ERI: Advancing Spontaneous Volunteer Coordination and Guidance for Effective Disaster Response

灾害造成混乱和不可预测的环境，传统的反应机制很容易被淹没。灾后，社区经常会有自发的志愿者涌入，他们渴望为救援工作做出贡献。然而，挑战在于如何最好地利用它们的能力和服务。该工程研究启动（ERI）项目支持使用自然语言处理和人工智能来分析和解释动态志愿者协调的社交媒体数据的研究。它还通过创新的搜索和救援知识图谱制定灾难响应策略，并通过增强现实技术进行情景指导。它旨在将多源非结构化数据集转化为可操作的见解，从而提高志愿者工作的效率和有效性，并推进智能灾害管理解决方案。更广泛的目标是培养一种备灾、参与和适应力强的社区精神，使个人能够为灾害应对和恢复做出有意义的贡献。计划研究的基础是将自然语言处理和时空推理与社交媒体分析相结合，同时开发一个搜索和救援知识图谱，通过增强现实增强情景指导。这些先进的工具和方法在利用灾害期间产生的大量但未得到充分利用的实时数据库方面发挥着核心作用，以便在最需要的地方为志愿者提供信息和指导。该项目打算建立一个动态的志愿人员协调系统，以适应正在展开的灾害情况的现实。此外，通过构建一个全面的知识图谱，封装了搜救行动中各种因素的复杂相互作用，该项目试图通过交互式增强现实界面提供针对具体情况的指导，从而提高培训的有效性和安全性。最终，这些技术的整合有望导致更灵活、更明智和更有凝聚力的志愿者资源动员。该奖项反映了美国国家科学基金会的法定使命，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。

Disasters create chaotic and unpredictable environments where traditional response mechanisms could be easily overwhelmed. In the aftermath, communities frequently experience an influx of spontaneous volunteers, eager to contribute to relief efforts. The challenge, however, lies in ways in which their capabilities and services can be best harnessed. This Engineering Research Initiation (ERI) project supports the research on the use of natural language processing and artificial intelligence to analyze and interpret social media data for dynamic volunteer coordination. It also develops disaster response strategies with an innovative search and rescue knowledge graph, enriched by augmented reality for situational guidance. It aims to transform multi-source, unstructured datasets into actionable insights, thereby enhancing the efficiency and effectiveness of volunteer efforts and advancing intelligent disaster management solutions. The broader ambition is to cultivate a community ethos of preparedness, engagement, and resilience, empowering individuals to contribute meaningfully to disaster response and recovery. Planned research is founded on integrating natural language processing and spatiotemporal reasoning with social media analysis, alongside developing a search-and-rescue knowledge graph for enhanced situational guidance through augmented reality. These advanced tools and methodologies play a central role in harnessing vast, yet underutilized, reservoir of real-time data generated during disasters to inform and guide volunteer actions where they are most needed. The project intends to establish a dynamic system for volunteer coordination that is adaptive to the unfolding realities of disaster scenarios. Furthermore, by constructing a comprehensive knowledge graph that encapsulates the complex interplay of factors in search and rescue operations, the project attempts to offer situation-specific guidance through an interactive augmented reality interface, thereby enhancing training’s effectiveness and safety. Ultimately, the integration of these technologies is expected to result in a more agile, informed, and cohesive mobilization of volunteer resources.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.