As the deployment of situational awareness mechanisms such as geothermal sensors, use of social network sites, and information and communication technologies (e.g., cell phones) become increasingly widespread to emergency responders, the problem of alert analysis has become very important. Broadcast of large amounts of alerts sent back to command centers for processing may impair the ability of analysts to connect dots that may otherwise adequately enable them to make informed decisions in a timely fashion. This paper investigates trends and patterns embedded in alert notifications generated over a given period of time in order to uncover correlations that may exist in the data. Data for this study are obtained from the National Center for Crisis and Continuity Coordination (NC4). We employ classical time series analysis to understand, explain and predict trends and patterns in the data. This work presents results obtained thus far in the quest for the effect of passage of time on alert patterns. Implications of this work in practice and research are discussed.
|Published - Jan 1 2010
|7th International Conference on Information Systems for Crisis Response and Management, ISCRAM 2010 - Seattle, WA, United States
Duration: May 2 2010 → May 5 2010
|7th International Conference on Information Systems for Crisis Response and Management, ISCRAM 2010
|5/2/10 → 5/5/10
All Science Journal Classification (ASJC) codes
- Information Systems