NSF Convergence Accelerator Track J: Artificial-Intelligence-Based Decision Support for Equitable Food and Nutrition Security in the Houston Area

NSF 融合加速器轨道 J:基于人工智能的决策支持,实现休斯顿地区公平的粮食和营养安全

基本信息

  • 批准号:
    2236305
  • 负责人:
  • 金额:
    $ 75万
  • 依托单位:
  • 依托单位国家:
    美国
  • 项目类别:
    Standard Grant
  • 财政年份:
    2022
  • 资助国家:
    美国
  • 起止时间:
    2022-12-15 至 2024-11-30
  • 项目状态:
    已结题

项目摘要

Disadvantaged communities continue to be afflicted with health issues due to limited access to nutritious food and inadequate knowledge about healthy food choices. The COVID-19 pandemic has exacerbated these issues. One of the most critical steps in addressing food insecurity is to improve understanding of the resources required and the challenges faced in procurement, distribution, access, and utilization of food resources in underserved communities. On the demand side, stakeholders must identify the nutritional needs, cultural preferences, and food preparation equipment and supplies of food-insecure households. If an individual does not know what a particular food is nor how to prepare it, it will go to waste, and the efforts of the food charity ecosystem will fail. On the supply side, stakeholders must streamline logistics and improve communication and coordination to optimize the supply chain (upstream procurement and downstream distribution) to minimize inefficiencies and coordinate the efforts of various food charities. Through a community-driven approach, this project brings together civic collaborators with university researchers to develop and build a locally-oriented food charity ecosystem based on data-driven smart technologies in the Greater Houston region. Our socio-technical approach addresses four overall research questions: (1) How can we redefine, model, and predict food deserts? (2) How can we minimize food waste? (3) How can we impact nutrition literacy? (4) How can we measure the health effects of having access to culturally appropriate nutritious food?These questions drive the following objectives: (i) Assess, model, and predict geographic areas with limited access to affordable and nutritious food; (ii) Analyze communities to find untapped strengths in preparing culturally appropriate recipes and transfer this knowledge to like-minded community members, (iii) Build infrastructure for food pantries to provide culturally appropriate food they have in stock and recipes/food preparation instructions, (iv) Create a blockchain-based marketplace for food donations, (v) Develop educational material in multiple languages and partner with Community Health Workers to disseminate it, and (vi) Measure the health effects of having access to culturally appropriate nutritious food.Our multidisciplinary team brings together researchers in computer science, urban planning, community engagement, nutrition education/community healthy lifestyle program development, supply chain, measurement and evaluation, and a diverse set of “on the ground” practitioner partners. Our team is focused on turning research into action. The decision-making tools will be disseminated to other food ecosystem members to address all aspects of culturally aware food distribution.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.
由于获得营养食品的机会有限,以及对健康食品选择的了解不足,弱势社区继续受到健康问题的困扰。新冠肺炎疫情加剧了这些问题。解决粮食不安全问题的最关键步骤之一是提高对所需资源的了解,以及在服务不足的社区采购、分配、获取和利用粮食资源方面所面临的挑战。在需求方面,利益攸关方必须确定粮食不安全家庭的营养需求、文化偏好以及食品制备设备和供应。如果一个人不知道一种特定的食物是什么,也不知道如何准备,它就会浪费,食物慈善生态系统的努力也会失败。在供应方面,利益攸关方必须精简物流,改善沟通和协调,以优化供应链(上游采购和下游分销),将效率低下降至最低,并协调各种食品慈善机构的努力。通过社区驱动的方法,该项目将民间合作者与大学研究人员聚集在一起,在大休斯顿地区基于数据驱动的智能技术开发和构建以本地为导向的食品慈善生态系统。我们的社会技术方法解决了四个总体研究问题:(1)我们如何重新定义、模拟和预测食物沙漠?(2)我们如何减少食物浪费?(3)我们如何影响营养素养?(4)我们如何衡量获得适合文化的营养食物对健康的影响?这些问题推动以下目标:(I)评估、建模和预测可获得负担得起的营养食物的地理区域;(Ii)分析社区,以发现在准备符合文化习惯的食谱方面尚未开发的优势,并将这些知识传递给志同道合的社区成员,(Iii)为食品储藏室建立基础设施,以提供他们现有的符合文化习惯的食物和食谱/食物制备说明,(Iv)创建基于区块链的食品捐赠市场,(V)开发多种语言的教育材料,并与社区卫生工作者合作传播,以及(Vi)衡量获得符合文化习惯的营养食物对健康的影响。我们的多学科团队汇集了计算机科学、城市规划、社区参与、营养教育/社区健康生活方式计划开发、供应链、衡量和评估,以及不同的“实地”实践者合作伙伴。我们的团队专注于将研究转化为行动。这些决策工具将被分发给其他食品生态系统成员,以解决具有文化意识的食品分配的所有方面。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。

