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 well-functioning 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.