I-Corps: Data Analytics for Hand-Picked Agriculture

I-Corps：精心挑选的农业数据分析

基本信息

批准号：
1748498
负责人：
Richard Sowers
金额：
$ 5万
依托单位：
University of Illinois at Urbana-Champaign
依托单位国家：
美国
项目类别：
Standard Grant
财政年份：
2017
资助国家：
美国
起止时间：
2017-10-01 至 2019-03-31
项目状态：
已结题

来源：
https://www.nsf.gov/awardsearch/showAward?AWD_ID=1748498&HistoricalAwards=false
关键词：
Corps Data Analytics Hand Picked

项目摘要

The broader impact/commercial potential of this I-Corps project is to improve food safety and security of hand harvested food crops through individualized geo-spatial data collection. Much like highway cameras have an ability to tell the status of traffic on a given freeway are vastly improved through the individualized data of each driver and their phones, hand harvested food can benefit from improving traceability and transparency from block level data to single points of harvest, recalling intersecting mapping data. Geo-specific data can also enable better land productivity measurement over textual block data. Individualized, personally owned, data enables workers to have portability of information, building a resume of dependability and performance. In addition, it becomes an integral component of a viable transparency scheme. The project will potentially improve the economic standing of harvesters, improve the capability of farmers to better understand their workforce and land, assist marketers with improved data to insure against breakdowns in food safety, and enable consumers transparency without added steps to the system.This I-Corps project further develops improved data collection methods in high-value hand-picked specialty crops. The data in question is a precise record of who harvests what, where and when. Contextual data (quality, irrigation/fertilization data, cultural practice maps, etc.) are added and visualized for farmers. The project will test the relationship of data sets toward improved decision skills; better management depends on better measurement. It provides a better understanding of inhomogeneities in space and time. Addressing these inhomogeneities leading to investigation and reductions of variance. The system will enables comprehension of bottlenecks and workflow problems in labor process and allow dynamic and real-time decisions. The system will also allow quantitative approaches toward finding optimal decisions in several parts of the system and provide a platform for decentralized decision-making based on common data.

该I-Corps项目的更广泛的影响/商业潜力是通过个性化地理空间数据收集来改善手工收获的食品作物的安全性和安全性。就像高速公路摄像机能够通过每个驾驶员及其手机的个性化数据大大改善在给定高速公路上的交通状况一样，手收集的食物可以从提高可追溯性和从收获单点到收获点的透明度而受益，从而回想起相交的映射数据。与文本块数据相比，特定于地理特定的数据还可以实现更好的土地生产率测量。个性化的，个人拥有的数据使工人能够具有可移植性的信息，建立可靠性和绩效的简历。另外，它成为可行透明度方案的组成部分。该项目将有可能改善收割者的经济地位，提高农民更好地了解其劳动力和土地的能力，帮助营销人员改进数据，以确保不防止食品安全的破裂，而在没有添加的系统的情况下使消费者透明度可以透明度。这项I-Corps项目进一步开发了改进的高价值手工收集的数据收集方法，该方法在高级挑选的专用专家中得到了改进的数据收集方法。所讨论的数据是谁收获什么，何时何地的精确记录。添加并为农民添加了上下文数据（质量，灌溉/受精数据，文化实践图等）。该项目将测试数据集与提高决策技能的关系；更好的管理取决于更好的测量。它可以更好地理解时空中的不均匀性。解决这些不均匀性，导致调查和减少方差。该系统将在人工过程中理解瓶颈和工作流问题，并允许动态和实时决策。该系统还将允许定量方法在系统的几个部分中找到最佳决策，并为基于共同数据的分散决策提供平台。