Towards better social crisis data with HERMES: Hybrid sensing for EmeRgency ManagEment System

被引：1
|
作者：
Avvenuti M. [1 ]
Bellomo S. [2 ]
Cresci S. [2 ]
Nizzoli L. [1 ,2 ]
Tesconi M. [2 ]
机构：
[1] Department of Information Engineering, University of Pisa
[2] Institute of Informatics and Telematics, National Research Council (IIT-CNR)
来源：
Pervasive and Mobile Computing | 2020年 / 67卷
基金：
欧盟地平线“2020”;
关键词：
Artificial intelligence; Emergency management; Human-as-a-sensor; Hybrid sensing; Online social networks;
D O I：
10.1016/j.pmcj.2020.101225
中图分类号：
学科分类号：
摘要：
People involved in mass emergencies increasingly publish information-rich contents in Online Social Networks (OSNs), thus acting as a distributed and resilient network of human sensors. In this work we present HERMES, a system designed to enrich the information spontaneously disclosed by OSN users in the aftermath of disasters. HERMES leverages a mixed data collection strategy, called hybrid sensing, and state-of-the-art AI techniques. Evaluated in real-world emergencies, HERMES proved to increase: (i) the amount of the available damage information; (ii) the density (up to 7×) and the variety (up to 18×) of the retrieved geographic information; (iii) the geographic coverage (up to 30%) and granularity. © 2020 Elsevier B.V.
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