The prevalence of high-speed data management and communication systems have produced countless large volumes of high-veracity, real-time data collections across many domains. For example, natural disasters initiate a myriad of human communications, data exchange, and situational assessments. It is crucial to quickly collect and analyze all of the relevant data, as life or death decisions may rest on the outcome. Hurricane Irma in 2017 caused the largest civil evacuation in Florida’s history and emphasizes two critical problems in emergency management: 1) pre-storm evacuation coordination; and 2) post-storm support for shelter-in-place locations. Disaster information integration and fusion technologies have the potential to deliver enhanced situational awareness tools across all sectors, enabling a more efficient, effective, and automated emergency management and recovery process. However, there is no discernible approach to identify and exploit the underlying patterns of each dataset while also minimizing possible drawbacks. This project aims to utilize multimodal data, such as text messages, images, videos, traffic information, and geo-referencing information, from various sources including social media, news, government announcements, and radio broadcasts. This work will investigate the analysis and fusion of this information to provide useful insights for aiding the decision-making process for both residents and government agencies. The goal is to develop new tools and technologies that can support emergency managers to better evaluate the effectiveness of disaster management policies such as evacuation.
The proposed research provides potential solutions to solve crucial information analysis challenges related to disaster information management while leveraging the team's previous work. In addition, the team's research approach offers rapid key information identification, efficient multimodal data integration that facilitates emergency management, and enhances dynamic community disaster information sharing. Moreover, solutions developed could later be extended to other domains in the information management field. This project fosters collaboration among two institutions, Florida International University (FIU) and University of Tokyo, as well as institutions across the public and private sectors, to develop advanced techniques for effective emergency response and disaster management. The broader impact of this work will lead to scientific advances in the preparation, response, recovery, and mitigation of major disasters. As the largest graduate Hispanic Serving Institution in the continental United States, FIU will also benefit from the impact of this project that expands the participation of underrepresented groups in STEM fields. The research findings of this project will be broadly disseminated via publications, presentations, and an organized workshop.
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.