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Technological solution for urban mobility planning

Data-driven sustainable urban mobility planning

The problem

Traffic management in cities and mobility planning has historically been carried out in a very manual way, through the collection of data with household surveys, with samples that are not entirely representative and static, without taking into account other particularities such as night or weekend mobility and, therefore, with enormous biases in these studies.

The opportunity

Thanks to Artificial Intelligence (Machine and Deep Learning) and the Internet of Things (IoT), there is an opportunity to collect mobility data in real time, to collect in much larger and more representative samples, to extract value from all this data of great use for mobility consultants or the corresponding public institutions and, in short, to possess relevant and updated information in real time.

What is MathIT.Motus?

MathIT.Motus is a powerful technological solution capable of analyzing huge volumes of information related to the geolocation of citizens in real time and extracting and inferring information such as origin-destination matrices with the desired granularity, user profiles, means of transport used, usage times, associated costs, mobility generator and attractor points, etc.

All this in an automated, anonymized and fully updated way in real time.

Business value

The elimination of statistical bias in this type of study will help public institutions (mainly city councils) and mobility consultants to make better decisions, to plan more reliably, to predict whether a mobility infrastructure will be used or not, to design more sustainable urban mobility plans, etc.

Why MathIT.Motus?

  

  

 

  

 

  

oga MathIT.Motus

MathIT.Motus is an important part of your solution.