Urban Intelligence: A Modular, Fully Integrated, and Evolving Model for Cities Digital Twinning

The Urban Intelligence (UI) paradigm proposes an ecosystem of technologies to improve urban environment, wellbeing, quality of life and smart city systems. It fosters the definition of a digital twin of the city, namely a cyber-physical counterpart of all the city systems and sub-systems. Here we propose a novel approach to UI that extends available frameworks combining advanced multidisciplinary modelling of the city, simulation and learning tools with numerical optimization techniques, each of them specialized for the digital representation of city systems and subsystems, including not only city infrastructures, but also city users and their interactions. UI provides sets of candidate policies in complex scenarios and supports policy makers and stakeholders in designing sustainable and personalized solutions. The main characteristics of the proposed UI architecture are (a) fully multidisciplinary integration of city layers, (b) connection and evolution with the city, (c) integration of participative strategies to include 'human-oriented' information, and (d) modularity of application.

Tipo Pubblicazione: 
Contributo in atti di convegno
Author or Creator: 
Castelli Giordana (1)
Tognola Gabriella (2)
Campana Emilio Fortunato (1)
Cesta Amedeo (3)
Diez Matteo (4)
Padula Marco (5)
Ravazzani Paolo (2)
Rinaldi Giovanni (6)
Savazzi Stefano (2)
Spagnuolo Michela (7)
Strambini Lucanos (2)
Publisher: 
IEEE, New York, USA
Source: 
2019 IEEE 16th International Conference on Smart Cities: Improving Quality of Life Using ICT & IoT and AI (HONET-ICT), pp. 33–37, Charlotte, NC, USA, USA, 6-9/10/2019
info:cnr-pdr/source/autori:Castelli Giordana (1); Tognola Gabriella (2); Campana Emilio Fortunato (1); Cesta Amedeo (3); Diez Matteo (4); Padula Marco (5); Ravazzani Paolo (2); Rinaldi Giovanni (6); Savazzi Stefano (2); Spagnuolo Michela (7); Strambini Lu
Date: 
2019
Resource Identifier: 
http://www.cnr.it/prodotto/i/418400
https://dx.doi.org/10.1109/HONET.2019.8907962
info:doi:10.1109/HONET.2019.8907962
https://ieeexplore.ieee.org/document/8907962/authors#authors
urn:isbn:978-1-7281-3971-5
Language: 
Eng