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
