Urban Intelligence: Toward the Digital Twin of Matera and Catania

Castelli, Giordana; Cesta, Amedeo; Ciampi, Mario; Benedictis, Riccardo De; Pietro, Giuseppe De; Diez, Matteo; Felici, G.; Malvezzi, Roberto; Masini, Barbara M.; Pellegrini, Riccardo; Scalas, Andreas; Stecca, Giuseppe; Strambini, Lucanos Marsilio; Tognola, Gabriella; Ravazzani, Paolo; Campana, Emilio F.

doi:10.1109/blorin54731.2022.10028437

Cited by 2 publications

(1 citation statement)

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“…These UI systems represent a paradigm shift in urban management, leveraging DTs, as well as data-driven insights, artificial intelligence, and interconnected networks to enhance the quality of life for citizens, while optimizing resource utilization. The adoption of UI based on DTs, and the integration of CPS, IoT, and data of the city, provide a cyber-physical counterpart to city systems, to increase the sustainable growth of the city and strengthening its functions, while ensuring the enhanced quality of life and health of the citizens [16,17]. Specific structures and IT technologies are necessary for the proper functioning of the DT context: network infrastructure, dedicated IoT sensor networks, information systems, and high-level web services, such as cloud or edge-computing environments [18], are required to collect and manage the heterogeneous data of the city [19,20] and to provide a proper hardware and software infrastructure to allow the execution of the required models, visualizations, and user interface functionalities [21,22].…”

Section: Introductionmentioning

confidence: 99%

An Urban Intelligence Architecture for Heterogeneous Data and Application Integration, Deployment and Orchestration

Silvestri,

Tricomi,

Bassolillo

et al. 2024

Sensors

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This paper describes a novel architecture that aims to create a template for the implementation of an IT platform, supporting the deployment and integration of the different digital twin subsystems that compose a complex urban intelligence system. In more detail, the proposed Smart City IT architecture has the following main purposes: (i) facilitating the deployment of the subsystems in a cloud environment; (ii) effectively storing, integrating, managing, and sharing the huge amount of heterogeneous data acquired and produced by each subsystem, using a data lake; (iii) supporting data exchange and sharing; (iv) managing and executing workflows, to automatically coordinate and run processes; and (v) to provide and visualize the required information. A prototype of the proposed IT solution was implemented leveraging open-source frameworks and technologies, to test its functionalities and performance. The results of the tests performed in real-world settings confirmed that the proposed architecture could efficiently and easily support the deployment and integration of heterogeneous subsystems, allowing them to share and integrate their data and to select, extract, and visualize the information required by a user, as well as promoting the integration with other external systems, and defining and executing workflows to orchestrate the various subsystems involved in complex analyses and processes.

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