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Running a city is about data management

Uber Movement is an initiative that offers city authorities access to all information about the location of their vehicles in real time to help manage traffic flows.

The move, an attempt by the company to improve relations and communication with city authorities which in many cases have not always been particularly easy. But the simple truth is that cities have become highly complex ecosystems whose management requires efficient information processing.

We are seeing it more and more every day: measures such as the total or partial restriction of traffic, for example, such as those currently in force in several French cities due to pollution, depend on real-time readings of pollution sensors and a careful study of weather patterns. Controling parking spaces through data provided by applications or knowing how many people are using public transport at a given time are just a few examples of how municipal teams are creating information-rich environments.

Our increasingly large cities are becoming more and more difficult to manage, and require more efficient management of intelligence and data. Bestiario’s mapping project of the number of commuting trips in Barcelona using the aggregated anonymous data of 300,000 mobile phone users, the study of urban transport movement in several Latin American cities, or Telefónica’s Smart Steps project are clear examples of how to study urban mobility, requiring not only access to data but also the development of adequate systems of representation, visualization and management.

So-called smart cities are places where data is generated and used for their management. City Halls around the world are beginning to see the need to incorporate skills once more typical of other types of environments: how to deal with traffic-related pollution? Reduce the number of vehicles by half depending on the number and the day of the month, or restrict vehicles that pollute the most? A difficult decision, and one that involves taking into account all kinds of factors, and that would clearly benefit from properly monitoring as much data as possible.

How to effectively monitor the deterrent effect of parking restrictions or an urban toll system? Should we invest in an autonomous bus transport system that covers certain routes, such as Helsinki or Las Vegas have done? Soon, more and more cities will be ecosystems in which we will practically log in, in which our movements and those of our vehicles will be inputted into databases that protect our privacy. In Singapore or London, information on vehicle movements can be monitored in real time by cameras, which are also used to charge for access to certain parts of the city. In Amsterdam, you have to sign on when entering and leaving trams, in order to generate the appropriate information.

One of the factors that will determine decisions such as to approve the operation of a given service in a city could be its contribution to a municipal API that provides information to its managers and under an open data model, allows developers to come up with applications to make cities better places to live and work. Apps such as Citymapper, Moovel, Waze and others monitor and assist people on the move, producing maps in real time that could be of use to city authorities.

When we talk about smart cities, we have to consider the possibilities that the management of the data provided by the various agents operating in it, along with the sensors deployed within their infrastructure may offer.

In many ways, the round table I had the opportunity to attend in Detroit with the mayors of Atlanta, Chicago, Columbus and Detroit made it clear to me that managing cities, from restrictions on the construction of housing or on parking is becoming increasingly professionalized. City authorities must now be real-time information managers: not skills we normally associate with our local politicians. The question we have to ask them is whether they are prepared to join this transition?

(En español, aquí)

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