CyberSEES: Type2: Collaborative Research: SmartFarm - Research and Education for Sustainable Agriculture Practices

生态可持续性在很大程度上取决于世界粮食生产是否有能力利用既能加强环境管理又能提高农业生产力的新技术来管理日益有限的自然资源（如可耕地和水）。 为了提高农业生产力和生产力的可持续增长，种植者越来越多地转向环境传感器测量、数据采集和数据分析。然而，到目前为止，这些工具还没有得到小农农业企业的广泛使用。 重要的是，个体种植者和牧场主在商业和研究领域的许多最新进展中服务不足，这些进展使数据分析成为简单的“黑匣子”最终用户产品。目前为这些选民提供的决策支持服务是各种有限的，专有的，复杂的，昂贵的，要求种植者放弃对他们的数据的控制，或者不是广泛可用的。 因此，该项目调查了一个名为SmartFarm的综合研究，教育和推广计划，该计划将计算机科学，农艺学和精准农业的新科学研究与新的推广和教育途径结合起来，使我们的青年和社区能够转变并确保农业的可持续性。该研究将为种植者带来易于使用的新计算技术，促进数据隐私和控制，并实现以农场为中心的数据驱动分析和决策支持，帮助种植者可持续地提高产量。 此外，教育和外联计划将向技术熟练、生态意识日益增强的青年介绍与计算机科学和精准农业科学有关的挑战和奖励，使他们做好充分准备，并受到启发，参与应对增加可持续粮食生产的全球挑战。该项目研究了统一的网络基础设施和农业分析，以使个体种植者能够进行精确的、农艺学驱动的耕作，而不是像今天这样。 该系统名为SmartFarm，将不同的环境传感器技术集成到一个定制的、开源的、基于云的数据设备中，并提供新的分析，为种植者提供安全、易于使用、低成本的数据分析和决策支持系统。 使用开源私有云平台，该数据设备可以在一系列规模上托管，包括个人、农场私有云、大规模公共云或两者的某种组合。 该研究计划将促进新的知识：（一）农场控制，动态决策支持和应急响应的多分析农业应用;（二）自我管理，可扩展的私有云系统;（三）强大的传感和数据采集技术，应用程序编程接口，以及为农民和牧场主量身定制的处理引擎;以及（iv）用于精准农业的私有云和混合云软件架构，其代码和数据与公共云行业标准兼容。 推广和教育工作将使学生接触到跨学科的研究和教育活动，培养他们成为精准农业新技术的新农学家。

Ecological sustainability depends critically on the ability of world food production to manage increasingly limited natural resources (such as arable land and water) with new techniques that both enhance environmental stewardship and increase farm productivity. To make agriculture more productive and the productivity gains sustainable, growers are increasingly turning to environmental sensor measurement, data acquisition, and data analysis. To date, however, these tools have failed to achieve widespread use by smallholder agricultural concerns. Importantly, individual growers and ranchers are underserved by many recent advances in the commercial and research sectors that make data analytics consumable as simple "black box" end-user products. Current decision support offerings for these constituencies are variously limited, proprietary, complex, costly, require that growers relinquish control over their data, or are not widely available. This project therefore investigates a comprehensive research, educational, and outreach program called SmartFarm, which couples new scientific research in computer science, agronomics, and precision agriculture with novel outreach and educational pathways that enable our youth and communities to transform and ensure agriculture sustainability. The research will bring new computing technologies to growers that are easy to use, facilitate data privacy and control, and enable farm-focused, data-driven analysis and decision support that helps growers increase their yields sustainably. In addition, the educational and outreach plans will introduce technically adept youth, who are increasingly ecologically conscious, to the challenges and rewards associated with computer science and precision agricultural science so that they are adequately prepared and inspired to participate in the global challenge of increasing sustainable food production.To address the problem of sustainable food security and food safety, this project investigates unifying cyberinfrastructure and agriculture analytics to enable precision, agronomics-driven farming by individual growers unlike what is available today. The proposed system, called SmartFarm, integrates disparate environmental sensor technologies into a customized, open-source, cloud-based data appliance with new analytics that provide growers with a secure, easy to use, low-cost data analysis and decision support system. Using open-source private cloud platforms, this data appliance can be hosted at a range of scales including personal, private clouds on-farm, large-scale public clouds, or in some combination of the two. The research program will facilitate new knowledge in: (i) multi-analytic agricultural applications for farm control, dynamic decision support, and emergency response; (ii) self-managing, extensible private cloud systems; (iii) robust sensing and data acquisition techniques, application programming interfaces, and processing engines tailored to the needs of farmers and ranchers; and (iv) private and hybrid cloud software architectures for precision farming that are code and data compatible with public cloud industry standards. The outreach and education efforts will expose students to cross-disciplinary research and educational activities that train them as new agronomists in new technologists in precision agricultural.