MRI: Acquisition of Sensing and Computing Equipment for Smart High-Tunnel Greenhouses

MRI：为智能高隧道温室采购传感和计算设备

• 批准号: 1040254
• 负责人: Hui Chen
• 金额: $ 23.07万
• 依托单位: Virginia State University
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2010
• 资助国家: 美国
• 起止时间: 2010-09-15 至 2015-08-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1040254&HistoricalAwards=false
• 关键词: MRI; Acquisition; Sensing; Computing; Equipment

Proposal #: 10-40254PI(s): Chen, Hui Damevski, Kostadin; Mullins, Christopher; Rafie, Ahmad R.; Wang, JuInstitution: Virginia State UniversityTitle: MRI/Acq.: Acq. of Sensing and Computing Equipment for Smart High-Tunnel GreenhousesProject Proposed:This project from an MSI, principally undergraduate university, acquiring actuating devices, server computers, visualization workstations, etc., to form a Cyber-Physical System (CPS) that converts high-tunnel greenhouses into a ?smart? greenhouse system, aims to detect variations in the environmental conditions (e.g., moisture and temperature) and enable fine-grained control. Enabling the investigation of determining how recent advances in sensing, networking, and computing research can benefit agriculture practice (specifically, high-tunnel greenhouses), the work provides a window to expose practical problems that arise from setting up and operating the smart greenhouse system. Aiming to produce affordable and reliable CPS that can support automation in high-tunnel greenhouses the project looks into:- Water management in high-tunnel greenhouses,- Random scheduling for sensor networks,- Localization of sensor nodes that leverages radio tomographic images,- Fault-tolerant agriculture CPS, and- High programmer productivity environments for heterogeneous CPS.The project might lead to broader acceptance and use of the systems.Broader Impacts: The research instrument should foster collaboration among computer science and agricultural faculty, providing a field laboratory where students can conduct meaningful research-oriented experiments and thus increase the involvement of minority and women students in science, engineering, computer science, and mathematics. The research should contribute to affordable and robust systems and application in precision agriculture, and lead to sustainable agricultural practices and higher crop yields, indeed, a strong benefit for society at large. Moreover, undergraduate and graduate research and instruction and training should see improvement with the incorporation of more sophisticated real-world motivating examples and experiments.

提案编号：10- 40254 PI：Chen，Hui Damevski，Kostadin; Mullins，Christopher; Rafie，Ahmad R.; Wang，JuInstitution：Virginia State University职称： MRI/采集：获取智能高隧道温室的传感和计算设备项目建议：该项目来自MSI，主要是本科大学，获取驱动设备，服务器计算机，可视化工作站等，形成一个网络物理系统（CPS），将高隧道温室转化为一个？聪明吗温室系统，旨在检测环境条件的变化（例如，湿度和温度），并实现精细控制。该研究旨在确定传感，网络和计算研究的最新进展如何使农业实践（特别是高隧道温室）受益，该工作提供了一个窗口，以揭示设置和操作智能温室系统所产生的实际问题。该项目旨在生产价格合理且可靠的CPS，以支持高隧道温室的自动化，该项目研究了：-高隧道温室中的水管理，-传感器网络的随机调度，-利用无线电断层成像图像的传感器节点定位，-容错农业CPS，以及-异构CPS的高编程器生产力环境。该项目可能会导致更广泛的接受和使用系统。研究工具应促进计算机科学和农业教师之间的合作，提供一个实地实验室，学生可以在那里进行有意义的研究性实验，从而增加少数民族和妇女学生对科学、工程、计算机科学和数学的参与。这项研究应有助于在精准农业中建立负担得起的、强大的系统和应用，并导致可持续的农业实践和更高的作物产量，实际上，这对整个社会都有很大的好处。此外，本科生和研究生的研究、教学和培训应该会随着更复杂的现实世界激励性例子和实验的结合而得到改善。