I-Corps Teams: Wireless Sensor Network Based Localization and Navigation for Precision Agriculture

I-Corps 团队：基于无线传感器网络的精准农业定位和导航

• 批准号: 1638927
• 负责人: Vijaya Kumar Devabhaktuni
• 金额: $ 5万
• 依托单位: University of Toledo
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2016
• 资助国家: 美国
• 起止时间: 2016-04-15 至 2017-02-28
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1638927&HistoricalAwards=false
• 关键词: Corps; Teams; Wireless; Sensor; Network

According to a USDA summary circa 2015, there exist 2.08 million farms in the US, spanning a total of 913 million acres with an average farm size of 438 acres. Efficiency and productivity are integral factors in profitability from agricultural operations. Efficiency and productivity critically depend on the level of automation or semi-automation, continuous real-time monitoring, continuous and timely intervention, and our ability to benefit from emerging scientific and technological innovations (e.g. low-cost and high-precision sensors, wireless technologies, etc). As part of previous NSF funded research, this I-Corps team has pioneered efficient localization algorithms for wireless sensor networks. The algorithms offer computational speed and real-time localization accuracy. Motivated by the broader impacts of these algorithms, the team is now interested in evaluating their commercial and technological potential to increase efficiency and productivity in American agriculture. This NSF I-Corps project and its potential outcomes are expected to be of high interest to the US Department of Agriculture. Potential customers include (1) Large agricultural companies; (2) Manufacturers of precision agriculture equipment; (3) Precision farming service providers; and most importantly (4) American farmers. This NSF I-Corps project will enable the team to better understand the market needs for an "electronic localization system," identify competing precision farming solutions, and build a demonstrable prototype. The proposed hardware consists of an array of sensor nodes with calibration and measurement capabilities (e.g. moisture, nitric oxide, sodium, temperature, etc.) that can be deployed throughout a given farmland. Software consists of data fusion and data-2-decision algorithms developed via our previously funded NSF technology (i.e. localization of a node). Functionally, each node is capable of detecting anomalies (e.g. high temperature and low moisture) and sending alert signals to the base station. The system alerts the farmer (or an autonomous vehicle) and offers precise localization and navigation to the concerned site for executing real-time remedial measures. The technology aims to eliminate dependence on global positioning systems (GPS), thereby offering a cost-effective precision farming solution for many rural environments where GPS is either undependable or unavailable. In this proposed I-Corps project, the team will (1) Interact with potential clients; (2) Investigate market needs and market size; (3) Learn about the supply chain and distribution channels; and (4) Talk to potential venture investors about what kind of precision agriculture innovations would be attractive for investment.

根据美国农业部2015年的一份摘要，美国有208万个农场，总面积为9.13亿英亩，平均农场面积为438英亩。效率和生产力是农业经营获利的组成因素。效率和生产力主要取决于自动化或半自动化的水平、持续的实时监控、持续和及时的干预，以及我们从新兴科学和技术创新中受益的能力（例如低成本和高精度传感器、无线技术等）。作为以前NSF资助的研究的一部分，这个I-Corps团队开创了无线传感器网络的高效定位算法。该算法提供计算速度和实时定位精度。受这些算法更广泛影响的激励，该团队现在有兴趣评估其商业和技术潜力，以提高美国农业的效率和生产力。NSF I-Corps项目及其潜在成果预计将引起美国农业部的高度兴趣。潜在客户包括（1）大型农业公司;（2）精准农业设备制造商;（3）精准农业服务提供商;最重要的是（4）美国农民。这个NSF I-Corps项目将使该团队能够更好地了解市场对“电子定位系统”的需求，确定竞争性的精准农业解决方案，并建立一个可演示的原型。所提出的硬件由具有校准和测量能力（例如水分、一氧化氮、钠、温度等）的传感器节点阵列组成。可以在指定的农田中部署。软件由数据融合和数据2决策算法组成，这些算法是通过我们以前资助的NSF技术（即节点本地化）开发的。在功能上，每个节点都能够检测异常（例如高温和低湿度）并向基站发送警报信号。该系统提醒农民（或自动驾驶车辆），并提供精确的定位和导航到有关网站，以执行实时补救措施。该技术旨在消除对全球定位系统（GPS）的依赖，从而为GPS不可靠或不可用的许多农村环境提供具有成本效益的精准农业解决方案。在这个拟议的I-Corps项目中，该团队将（1）与潜在客户互动;（2）调查市场需求和市场规模;（3）了解供应链和分销渠道;（4）与潜在的风险投资者讨论什么样的精准农业创新对投资有吸引力。