Mobility and prediction : an asset for crisis management
Résumé
Recommendations have long been a means of helping users select services.
In a smart city environment, recommendation algorithms should take into account
the user’s context to gain in accuracy. What is the context of a smart city user
and how can it be captured? These are the two questions we answer in this paper.
After specifying what we understand by context information, we show how the city’s
mobility pattern can be used to infer rich contextual information. The main objective
of our project will be finally to recommend services according to an estimated trajectory
of a user in the smart city. For the application domains that we wish to consider
in the future we have: emergency situation and crisis management that are among the
most crucial dimensions of smart and future cities design.