Pervasive and Mobile Computing ( IF 2.725 ) Pub Date : 2020-07-25 , DOI: 10.1016/j.pmcj.2020.101225
Marco Avvenuti; Salvatore Bellomo; Stefano Cresci; Leonardo Nizzoli; Maurizio Tesconi

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.

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