  Digital Twins are digital replica of real entities and are becoming
fundamental tools to monitor and control the status of entities, predict their
future evolutions, and simulate alternative scenarios to understand the impact
of changes. Thanks to the large deployment of sensors, with the increasing
information it is possible to build accurate reproductions of urban
environments including structural data and real-time information. Such
solutions help city councils and decision makers to face challenges in urban
development and improve the citizen quality of life, by ana-lysing the actual
conditions, evaluating in advance through simulations and what-if analysis the
outcomes of infrastructural or political chang-es, or predicting the effects of
humans and/or of natural events. Snap4City Smart City Digital Twin framework is
capable to respond to the requirements identified in the literature and by the
international forums. Differently from other solutions, the proposed
architecture provides an integrated solution for data gathering, indexing,
computing and information distribution offered by the Snap4City IoT platform,
therefore realizing a continuously updated Digital Twin. 3D building models,
road networks, IoT devices, WoT Entities, point of interests, routes, paths,
etc., as well as results from data analytical processes for traffic density
reconstruction, pollutant dispersion, predictions of any kind, what-if
analysis, etc., are all integrated into an accessible web interface, to support
the citizens participation in the city decision processes. What-If analysis to
let the user performs simulations and observe possible outcomes. As case of
study, the Digital Twin of the city of Florence (Italy) is presented. Snap4City
platform, is released as open-source, and made available through GitHub and as
docker compose.
