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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