|
Michael Ammann, Tuomas Peltonen, Juhani Lahtinen, Kaj Vesterbacka, Tuula Summanen, Markku Seppänen, et al. (2010). KETALE Web application to improve collaborative emergency management. In C. Zobel B. T. S. French (Ed.), ISCRAM 2010 – 7th International Conference on Information Systems for Crisis Response and Management: Defining Crisis Management 3.0, Proceedings. Seattle, WA: Information Systems for Crisis Response and Management, ISCRAM.
Abstract: KETALE is a database and web application intended to improve the collaborative decision support of the Finnish Radiation and Nuclear Safety Authority (STUK) and of the Finnish Meteorological Institute (FMI). It integrates distributed modeling (weather forecasts and dispersion predictions by FMI, source term and dose assessments by STUK) and facilitates collaboration and sharing of information. It does so by providing functionalities for data acquisition, data management, data visualization, and data analysis. The report outlines the software development from requirement analysis to system design and implementation. Operational aspects and user experiences are presented in a separate report.
|
|
|
Krispijn Scholte, & Leon J.M. Rothkrantz. (2014). Personal warning system for vessels under bad weather conditions. In and P.C. Shih. L. Plotnick M. S. P. S.R. Hiltz (Ed.), ISCRAM 2014 Conference Proceedings – 11th International Conference on Information Systems for Crisis Response and Management (pp. 359–368). University Park, PA: The Pennsylvania State University.
Abstract: Many services provide weather forecasts, including severe weather alerts for the marine. It proves that many ships neglect the warnings because they expect to be able to handle the bad weather conditions. In order to identify possible unsafe situations the Coast Guard needs to observe marine vessel traffic 24 hours, 7 days a week. In this paper we propose a system that is able to support the Coast Guard. Ships can be localized and tracked individually using the Automatic Identification System (AIS). We present a system which is able to send a personal alert to ships expected to be in danger now or the near future. Ships will be monitored in the dangerous hours and routed to safe areas in the shortest time. The system is based on AIS data, probabilistic reasoning and expertise from the Coast Guard. A first prototype will be presented for open waters around the Netherlands.
|
|
|
Ana Rosa Trancoso, José Delgado Domingos, Maria João Telhado, & João Corte-Real. (2011). Early warning system for meteorological risk in Lisbon municipality: Description and quality evaluation. In E. Portela L. S. M.A. Santos (Ed.), 8th International Conference on Information Systems for Crisis Response and Management: From Early-Warning Systems to Preparedness and Training, ISCRAM 2011. Lisbon: Information Systems for Crisis Response and Management, ISCRAM.
Abstract: The current work describes and evaluates an early warning system for meteorological risk in Lisbon that has been functioning in SMPC since February 2008. The system aims to integrate multiple sources of information and facilitate cross checking observations, forecasts and warnings, allowing for an efficient and timely evaluation of the alert level to issue. Currently, it comprises hourly weather and tide level forecasts and automated warnings for Lisbon city, given by MM5 and WRF models running at IST. Results show MM5 performing better than WRF except for warm weather. The overall skill of the warning system is 40% with some false alarm ratios, mainly for forecasts with more than 3 days in advance. This is a reasonable characteristic for early warning since a potentially problematic situation can be anticipated and checked avoiding unnecessary economic expenditures if the warnings do not persist.
|
|