项目成果

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Ioannis Kakadiaris其他文献

AI-enabled Cardiac Chambers Volumetry and Calcified Plaque Characterization in Coronary Artery Calcium (CAC) Scans (AI-CAC) Significantly Improves on Agatston CAC Score for Predicting All Cardiovascular Events: The Multi-Ethnic Study of Atherosclerosis
冠状动脉钙 (CAC) 扫描 (AI-CAC) 中支持 AI 的心室容量和钙化斑块特征显着改善 Agatston CAC 评分,用于预测所有心血管事件:动脉粥样硬化的多种族研究
  • DOI:
  • 发表时间:
    2024
  • 期刊:
  • 影响因子:
    0
  • 作者:
    M. Naghavi;A. Reeves;K. Atlas;Chenyu Zhang;T. Atlas;C. Henschke;D. Yankelevitz;M. Budoff;Dong Li;Sion Roy;Khurram Nasir;Jagat Narula;Ioannis Kakadiaris;S. Molloi;Zahi Fayad;David Maron;Michael McConnell;Kim Williams;Daniel Levy;Nathan S Wong
  • 通讯作者:
    Nathan S Wong
Introduction to the special issue on human modeling, analysis, and synthesis
  • DOI:
    10.1007/s00138-003-0122-5
  • 发表时间:
    2003-09-01
  • 期刊:
  • 影响因子:
    2.300
  • 作者:
    Ioannis Kakadiaris;Rajeev Sharma;Mohammed Yeasin
  • 通讯作者:
    Mohammed Yeasin
Developing a healthy food access index (HFAI): Web-based mapping and future directions for AI integrations
开发健康食品获取指数(HFAI):基于网络的绘图以及人工智能集成的未来方向
  • DOI:
    10.1016/j.cities.2025.105908
  • 发表时间:
    2025-06-01
  • 期刊:
  • 影响因子:
    6.600
  • 作者:
    Junfeng Jiao;Kijin Seong;Marcus Sammer;Ryan Hardesty Lewis;Alison Reese;Norma Olvera;Susie L. Gronseth;Elizabeth Anderson-Fletcher;Ioannis Kakadiaris
  • 通讯作者:
    Ioannis Kakadiaris
Artificial intelligence applied to coronary artery calcium scans (AI-CAC) significantly improves cardiovascular events prediction
人工智能应用于冠状动脉钙扫描(AI-CAC)可显著改善心血管事件预测
  • DOI:
    10.1038/s41746-024-01308-0
  • 发表时间:
    2024-11-05
  • 期刊:
  • 影响因子:
    15.100
  • 作者:
    Morteza Naghavi;Anthony P. Reeves;Kyle Atlas;Chenyu Zhang;Thomas Atlas;Claudia I. Henschke;David F. Yankelevitz;Matthew J. Budoff;Dong Li;Sion K. Roy;Khurram Nasir;Sabee Molloi;Zahi Fayad;Michael V. McConnell;Ioannis Kakadiaris;David J. Maron;Jagat Narula;Kim Williams;Prediman K. Shah;Daniel Levy;Nathan D. Wong
  • 通讯作者:
    Nathan D. Wong

Ioannis Kakadiaris的其他文献

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{{ truncateString('Ioannis Kakadiaris', 18)}}的其他基金

D-ISN/Collaborative Research: Financial and Network Disruptions in Counterfeit and Illegal Medicines Trade
D-ISN/合作研究:假冒和非法药品贸易中的财务和网络中断
  • 批准号:
    2146335
  • 财政年份:
    2022
  • 资助金额:
    $ 75万
  • 项目类别:
    Standard Grant
SCC-CIVIC-FA Track B: Artificial-Intelligence-Based Decision Support for Equitable and Resilient Food Distribution during Pandemics and Extreme Weather Events
SCC-CIVIC-FA 轨道 B:基于人工智能的决策支持,在大流行和极端天气事件期间实现公平和有弹性的粮食分配
  • 批准号:
    2133352
  • 财政年份:
    2021
  • 资助金额:
    $ 75万
  • 项目类别:
    Standard Grant
SCC-CIVIC-PG Track B: Equitable Food-Security: Disaster-resilient supply chains for pandemics and extreme weather events
SCC-CIVIC-PG 轨道 B:公平粮食安全:应对流行病和极端天气事件的抗灾供应链
  • 批准号:
    2043988
  • 财政年份:
    2021
  • 资助金额:
    $ 75万
  • 项目类别:
    Standard Grant
Supporting Student Development Activities at the International Joint Conference on Biometrics (IJCB2020)
在国际生物识别联合会议(IJCB2020)上支持学生发展活动
  • 批准号:
    2038085
  • 财政年份:
    2020
  • 资助金额:
    $ 75万
  • 项目类别:
    Standard Grant
D-ISN: TRACK 2: Collaborative Research: Financial Network Disruptions in Illicit and Counterfeit Medicines (FIND-M)
D-ISN:轨道 2:合作研究:非法和假冒药品的金融网络中断 (FIND-M)
  • 批准号:
    2039946
  • 财政年份:
    2020
  • 资助金额:
    $ 75万
  • 项目类别:
    Standard Grant
I-Corps: Exploiting matching score distributions to improve biometric recognition
I-Corps:利用匹配分数分布来提高生物特征识别
  • 批准号:
    1561151
  • 财政年份:
    2015
  • 资助金额:
    $ 75万
  • 项目类别:
    Standard Grant
Segmentation of 3D Tubular Structures
3D 管状结构的分割
  • 批准号:
    0638875
  • 财政年份:
    2006
  • 资助金额:
    $ 75万
  • 项目类别:
    Standard Grant
Collaborative Research: Physics-Based Modeling and Simulation for Post-Mastectomy Breast Reconstructive Surgery
合作研究:基于物理的乳房切除术后乳房重建手术建模与仿真
  • 批准号:
    0402591
  • 财政年份:
    2004
  • 资助金额:
    $ 75万
  • 项目类别:
    Continuing Grant
SEI: Cardiovascular Informatics
SEI:心血管信息学
  • 批准号:
    0431144
  • 财政年份:
    2004
  • 资助金额:
    $ 75万
  • 项目类别:
    Standard Grant
2003 Workshop on Robotics and Computer Vision: PI Meeting
2003 年机器人和计算机视觉研讨会:PI 会议
  • 批准号:
    0334822
  • 财政年份:
    2003
  • 资助金额:
    $ 75万
  • 项目类别:
    Standard Grant

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