response to changes throughout the plant lifecycle and care must be taken to control these variables precisely. This need for demanding management by a technically-educated farmer has restricted the widespread adoption of urban hydroponic farming. This project will result in a fully-automated precision farming platform managing the full scope of urban farming operations. The platform uses trends in a hydroponic grown zone to forecast changes to system variables and crop growth and to automatically and intelligently adjust vital parameters to optimize resource usage and maximize output. Because the precision doser will not require extensive agricultural expertise, it will make hydroponic farming accessible to small-scale farmers, restaurateurs, and private consumers. Once it becomes possible for non-industrial operations to establish hydroponics, urban farms can place sources of fresh, organic produce right in the heart of food deserts without reliance on GMOs, herbicides, or pesticides.This SBIR Phase I project proposes to develop a hydroponics farming control platform which intelligently predicts crop growth, forecasts vital system variables including the pH and electrical conductivity, and tunes environmental parameters in accordance with the forecasts, precisely adjusting the growing zone to maximize crop output while minimizing wasted resources. More than one-tenth of households in the United States cope without adequate nutrition or rely on processed foods, leading to the dual crisis of food insecurity and obesity throughout urban environments. Because they do not have the same extensive land and water requirements as traditional farming, hydroponic operations can take root in urban environments where access to fresh, nutritious produce is restricted. This project will target two aspects of hydroponic agriculture essential to the development of a precision farming tool: crop output and system parameters. By analyzing trends in plant growth, the platform will inform decision-making around resource usage, allowing the grower to adjust system parameters that promote the most successful crops. The final platform will directly address the concern of food deserts in urban localities, by offering a means to grow fresh produce locally, reducing the production costs of standard farming operations, and optimizing crop output in hydroponic systems.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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