Smart-Evac: Big Data-Based Decision Making for Emergency Evacuation

Smart-Evac manages emergency evacuation systems after a natural disaster. Unlike existing disaster risk reduction (DRR) systems, Smart-Evac takes cloud computing and big data characteristics into consideration during decision making. The authors consider human anxiety to be a major contributor to network congestion immediately following a disaster. They envision tracing clusters of trapped peoples where network usage is comparatively high. The Smart-Evac system ranks these clusters based on volume, velocity, and variety (the 3Vs of big data). Based on this ranking, the system provides immediate evacuation service to the top-listed clusters to mitigate the exponential rise of network congestion. The system used the analytical hierarchy process (AHP) to achieve the proper ranking of the clusters to support decision makers efficiently. In addition, Smart-Evac provides immediate cloud-based basic healthcare facilities and ambulatory medical services to victims after successful evacuation. Immediate priority-based healthcare in turn reduces the haphazard rush to nearby hospitals.