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- Publisher
- Springer Journals
- Copyright
- Copyright © 2019 by Springer Nature Switzerland AG
- Subject
- Computer Science; Performance and Reliability; Software Engineering/Programming and Operating Systems; Artificial Intelligence; Simulation and Modeling ; User Interfaces and Human Computer Interaction; Health Informatics
- ISSN
- 2199-4668
- eISSN
- 2199-4676
- DOI
- 10.1007/s40860-019-00073-2
- Publisher site
- See Article on Publisher Site
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.
Journal
Journal of Reliable Intelligent Environments – Springer Journals
Published: Feb 26, 2019