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Communication Dans Un Congrès Année : 2017

Processing, mining and visualizing massive urban data

Résumé

The development of smart technologies and the advent of new observation capabilities have increased the availability of massive urban datasets that can greatly benefit urban studies. For example, a large amount of urban data is collected by various sensors, such as smart meters, or provided by GSM, Wi-Fi or Bluetooth records, ticketing data, geotagged posts on social networks, etc. Analysis of such digital records can help to build decision-making tools (for analytical, forecasting and display purposes) with a view to better understanding the operating of urban systems, to enable urban stakeholders to plan better when extending infrastructures and to provide better services to citizens in order to assist the development of the city and improve quality of life. This paper will focus on three main domains of application: transportation and mobility, water and energy.
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Dates et versions

hal-01570792 , version 1 (31-07-2017)

Identifiants

  • HAL Id : hal-01570792 , version 1

Citer

Pierre Borgnat, Etienne Come, Latifa Oukhellou. Processing, mining and visualizing massive urban data. ESANN2017, 25th European Symposium on Artificial Neural Networks, Computational Intelligence and Machine Learning, Apr 2017, Bruges, Belgium. 10p. ⟨hal-01570792⟩
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