EARS (earthquake alert and report system)

Abstract

Social sensing is based on the idea that communities or groups of people can provide a set of information similar to those obtainable from a sensor network. Emergency management is a candidate field of application for social sensing. In this work we describe the design, implementation and deployment of a decision support system for the detection and the damage assessment of earthquakes in Italy. Our system exploits the messages shared in real-time on Twitter, one of the most popular social networks in the world. Data mining and natural language processing techniques are employed to select meaningful and comprehensive sets of tweets. We then apply a burst detection algorithm in order to promptly identify outbreaking seismic events. Detected events are automatically broadcasted by our system via a dedicated Twitter account and by email notifications. In addition, we mine the content of the messages associated to an event to discover knowledge on its consequences. Finally we compare our results with official data provided by the National Institute of Geophysics and Volcanology (INGV), the authority responsible for monitoring seismic events in Italy. The INGV network detects shaking levels produced by the earthquake, but can only model the damage scenario by using empirical relationships. This scenario can be greatly improved with direct information site by site. Results show that the system has a great ability to detect events of a magnitude in the region of 3.5, with relatively low occurrences of false positives. Earthquake detection mostly occurs within seconds of the event and far earlier than the notifications shared by Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from permissions@acm.org.

Optimizing disaster communication for future fire mitigation

“…Media to detect disasters that can be used include mass media, Instagram, Facebook, Twitter, and youtube [32][33][34][35]. Media is a valuable means of communication because it can be a source of information to increase public awareness, although it is still rarely adopted.…”

“…The media can be framed as a source of information so that people can trust the messages conveyed through the media [31]. Existing social media and mass media can be used for disaster communication and provide information related to mitigation and early detection of various types of disasters [29,[32][33][34][35][36][37].…”

Urgent Computing for Protecting People From Natural Disasters

“…Other studies on the use of social media data for signaling natural disasters have recently been carried out. For example, Avvenuti et al 8 developed the Earthquake Alert and Report System (EARS), which analyzes streaming data from Twitter for detecting seismic events. Such a system exploits a burst-detection algorithm to identify earthquakes from tweets, and processes the corpus of each message for determining the impact of the seismic events on people and infrastructure.…”

Multidimensional report analysis in urban incident management

“…Nagarajan, Gomadam, Sheth, et al present a system which analyzes tweets on three dimensions of theme, time, and space [3]. Similarly, Avvenuti, Cresci, Marchetti, et al provide a framework, which uses temporal reasoning (in terms of burst detection) and semantic analysis to assist real-time decision-making for earthquake crisis management [4]. In either case, however, spatio-temporal analysis is limited to the time and location of the report and not the incident to which the report refers.…”