SCC-IRG Track 1: Socially-integrated robust communication and information-resource sharing technologies for post-disaster community self-reliance
SCC-IRG Track 1: Socially-integrated robust communication and information-resource sharing technologies for post-disaster community self-reliance
批准号:
2311405
负责人:
Cynthia Chen
金额:
$200.0万
依托单位:
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
项目状态:
未结题
起止时间:
2023-10-01 至 2027-09-30
中文摘要
当灾难来袭时,社区往往会变得孤立,公民会聚集在一起相互帮助:人们共享资源,传递信息,并承担他们通常所在领域之外的任务。这些活动在学术文献和轶事文献中都有报道。其中一些例子包括:在2005年纽约交通局罢工期间,纽约人共用私人车辆和船只,导致纽约市交通服务瘫痪;在北卡罗来纳州罗兰市,邻居们使用用充气床垫自制的木筏帮助邻居逃离2016年S飓风马修造成的洪水。这些点对点资源共享活动填补了灾害期间应急机构无法填补的重要空白。该项目帮助填补这一空白,与华盛顿州的城乡、高收入和低收入社区合作,在灾难期间了解和推动更有效的当地信息和资源传播。该项目整合了硬件、强大的通信技术、社会能力和空间条件,以利用和加强以地点为基础的社会网络来共享信息资源;并调查了一个很少被研究的涉及通信、共享和抗灾能力的科学前沿。对于日益面临自然灾害风险并有兴趣通过信息和资源共享提高其复原力的社区来说,该项目的成果将可在日常和紧急的基础上加以推广和利用。更具体地说,该项目将与这两个社区共同设计,并在四个方面进行研究。推力1-强大的通信,将开发强大的离网社区网络,由社区拥有和运营。推力2-建立社区社交网络以实现信息资源共享,将进行调查,收集有关人们在社区内的分享行为和社交关系的信息,并开发新的模型来推断基于社区的社交网络。推力3--以社区为基础的信息资源共享,将制定将导致有效信息资源共享的模式和战略。关键假设是社会网络结构影响信息资源共享的最佳性和稳定性。推力4(Dynamic Map Your Neighborhood)整合了推力1-3的结果,并使用它们与西澳大利亚(城市和农村)的两个社区共同设计和试点测试应用程序。多样化的团队专业知识通过设计强大的通信技术促进跨学科的知识和方法,并通过新颖的方式征求社会联系信息和信息资源共享模型,该模型同时考虑了模型的最优化和人类的投入(例如,来自社区的领导人提名)。该奖项反映了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
When a disaster strikes, communities often become isolated and citizens come together to help each other: people share resources, pass along information, and take on tasks that are outside of their usual domains. These activities have been reported in both academic literature and anecdotal documents. Some examples include: New Yorkers’ sharing private vehicles and boats during the 2005 MTA strike that crippled NYC transit services; and neighbors helping neighbors escape from flooding caused by 2016’s Hurricane Matthew using rafts improvised from inflatable mattresses in Rowland, NC. These peer-to-peer resource sharing activities fill important gaps during times of disaster that cannot be fulfilled by emergency response agencies. This project helps fill this gap by working with urban and rural, higher- and lower-income communities in Washington State to understand and advance more effective local information and resource dissemination during a disaster. The project integrates hardware, robust communication technologies, social capacities, and spatial conditions to leverage and enhance place-based social networks for information-resource sharing; and investigate a little-studied scientific frontier intersecting communications, sharing, and disaster resilience. The results of the project will be scalable and useful on a daily and emergency basis to communities that increasingly face natural disaster risks and are interested in enhancing their resilience through information and resource sharing. More specifically, the project will co-design with the two communities and conduct research in four thrusts. Thrust 1—robust communications, will develop robust off-grid community-based networks that are owned and operated by the community. Thrust 2—building community social networks for information-resource sharing, will conduct surveys to collect information about people’s sharing behavior and their social ties within a community, and develop novel models to infer community-based social networks. Thrust 3—community-based information-resource sharing, will develop models and strategies that will lead to efficient information-resource sharing. The key hypothesis is that social network structures affect the optimality and stability of information-resource sharing. Thrust 4 (Dynamic Map your Neighborhood) integrates the results of Thrusts 1-3 and uses them to co-design and pilot-test applications with two communities in WA (urban and rural). The diverse team expertise facilitates knowledge and methods across disciplines through the design of robust communication technologies, and novel ways to solicit social ties information and information-resource sharing models that considers both model optimality and human inputs (e.g., leader nominations from the communities).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.
期刊论文(0)
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会议论文
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Learning Failure Propagation Patterns in Interdependent Network From Observed Post-Disaster Disruptions
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负责人:Cynthia Chen
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依托单位:
国内基金
海外基金
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