Integration of Heterogeneous Coronavirus Disease Covid-19 Data Sources Using Ogc Sensorthings Api

Environment and Planning B: Urban Analytics and City Science

Coors

2020

Devices from the Internet of Things are being increasingly used in everyday life, and they provide a massive amount of data in various formats. While implementing the Smart Cities initiative, these data are integrated and utilized together with the 3D city model for further applications. Based on Open Geospatial Consortium standards, heterogeneous sensor data can be integrated with the Open Geospatial Consortium SensorThings Application Programming Interface. Similarly, the 3D city model data can be stored and exchanged with the Open Geospatial Consortium CityGML format. However, currently, there is no concrete model to integrate these sensor data with the 3D city model using the Open Geospatial Consortium standards. The existing solution for integrating the sensor data into the 3D city model requires an extension or plug-in for adding the data to the CityGML model. In this paper, we introduce the concept of “CityThings” to integrate dynamic sensor data from the Open Geospatial Consortium SensorThings API into the CityGML 3D city models. We demonstrate the implementation of the CityThings concept in the Smart Villages project in the study area of Wüstenrot, Germany, by integrating dynamic sensor data from several systems including solar panels, agro-thermal plants, and weather monitoring sensors to visualize the sensor data with the 3D city model on the web platform. In the future, this concept can be applied to interconnect dynamic sensor data and 3D city model data in other Smart Cities applications.

Section: Methodsmentioning

confidence: 99%

Section: Methodsmentioning

confidence: 99%

CityThings: An integration of the dynamic sensor data to the 3D city model

Environment and Planning B: Urban Analytics and City Science

Coors

2020

“…After STA has been implemented, the client application can get the data via the resource path as shown in listing 1. STA had been widely applied to manage the heterogeneous data in our past research works in fields of mobility (Santhanavanich et al, 2018, Santhanavanich et al, 2020b, urban environmental (Ebrahim et al, 2021), and health (Santhanavanich et al, 2020a). Accordingly, the STA can optimize data delivery of spatio-temporal data to urban energy applications.…”

Section: Spatiotemporal Datamentioning

confidence: 99%

The Spatial Data Infrastructure of an Urban Digital Twin in the Building Energy Domain Using Ogc Standards

ISPRS Ann. Photogramm. Remote Sens. Spatial Inf. Sci.

Padsala

Würstle

et al. 2022

Abstract. As the world has more urbanized, cities need to assess and manage their building energy performances in order to achieve energy-reduction goals. The urban digital twins (UDT) offer promising solutions to this demand by providing valuable insights with qualitative and quantitative information about the building environment. The urban building energy data is not only measured from the equipped sensor devices but can also be simulated based on the analysis software. In this research, we aim to explore the development of the spatial data infrastructure (SDI) for managing building energy in the UDT application by employing the Open Geospatial Consortium (OGC) standards which increases the data usability and efficiency. In our concept SDI, the big data in the UDT application is managed with the OGC specifications as follows: OGC SensorThings API (STA) for data with Spatio-temporal characteristics, OGC API 3D GeoVolumes for 3D geospatial content delivery, OGC CityGML for virtual 3D city models, OGC API Features, Web Feature Service (WFS), and Web Map Service (WMS) for other 2D geospatial contents. This concept enables broad interoperability between multiple data layers and client applications. As a proof of concept, we developed the UDT application called with a highly visual and intuitive user interface using the proposed SDI concept as a part of the EnSysLE project in the study area of three regions in Germany: Ludwigsburg, Dithmarschen, and Ilm-Kreis. The proposed concept can be expanded to other UDT domains and on a larger scale in future work.

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

iCity. Transformative Research for the Livable, Intelligent, and Sustainable City

Sihombing

Kabiro

et al. 2022

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.