RAPID: Houston in Hurricane Harvey (H3): Establishing Disaster System-of-Systems Requirements for Network-Centric and Data-Enriched Preparedness and Response
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This RAPID study will collect and analyze time-sensitive data from Hurricane Harvey in Houston in order to document the needs, challenges, and required capabilities for enhanced management, decision-making, and situation awareness in disaster system-of-systems (interdependent processes, operations, and systems involved in disaster preparedness and response). The management success and efficiency of disaster system-of-systems depend on the ability to integrate individual systems and processes and communicate information in a network-centric manner. The outcomes of this study will include: (1) A research roadmap and ontology specifying the requirements and characteristics for disaster system-of-systems in order to improve situation awareness, risk reduction, and decision-making during preparedness and response to extreme weather events; (2) An automated multi-modal data analytics framework integrating multiple heterogeneous datasets for improved situation awareness of community risks, events, and activities; and (3) A network analysis providing a guide for where, to whom, and how to utilize smart technologies and systems to enable network-centric and data-enriched Disaster SoS. These outcomes will provide important understanding and guide for researchers and practitioners towards creation and implementation of smart technologies and data analytics systems that enhance the resilience of communities to extreme weather events. Establishing robust and resilient disaster system-of-systems (SoS) is essential to protect communities in extreme weather events. However, the current knowledge lacks important elements related to the SoS requirements and characteristics (e.g., architecture, technologies, and integration) to augment human processes, interactions, and decision-making. To address this knowledge gap, this study aims to collect and analyze perishable and time-bound data from the 2017 Hurricane Harvey in Houston to: (1) Map Disaster SoS elements, relationships, needs, and challenges through in-depth interviews and participatory workshops with elected and appointed officials, infrastructure managers, emergency responders, and decision-makers, as well as household surveys; (2) Examine the utility of cyber informatics and social sensing technologies to better integrate social media infrastructure with Disaster SoS for improving the community situation awareness; and (3) Map and analyze community networks to model communities by their activities, events, and communication in order to determine opportunities for utilizing smart technologies for network-centric preparedness and response processes. The outcomes of this project will have significant societal benefits that will build new smart and connected communities that are more resilient to extreme weather events. To attain the societal benefits, the project outcomes will be disseminated through three avenues: community engagement workshops, scholarly publications and presentations, and a project webpage.
