SCC-PG: A Sustainable and Connected Community-Scale Food System to Empower Consumers, Farmers, and Retailers
SCC-PG: A Sustainable and Connected Community-Scale Food System to Empower Consumers, Farmers, and Retailers
批准号:
2125516
负责人:
Oliver Kennedy
金额:
$15.0万
依托单位:
依托单位国家:
美国
项目类别:
Standard Grant
财政年份:
2021
资助国家:
美国
项目状态:
已结题
起止时间:
2021-10-01 至 2023-09-30
中文摘要
一个由利益相关者、资源、活动和信息组成的复杂网络将食物从农场运送到盘子,通过土壤到土壤食物系统(FS)。为了确保这一系统的健康,特别是在危机和不稳定时期,该系统的所有利益攸关方(例如,居民、食品生产者、研究人员和政策制定者)都需要新鲜、最新的信息,只有在社区成员的帮助下才能做到这一点。这个项目为一个可持续的、社区驱动的数据收集工具奠定了基础,该工具将同时通过回答一些问题来帮助社区成员更好地了解他们的食物系统,比如“我在哪里可以找到健康、新鲜、低成本的食物?”同时通过帮助保持数据的新鲜和最新,鼓励参与食品系统。该计划提案将开发概念验证,使用图像识别(例如,在零售店或农场摊位)来简化记录有关农产品展示中可获得的农产品的可用性、价格、类型和其他特性的信息的过程。该项目还将与社区成员合作,通过健康饮食讲习班和数据收集比赛推动该工具的采用。这个由研究人员和利益相关者组成的项目团队将与纽约西部(WNY)食品系统的非营利性和当地政府社区合作伙伴合作,开发名为REAP(Resilience For Resilience)的数据收集平台,允许众包数据扩大现有的WNY食品系统仪表盘。例如,通过允许众包农产品价格数据,该团队可以分析这些信息如何影响食品系统中消费者和供应商的行为。该项目将推动计算机视觉和不确定数据管理的最先进水平,方法是开发技术,使图像中的多个信息源相互关联,同时忽略干扰因素,并通过整个数据呈现管道跟踪系统对结果信息的置信度。拟议的工作还包括一项荟萃分析,使用事前和事后调查,以及对通过REAP捕获的数据进行图表分析,以检查共同产生的信息和与食品有关的行为行动的可用性和流动如何影响食品系统利益攸关方。REAP为正在进行的绘制WNY食物系统地图的努力奠定了基础,同时研究了城市和农村参与者。这一奖项反映了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
A complex network of stakeholders, resources, activities, and information move food from farm to plate through a soil to soil food system (FS). To ensure the health of this system, especially through times of crisis and instability, all of the system's stakeholders (e.g., residents, food-producers, researchers, and policy-makers) need fresh, up-to-date information, something only possible at scale through the aid of community members. This project lays the foundations for a sustainable, community-driven data collection tool that will simultaneously help community members to better understand their food system by answering questions like "Where can I find healthy, fresh, low-cost food?" while encouraging participation in the food system by helping to keep data fresh and up-to-date. This planning proposal will develop a proof-of-concept, using image recognition (e.g., at retail stores or farm stands) to streamline the process of recording information about the availability, price, types, and other characteristics of produce available at produce displays. The project will also work with community members to drive adoption of the tool through healthy eating workshops and data-collection competitions. Working collaboratively with non-profit and local government community partners in the Western New York (WNY) food system, the project team of researchers and stakeholder will develop data collection platform called REAP (Research, Education, Action, And Policy for Resilience) to allow crowdsourced data to augment an existing WNY food system dashboard. For example, by allowing for crowdsourced produce price data, the team can analyze how this information impacts the behaviors of both consumers and suppliers in the food system. The project will advance the state of the art in computer vision and uncertain data management by developing techniques to correlate multiple sources of information in images while ignoring distractors, and for tracking the system's confidence in the resulting information through the entire data presentation pipeline. The proposed work also includes a meta-analysis, using pre- and post- surveys, as well as graph analysis on the data captured through REAP, to examine how the availability and flow of co-produced information and food-related behavioral actions affect food system stakeholders. REAP lays the groundwork for ongoing efforts to map the WNY food system, simultaneously studying both urban and rural participants.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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会议论文
III: Medium: Collaborative Research: U4U - Taming Uncertainty with Uncertainty-Annotated Databases
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批准号:1956149
-
项目类别:Standard Grant
-
资助金额:$53.29万
-
财政年份:2020
-
负责人:Oliver Kennedy
-
依托单位:
NSF Student Travel Grant for 2019 Symposium on Cloud Computing (SOCC)
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批准号:1930814
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项目类别:Standard Grant
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资助金额:$1.5万
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财政年份:2019
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负责人:Oliver Kennedy
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依托单位:
CAREER: Declarative Uncertainty
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批准号:1750460
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项目类别:Continuing Grant
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资助金额:$54.23万
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财政年份:2018
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负责人:Oliver Kennedy
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依托单位:
CIF21 DIBBs: EI: Vizier, Streamlined Data Curation
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批准号:1640864
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资助金额:$272.57万
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财政年份:2017
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负责人:Oliver Kennedy
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依托单位:
III: Small: Just in Time Datastructures
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批准号:1617586
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项目类别:Standard Grant
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资助金额:$49.43万
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财政年份:2016
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负责人:Oliver Kennedy
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依托单位:
CI-P: Planning for a Community Infrastructure to Enable Pocket-Scale Data Management Research
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批准号:1629791
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项目类别:Standard Grant
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资助金额:$10.0万
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财政年份:2016
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负责人:Oliver Kennedy
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依托单位:
国内基金
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