Introducing the EUMigraTool (EMT)

The EMT is a solution-oriented tool with two main functions:
(I) Predicting migration flows
(II) Detecting risks of tensions related to migration
The backend of EMT comprises two complementary approaches to:
SIMULATION: based on agent-based modelling
FORECASTING: relies on deep learning architectures based on recent bibliography that enable the extraction of semantic information for several sources of information. This translates into the creation of joint probability distribution models of the events driving migration with the input signals from the information sources.



The EUMigraTool includes analysis of media content from TV-news (video content), web-news and social media (text content) using deep learning and proposing novel deep architectures in generative modelling and forecasting using sequential data. Predictions incorporate algorithms that consider the two key challenges associated with prediction of migration: (a) Adequate selection of relevant data sources, and (b) correct selection of the potential drivers to be monitored and to the warning thresholds to be set.
The EMT detects and identifies individual needs among migrants prior to their arrival in Europe
helping end-users to further analyse mixed migration flows and
to distinguish persons in need of International Protection (eligible for asylum status)
from those in different migration situations who, in the absence of legal routes, use illegal methods.


EMT is able to account for entry quote when forecasting migratory flows,
having a real number of migrants arriving to a particular country and region, helping NGOs understand the human
effort and material resources that need to be allocated in that particular territory before the arrival.


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