Abstract
This paper presents the research challenges of designing a combined physical sensor- and social sensor-based information framework to collect heterogeneous flooding disaster data, and then to fuse those data and generate actionable understandings. Our overall objective is to improve the response preparedness of critical infrastructures, contributing to the goal of smart and connected communities. We propose methods to model physical and social sensors, and open demographic data integration with regional knowledge, and to leverage these fused data for understanding impending events and conditions deleterious to lives and properties. In addition, the proposed system will predict the disaster events and provide knowledge-based recommendations to inform emergency management personnel to enable the resilience of the smart and connected communities. Preliminary experiments for the framework are promising. Further work is needed to validate the framework in collaboration with the local emergency managers.
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Acknowledgements
The work is partially supported by the National Science Foundation grant CNS-1763294. Authors would also like to acknowledge the support of Dr. Dong Wang, Dr. Brian Xu, and Mr. Ike Vayansky for their help in generating methodology diagram and experimental results. Authors would also like to thank Dr. Zhenlong Li for providing the social media data for analysis.
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Kumar, S.A.P., Bao, S., Singh, V. et al. Flooding disaster resilience information framework for smart and connected communities. J Reliable Intell Environ 5, 3–15 (2019). https://doi.org/10.1007/s40860-019-00073-2
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DOI: https://doi.org/10.1007/s40860-019-00073-2