Data analytics and research

Using data as an analytical tool to inform the continuous and future development of cities

Main Output

    Big Data Analysis
    City Metrics Development
    Micro Mobility Planning
    Disruptive Mobility Systems Provisioning
    City Segmentation Analysis
    Neural Network Correlations
    Transport Policies Development

Is data-driven analysis unveiling the hidden potentials of assets?

Today, available mobility data has revolutionized the approach to traffic engineering, transforming transport planning into a more proactive and specific field of work. This evolution defies the more traditional static approach to traffic engineering, which depended on generic case study-based manuals, which often contradict the very concept of forecasting, as they base expected future behaviour on evidence from the past.

H2020 Diamond Project, Ratio of Female Residents in Province of Barcelona
H2020 Diamond Project, Ratio of Female Residents in Province of Barcelona
H2020 Diamond Project, Ratio of Elderly Residents in Province of Barcelona
H2020 Diamond Project, Ratio of Elderly Residents in Province of Barcelona

Properly analysed data has the capability to unveil the potential of any asset and reveal its benefits. The approach to urban analytics is a breakthrough in its capacity to transform specified information into an asset that can be utilised as an analytical tool to anticipate integrated cause-and-effect mechanisms that continuously feed into future forecasting processes.

We are leading innovative research activities aimed at collecting large-scale disaggregated data to support the design of gender-equitable and inclusive transport systems

H2020 Diamond Project, Roads and Public Transit in Province of Barcelona
H2020 Diamond Project, Roads and Public Transit in Province of Barcelona

How can Big Data change the way we plan cities?

In transportation planning, manual/automatic traffic counts and household/ personal travel surveys were historically conducted to collect travel behavior data. Today, available mobility data has created disruptive changes to this approach, placing the transport planner in a more proactive role and providing a set of analytical tools for any venture investor, city decision, or other planning experts seeking to improve urban mobility. Big Data for transportation is collected as anonymous and accurate location data from mainly two sources: Location Based Services (LBS) from applications installed on mobile devices and from navigation GPS systems in vehicles. Through complex algorithms, the data is processed and converted in mobility analytics metrics that can provide powerful insights on travel patterns, such as origin-destination matrices, trip length, travel speed, trip purpose, trip duration and socio-economics.

H2020 Diamond Project, Roads and Parking in Province of Barcelona
H2020 Diamond Project, Roads and Parking in Province of Barcelona

Tools

Big Data analytics and visualizations require a set of specialized tools adequate for processing and analyzing the data through complex computations.

Geographic Information System tools are useful to visualize georeferenced structured data

Neural Network Algorithmics is used mainly to treat, correlate and score large datasets aimed to identify the most relevant properties.

References projects

       
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