Collaborative Research: SOCIUS: Socially Responsible Smart Cities

合作研究：SOCIUS：具有社会责任感的智慧城市

• 批准号: 1651566
• 负责人: Min Kyung Lee
• 金额: $ 10万
• 依托单位: Carnegie-Mellon University
• 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: 2016-09-01 至 2018-08-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1651566&HistoricalAwards=false
• 关键词: Collaborative; Research; SOCIUS; Socially; Responsible; Collaborative; Research; SOCIUS; Socially; Responsible

Every year, 3.5 million people in the US experience homelessness, with 1 in 30 children becoming homeless. Despite numerous government-sponsored programs and efforts by nonprofit organizations, many homeless people live in abject conditions. This research re-envisions smart city technologies to best serve those in need of access to basic resources including food, shelter and medical services. The proposed infrastructure will connect the currently disjoint efforts of public services, NGOs and private citizens, and use population-modeling and planning algorithms to match the varying and unpredictable supply with those who need it. In pursuit of the overarching goal of collecting and delivering services to maximize social welfare, this research will make advances in the science of population modeling, the analysis and design of human-centered planning algorithms, and technological challenges including secure and privacy-aware sensing modalities and mobile technologies.As part of a human-centered design approach, interviews and observations will be conducted to understand user needs, and design a system that multiple stakeholders can use to report their needs and extra supply. This collected data will be used by non-profit organizations to strategically distribute resources. The real-world stakeholders such as food banks, food pantries, shelters, street medicine teams, and food rescue organizations will be closely involved in the design and evaluation process.This research is high-risk and high-reward, and appropriate for EAGER. Failure means that the resulting planning algorithms will make unfair decisions and prioritize a few organizations or donors, or will make fair, but inefficient allocation decisions, which will endanger social justice and community well-being. Success will improve both efficiency of resource distribution and the quality of life of underserved populations in the United States. The completion of the project will produce 1) algorithms for optimal resource allocation that are both efficient and aware of human-in-the-loop concerns, and which can be used for other functions including disaster-response, and 2) communication infrastructure for non-profit organizations, volunteers, and populations in need, to coordinate other service activities. The project has potential for great societal impact: it will make charitable donations convenient and inexpensive for those with supply power, increasing the volume of donations and thereby reducing wastage. The outcome will be an improved realization of the philanthropic potential of the increasingly sharing nature of the American economy.

每年，美国350万人都会无家可归，其中30名儿童无家可归。尽管政府赞助的计划和非营利组织的努力，但许多无家可归者生活在卑鄙的条件下。这项研究重新考虑了智能城市技术，以最好地为需要获得基本资源（包括食品，住房和医疗服务）的人提供服务。拟议的基础设施将将公共服务，非政府组织和私人公民的当前不相交努力联系起来，并使用人口模型和规划算法与需要它的人将不同和不可预测的供应与不可预测的供应匹配。为了追求收集和提供服务以最大化社会福利的总体目标，这项研究将在人口建模科学，以人为中心的计划算法的分析和设计方面取得进步报告他们的需求和额外的供应。非营利组织将使用这些收集的数据来战略分配资源。实际的利益相关者，例如食品银行，食品储藏室，避难所，街头医学团队和食品救援组织，将密切参与设计和评估过程。这项研究是高风险和高级奖励，适合渴望。失败意味着由此产生的计划算法将做出不公平的决定并确定一些组织或捐助者的优先级，或者将做出公平但效率低下的决策，这将危害社会正义和社区福祉。成功将提高资源分配的效率和美国服务不足人群的生活质量。该项目的完成将产生1）用于最佳资源分配的算法，这些算法既有效又意识到人类的关注点，并且可以用于包括灾难响应在内的其他功能，以及2）非营利组织，志愿者，志愿者，志愿者和人口的交流基础设施，以协调其他服务活动。该项目具有巨大的社会影响力：它将使慈善捐赠方便且廉价的供应能力，从而增加捐款的数量，从而减少浪费。结果将改善美国经济越来越分享性质的慈善潜力。