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 crowdsensing, 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 7x) and the variety (up to 18x) of the retrieved geographic information; (iii) the geographic coverage (up to 30%) and granularity.
翻译:在这项工作中,我们介绍了HERMES,这是一个旨在丰富OSN用户在灾害发生后自发披露信息的系统。HERMES利用了混合数据收集战略,称为混合人群感测和最新的AI技术。在现实世界紧急情况下,HERMES已证明增加了:(一) 现有损坏信息的数量;(二) 检索到的地理信息的密度(最多为7x)和种类(最多为18x);(三) 地理覆盖范围(最多为30%)和颗粒度。