PFI-RP: A Smart Food Distribution System for Allocating Scarce Resources Under Extreme Events

PFI-RP：极端事件下分配稀缺资源的智能食品分配系统

• 批准号: 2234598
• 负责人: Lauren Davis
• 金额: $ 55万
• 依托单位: North Carolina Agricultural & Technical State University
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2023
• 资助国家: 美国
• 起止时间: 2023-08-15 至 2026-07-31
• 项目状态: 未结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=2234598&HistoricalAwards=false
• 关键词: PFI; RP; Smart; Food; Distribution

The broader impact/commercial potential of this Partnerships for Innovation - Research Partnerships (PFI-RP) project is to provide direct benefit to organizations engaged in the provision of food aid, which will translate to better outcomes for people and society, particularly with respect to increasing access to food for vulnerable populations during extreme events. Food insecurity is a persistent problem in the US despite the nearly 4 billion pounds of food rescued in 2020 by over 200 food banks. By leveraging actual data from the foodbanks, knowledge of the operations of foodbanks and the use of Artificial Intelligence (AI), the developed system will provide policy recommendations about the collection, storage, and distribution of food that will incorporate fairness in food distribution while reducing the cost of acquiring and distributing food, and cutting down food waste. These recommendations will transform how organizations rapidly adapt their operations according to environmental disruptions. The proposed project will create and enhance the resilience of smart food distribution systems for resource allocation under extreme events directly from data. A generalizable framework for aggregating and standardizing the collection of data across various media (operational data, publicly available) to provide adaptive predictions of supply and need (at scale) will be developed. The developed data-driven optimization models will facilitate near real-time evaluation of food distribution strategies and provide interactive and interpretable model visualizations of the material, financial, and physical capacity of the food distribution networks. Managers responsible for supply chains in medium to large hunger relief organizations will benefit from the Al-driven resource management software to increase the number of food insecure households served. Additionally the project will inform research on decision-making which will ultimately make hunger relief organizations more resilient in extreme situations thus mitigating the negative impacts of disruptions to supply chain networks.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.

这一创新-研究伙伴关系（PFI-RP）项目的更广泛影响/商业潜力是为参与提供粮食援助的组织提供直接利益，这将转化为人民和社会的更好成果，特别是在极端事件期间增加弱势群体获得粮食的机会。 尽管2020年有超过200家食品银行拯救了近40亿磅食品，但食品不安全是美国持续存在的问题。 通过利用来自食品银行的实际数据，食品银行运营的知识和人工智能（AI）的使用，开发的系统将提供有关食品收集，存储和分配的政策建议，这些建议将公平地纳入食品分配，同时降低获取和分配食品的成本，并减少食物浪费。 这些建议将改变组织如何根据环境破坏快速调整其运营。拟议的项目将建立和加强智能食品分配系统的弹性，以便直接从数据中分配极端事件下的资源。将制定一个可推广的框架，将各种媒介收集的数据（公开的业务数据）汇总起来并使之标准化，以便对供应和需求（大规模）进行适应性预测。 开发的数据驱动的优化模型将有助于近实时评估食品配送策略，并提供食品配送网络的材料，财务和物理能力的交互式和可解释的模型可视化。大中型饥饿救济组织负责供应链的管理人员将受益于Al驱动的资源管理软件，以增加所服务的粮食不安全家庭的数量。 此外，该项目将为决策研究提供信息，最终使饥饿救济组织在极端情况下更具弹性，从而减轻供应链网络中断的负面影响。该奖项反映了NSF的法定使命，并通过使用基金会的知识价值和更广泛的影响审查标准进行评估，被认为值得支持。