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Hoang Nam Ho, Mourad Rabah, Ronan Champagnat, & Frédéric Bretrand. (2019). Towards an Automatic Assistance in Crisis Resolution with Process Mining. In Z. Franco, J. J. González, & J. H. Canós (Eds.), Proceedings of the 16th International Conference on Information Systems for Crisis Response And Management. Valencia, Spain: Iscram.
Abstract: To deal with a crisis situation, experts must undertake a chain of activities, called process, to minimize crisis
consequences. To assist the expert in making decision in crisis resolutions, authors propose a method aiming at
discovering crisis response processes. This method is based on a two-step strategy: the first step classifies the
system?s traces, representing stakeholders? past actions, into different sets, where each one represents a set of
response processes according to a specific context; the second step uses process mining algorithm to discover
the corresponding response plan process model based on the obtained chain of activities for each previously
classified context. These response plans will be a referenced aid for experts while making crisis resolution,
according to each context. The proposed approach is illustrated on the traces issued from the crisis caused by the
2010 Xynthia storm in France.
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Quentin Schoen, Sébastien Truptil, Franck Fontanili, Matthieu Lauras, & Anne-Ghislaine Anquetil. (2017). Tracking in real time the blood products transportations to make good decisions. In eds Aurélie Montarnal Matthieu Lauras Chihab Hanachi F. B. Tina Comes (Ed.), Proceedings of the 14th International Conference on Information Systems for Crisis Response And Management (pp. 173–180). Albi, France: Iscram.
Abstract: The French Blood Establishment (EFS) is the only one in France allowed dealing with the blood supply chain. The EFS centers are scattered in France and blood products are transported over hundreds of kilometers, from collection sites to hubs and from the hubs to distribution sites. The strong constraints on lifetime and storage conditions imply a traceability of transportation steps very accurate, which is necessary in case of unexpected and unwanted events. To make “good” decisions, we propose in this research work to use the Physical Internet philosophy. Thanks to sensors in containers and Complex Event Processing modules to aggregate and filter the data collected, we would be able to create a real time “field model”. In case of crisis this model would be helpful and perfectly adapted to help the crisis unit to make “good” decisions and maybe propose solutions based on the past events.
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