Design of DSS for supporting preparedness to and management of anomalous situations in complex scenarios

Research output: Chapter in Book/Report/Conference proceedingChapter (peer-reviewed)

8 Citations (Scopus)


Decision Support Systems (DSS) are complex technological tools, which enable an accurate and complete scenario awareness, by integrating data from both “external” (physical) situation and current behaviour and state of functioning of the technological systems. The aim is to produce a scenario analysis and to guess identify educated the most efficient strategies to cope with possible crises. In the domain of Critical Infrastructures (CI) Protection, DSS can be used to support strategy elaboration from CI operators, to improve emergency managers capabilities, to improve quality and efficiency of preparedness actions. For these reasons, the EU project CIPRNet, among others, has realised a new DSS designed to help operators to deal with the complex task of managing multi-sectorial CI crises, due to natural events, where many different CI might be involved, either directly or via cascading effects produced by (inter-)dependency mechanisms. This DSS, called CIPCast, is able to produce a real-time operational risk forecast of CI in a given area; other than usable in a real-time mode, CIPCast could also be used as scenario builder, by using event simulators enabling the simulation of synthetic events whose impacts on CI could be emulated. A major improvement of CIPCast is its capability of measuring societal consequences related to the unavailability of primary services such as those delivered by CI.
Original languageEnglish
Title of host publicationStudies in Systems, Decision and Control
PublisherSpringer International Publishing
Publication statusPublished - 2016


All Science Journal Classification (ASJC) codes

  • Computer Science (miscellaneous)
  • Decision Sciences (miscellaneous)
  • Economics, Econometrics and Finance (miscellaneous)
  • Automotive Engineering
  • Control and Systems Engineering
  • Control and Optimization
  • Social Sciences (miscellaneous)

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