Vehicle Data Activity Quantification Using Spatio-Temporal GIS on Modelling Smart Cities

Smart Cities are often defined as systems of systems
where a heterogeneity of digital services oriented to the wellfunctioning
of metropolises converge. It is essential to understand
where, when and how much digital data is generated since
upstream traffic is progressively growing, in volume and share.
One of the main challenges is how to work with continuous
time digital communication services for mobile entities. It may
become impractical or even infeasible to work in continuous time
when dealing with a large number of data generating entities.
Moreover, it is unclear how to integrate the contribution of
these services into a common framework together with other
Smart City oriented services. This integration would contribute
to understand distributed digital data activity in cities in a
holistic way. Consequently, we analyze how different ways of
discretizing services to work with a large number of vehicles
perform, compared to the continuous time case. We also integrate
them into a common framework for quantifying digital activity
in metropolitan areas. The experiments are carried out using
empirically collected spatio-temporal vehicle positioning data in
a real geographical scenario.