Crisis scenarios

The aim of the Crisis scenarios module is to alert the various publics that a previously modeled situation is about to occur.

Corrective measures can then be implemented to avoid the consequences of the situation.

Crisis Scenarios use Machine Learning algorithms to contextualize situations identified by human analysis.

Data analysis is done retrospectively. It is therefore necessary to model the situations that must be monitored (determine objective criteria).

Each criterion represents a weak signal. As soon as several criteria occur within a particular time window, the situation escalates and becomes critical.

Each situation modeled in this way has a probabilistic indicator (probability of occurrence).

For more information on the future Crisis Scenarios feature, visit the Canopsis documentation.