• social sensing
• crowdsensing
• opportunistic sensing
• participatory sensing
• social mining

Our project aims to create, implement and deploy a platform based on a decision support system for gathering eyewitness reports to improve the situation-awareness in the aftermath of an emergency, focusing in particular on earthquakes. While doing so, we would like to find out if an approach combining opportunistic and participatory sensing methods is possible. Our system, in fact, focuses on detecting eyewitnesses with an opportunistic approach and then aims to transform these potential eyewitnesses into volunteers willing to share information.

The platform retrieves earthquake notifications from an official channel and, immediately after, exploits the messages shared on Twitter for a fixed time-slot. In doing so, we collect messages posted by potential eyewitnesses. Data mining and natural language processing techniques are performed in order to select meaningful and comprehensive sets of tweets. We then concentrate on the filtered tweets in order to try to engage with their authors and enhance situation awareness.

Information retrieved by our system can be extremely useful to all the government agencies interested in mitigating the impact of earthquakes, as well as news agencies looking for new information to publish.