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Title	Rendering 3D City For Smart City Digital Twin
ID_Doc	45049
Authors	Adreani L.; Colombo C.; Fanfani M.; Nesi P.; Pantaleo G.; Pisanu R.
Year	2022
Published	Proceedings - 2022 IEEE International Conference on Smart Computing, SMARTCOMP 2022
DOI	http://dx.doi.org/10.1109/SMARTCOMP55677.2022.00046
Abstract	The field of 3D city modelling has attracted a growing interest for representing the city digital twin, providing interactive visualizations of building infrastructures integrated with a wide range of data typically produced in a Smart City environment. This paper presents a method for producing a 3D city model with photorealistic rooftop textures extracted from aerial images, as well as the integration of the 3D city model into an open-source Smart City framework. The proposed solution provides a smart visualization of 3D city entities integrated with a large variety of Smart City data (coming, for instance, from IoT Devices which generate time-series data, heatmaps, geometries and shapes related to traffic flows, bus routes, cycling paths etc.). The proposed method for rooftop detection and alignment follows a deep learning approach based on U-Net architecture, and it has been validated against a manually created ground-truth of 50 buildings scattered uniformly on the covered area. The solution is implemented in the open-source Snap4City Smart City platform. DEMO: The solution will be demonstrated and the readers and conference attendees will be capable to interact and work with the tools by using the links provided. © 2022 IEEE.
Author Keywords	3D City model; digital twin; Photorealistic texture; Smart City applications

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