Abstrait

Twitter Based Earthquake Alert System

Anitha.R , S.Selvakumar , V.Anusha Sowbarnika, N.Varatharajan

Twitter, a popular microblogging service, has received much attention recently. We investigate the real-time interaction of events such as earthquakes. Propose an algorithm to monitor tweets and to detect a target event. To detect a target event, we devise a classifier of tweets based on features such as the keywords in a tweet, the number of words, and their context. we produce a probabilistic spatiotemporal model for the target event that can find the center and the trajectory of the event location. We consider each Twitter user as a sensor and apply Kalman filtering and particle filtering. The particle filter works better than other compared methods in estimating the centers of earthquakes and the trajectories of typhoons. As an application, we construct an earthquake reporting system in Japan. Our system detects earthquakes promptly and sends e-mails and SMS alerts to registered users. Notification is delivered much faster than the announcements that are broadcast by the JMA.