Project Funded by Ministerio de Economía, Indústria y Competitividad with project number: RTC-2017-6094-4, Retos-Colaboración 2017 program. Partners: System, Virtualdesk and Universidad Politécnica de Madrid.


Project Partners: 
Start Date: 
Saturday, 1 September 2018 to Thursday, 30 April 2020
Optimized mobility by Big-Data, Integrated Information and Multi-modal Algorithmics

MOBIAM makes mobility information accurate, continuous and multi-modal, dramatically improving solutions based on surveys and reducing the cost; creating a comprehensive platform that integrates data mobility for pedestrians, private vehicle and transport and exogenous variables to characterize the modal mobility, origin-destination matrices generate multi-modal and predict future demand and mobility.



Vehicular congestion is a global problem that generates significant economic losses (between 2% and 4% of GDP) and a drastic deterioration of the environment and health (7 million premature deaths from air pollution). This problem is even more important in urban areas and will worsen in the coming years with the excessive population growth in cities.

In recent years, both public administration through policies to reduce fossil fuel consumption and emission of greenhouse gases, as a global mobility market has exceeded 400 trillion euros, have responded to the obvious demand for technological solutions to mitigate the problem. But so far, there has even managed to curb the effect.

The problem of urban mobility must be addressed from a global perspective of its main modes of transport: private vehicle, public transport and pedestrians. It is therefore necessary to have an integrated, accurate, continuous and limited cost. To date, this information is collected through surveys that do not meet any of these requirements by relying on a small sample of the population, which produces results without updating for over 10 years at a high cost in excess of 2 million euros for Community .



MOBIAM born with the aim of achieving a comprehensive settlement of mobility. To do so, it creates an integral platform mobility MOBIAM PIMOV which integrates data from each transport mode, build modules bigdata for modal characterization of urban areas, generates algorithms joint operation of the multi-modal mobility and builds modules prediction to improve their overall performance.

Data on mobility of private vehicles and pedestrians come from two information systems based on Bluetooth and Wi-Fi identification respectively developed by the Group of Biometry, Biosignals, Security and SmartMobility (GB2S) of the Polytechnic University of Madrid. Meanwhile, public transport data are accessed through a big-data platform created by VIRTUALDESK. Finally, the platform will be supported MOBIAM PIMOV based on the SMART smart city platform, provided by SISTEM. In this way, the project focuses on investing maximum effortin the development of the not yet existing solutions in the market. 





The MOBIAM project generates a product catalog information on urban mobility, integrated into a platform capable of monitoring the various modes of transport, characterize global mobility and the impact of meteorological and environmental factors, measure their performance and representative Multimodal variables and predict future demand.

For the development of this product catalog, the project is designed with the following structure: