Disruptive technologies empowering decision-making in the public sector, sharing our results adopting a data-driven approach , 25th May at 15:30.
Transport planning plays a major role in defining the way public resources such as funds and spaces are used. This is also the case in Helsinki, Finland.
The Chief Technology Office (CTO) of the Municipality of Amsterdam and Waag are exploring innovative ways of collaborating with businesses and societal organisations on data collection and sharing
The URBANITE integrated architecture presents a theoretical vision of the URBANITE system covering all the functional and non-functional initial requirements set by the technical work-packages.
A data-driven policy-making aims to make optimal use of data and collaborate with citizens to co-create urban policies and, in general, to conduct a more reliable decision-making process.
The urban transformation, and the changes that the world is undergoing, lead, today more than ever, to the need to make faster and more timely choices in the field of mobility management.
During 2021, 4 General Virtual Assemblies were held. Due to COVID-19, the meeting was held online using Teams.
How disruptive technologies can strengthen urban mobility transformation, the experience of URBANITE
Today’s cities are facing a revolutionary era in urban mobility and decision-makers have to face more and more complex challenges when managing and planning mobility.
Creating simulation scenarios for the four cities included in the URBANITE project, those being Bilbao, Amsterdam, Helsinki and Messina, is a part of the activities performed by the URBANITE team.
Giovanni Parrino, Francesco Martella, Giuseppe Ciulla, Roberto Di Bernardo,
The scope of URBANITE SoPoLab, which stands for Social Policiy Lab, is
In the last 25 years Bilbao has suffered an important urban transformation from an industrial economy with heavy industry and harbour facilities to a city based on a service economy.
Mobility policy needs to include citizens - after all, we are all experts on the way we move about in our daily lives.
The Urbanite project will provide technical support to decision-makers in the domain of urban mobility. This support takes the form of predictive models constructed by specialized AI algorithms.
Due to digitalization, there is a growing number of traffic and mobility data available for the cities to use world-wide. It is usually in the interest of cities to take control over this data.
In the context of URBANITE, we are currently performing a survey of existing methods for data modelling and visualizations that could apply to the urban mobility planning domain.
As reported in “eGovernment Benchmark 2016. A turning point for eGovernment development in Europe?”,
Urban mobility faces more significant long-term uncertainty and complexity generated by two main factors: the demand for growth in urban environments, the pressure