Vision about Connected City

Information and data are the wealth of today’s society, having evolved from a surveillance and control culture to a massive public and private manipulation of data, leading to the so-called big data paradigm that has allowed a shift away from the Information Age and Information Society to the Knowledge Society (Hilbert, 2013). However, the current overall availability of information and data does not necessarily imply knowledge without the capacity to validate, interpret and use the information.

The Global Pulse White Paper “Big Data for Development: Opportunities & Challenges” (Letouzé, 2012) raises the issue of how to use the digital data sources in the field of international development, and reports forthcoming possibilities of real time data and the new attitude of the data-driven decision making that have started to become a new way of thinking in the public sector. However, the extraction of knowledge from data is not new to the industry, considering what Google, Facebook and Amazon are doing to give services and evaluate new trends (e.g. Google Trends, breaking-news), but also the interconnection of small databases (Driscoll, 2012). Nowadays, massive data availability from the worldwide web allows tracking words, as well as locations, that are analysed and matched through several databases, allowing the prediction of people’s activities and making obsolete the expensive and time-consuming statistical surveys (Hilbert, 2013).

The understanding of the factors influencing mobility patterns and travel behaviour is the key to ensure the acceptance of innovations and services that could readdress the mobility patterns to more sustainable behaviours and optimize investments in transport systems. The behavioural analysis of the mobility patterns is a key to better plan and programme transport systems as well as to define Key Performance Indicators (KPIs) useful to the decision makers for improving mobility services.

An ambitious objective should be to reshape the mobility patterns of the contemporary cities also thanks to the knowledge through the use of big data and the active involvement of citizens. The challenge is to develop a framework for collecting, analysing and extracting urban mobility information from several sources to support:

  • planning and programming of public transport;
  • control of the quality of service;
  • managing mobility;
  • supplying new services for the customers.