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.

翻译：数字孪生是真实实体的数字化副本，已成为监测与控制实体状态、预测其未来演化、以及模拟不同场景以理解变更影响的核心工具。得益于传感器的大规模部署，日益增长的信息使构建包含结构数据与实时信息的城市环境精准复现成为可能。此类解决方案通过分析实际状况、借助模拟与假设场景分析预先评估基础设施或政策变更的结果、或预测人类活动和/或自然事件的影响，助力市政当局与决策者应对城市发展挑战并提升市民生活质量。Snap4City智能城市数字孪生框架能够回应文献及国际论坛所识别的需求。与其他方案不同，本架构通过Snap4City物联网平台提供数据采集、索引、计算与信息分发的集成解决方案，从而构建持续更新的数字孪生体。三维建筑模型、道路网络、物联网设备、万维网实体、兴趣点、路径轨迹等，以及交通密度重构、污染物扩散、各类预测、假设场景分析等数据分析处理结果，均集成于可访问的Web界面中，以支持市民参与城市决策过程。假设场景分析功能使用户可执行模拟并观察可能结果。以意大利佛罗伦萨市为例进行案例研究。Snap4City平台以开源形式发布，通过GitHub和Docker Compose提供。