Storing and Visualising Dynamic Data in the Context of Energy Analysis in the Smart Cities

Thunyathep Santhanavanich (), Rosanny Sihombing, Pithon Macharia Kabiro, Patrick Würstle and Sabo Kwado Sini
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Thunyathep Santhanavanich: Hochschule für Technik Stuttgart
Rosanny Sihombing: Hochschule für Technik Stuttgart
Pithon Macharia Kabiro: Hochschule für Technik Stuttgart
Patrick Würstle: Hochschule für Technik Stuttgart
Sabo Kwado Sini: Hochschule für Technik Stuttgart

Chapter 16 in iCity. Transformative Research for the Livable, Intelligent, and Sustainable City, 2022, pp 251-265 from Springer

Abstract: Abstract There is increased activity in developing workflows and implementations in the context of urban energy analysis simulation based on 3D city models in smart cities. At the University of Applied Sciences Stuttgart (HFT Stuttgart), an urban energy simulation platform called ‘SimStadt’ has successfully been developed. It uses the CityGML 3D city model to simulate the heat demand, photovoltaic potential, and other scenarios that provide dynamic simulation results in both space and time dimensions. Accordingly, a tool for managing dynamic data of the CityGML models is required. Earlier, the CityGML Application Domain Extension (ADE) had been proposed to support additional attributes of the CityGML model; however, there is still a lack of open-source tools and platforms to manage and distribute the CityGML ADE data efficiently. This article evaluates and compares alternative methods to manage dynamic simulation results of the 3D city model and visualise these data on the 3D web-based smart city application, including the use of SimStadt web services, databases, and OGC SensorThings API standard.

Keywords: Urban energy analysis; 3D building model; CityGML; 3D tiles; SensorThings; Smart cities; SimStadt (search for similar items in EconPapers)
Date: 2022
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DOI: 10.1007/978-3-030-92096-8_16

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