• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.39 no.5
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• pp.297-311
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• 2021

Around the world, there is an increasing interest in Digital Twin cities. Although geospatial data is critical for building a digital twin city, currently-established spatial data cannot be used directly for its implementation. Integration of geospatial data is vital in order to construct and simulate the virtual space. Existing studies for data integration have focused on data transformation. The conversion method is fundamental and convenient, but the information loss during this process remains a limitation. With this, standardization of the data model is an approach to solve the integration problem while hurdling conversion limitations. However, the standardization within indoor space data models is still insufficient compared to 3D building and city models. Therefore, in this study, we present a comparative analysis of data models commonly used in indoor space modeling as a basis for establishing a generic indoor space feature model. By comparing five models of IFC (Industry Foundation Classes), CityGML (City Geographic Markup Language), AIIM (ArcGIS Indoors Information Model), IMDF (Indoor Mapping Data Format), and OmniClass, we identify essential elements for modeling indoor space and the feature classes commonly included in the models. The proposed generic model can serve as a basis for developing further indoor feature models through specifying minimum required structure and feature classes.

• Spatial Information Research
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• v.21 no.2
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• pp.11-21
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• 2013

W ith the recent increasing build and application for 3D spatial information, the importance of management and application for spatial information based on indoor space has been increased. Especially, Due to the increasing of the scale and complexity of the building according to the development of construction technologies several studies have been conducted to provide the services based on indoor space such as indoor navigation for disaster. Therefore, to efficient manage and service for information of complicated indoor space, it is necessary to extend and develop 3D spatial model and services that have been developed for outdoor space. In this paper, Indoor Spatial Data Model(ISDM) is developed to support building spatial information for complicated indoor space and location based services through topological information. ISDM contains a feature model which is a CityGML Application Domain Extension(ADE) model and a topology model that refers the IndoorGML.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.32 no.2
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• pp.143-151
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• 2014

As the interest in indoor space increases, the demands for various services based on indoor space is increasing. With the demands, to construct spatial information for indoor space is also required, but there is not defined the LOD(Level of Detail) for indoor spatial data. Therefore, in this paper we classified data for indoor space data construction, and then we defined the accuracy and detail about the level of detail to provide suitable application services according to the type and representation method of each data. Most previous researches are focus on the geometrical representation, but in this paper we define a indoor LOD model based on type and representation method of data. In addition, we present applicable services with proposed LOD model and suggest a guideline for construction and application of indoor space.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.38 no.6
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• pp.611-622
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• 2020

As the advancement of technologies on indoor positioning systems and measuring devices such as LiDAR (Light Detection And Ranging) and cameras, the demands on analyzing and searching indoor spaces and visualization services via virtual and augmented reality have rapidly increasing. To this end, it is necessary to model 3D objects from measured data from real-world structures. In addition, it is important to store these structured data in standardized formats to improve the applicability and interoperability. In this paper, we propose a method to construct IndoorGML data, which is an international standard for indoor modeling, from point cloud data acquired from LiDAR sensors. After examining considerations that should be addressed in IndoorGML data, we present a construction method, which consists of free space extraction and connectivity detection processes. With experimental results, we demonstrate that the proposed method can effectively reconstruct the 3D model from point cloud.

• Spatial Information Research
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• v.16 no.4
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• pp.441-453
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• 2008

With the rapid progress of location based services, GIS, and ubiquitous computing technologies, the space that we are dealing with is no longer limited to outdoor space but being extended to indoor space. Indoor space has some differences from outdoor space, therefore to provide integrated spaces and seamless services, it is required to establish new theories, data models, and systems. For this reason, ambitious project has been launched last year to establish a theoretical background, develop a core technologies and systems, and provide services of indoor spatial awareness. In this paper, we present an overall sketch on the project and major research topics. First, we present the ISA (indoor spatial awareness) project with its goal and research topics. Second, a simplified 3D spatial model, called prism model, is proposed as a basic data types and operators of indoor spatial DBMS. Third, a indoor feature data model, developed T. Kolbe et al. who is a member of this project team, is introduced in this paper. This model provides a basis for the integration of different spaces.

• Spatial Information Research
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• v.21 no.5
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• pp.73-82
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• 2013

In recent years, according to the increase of interests in indoor space, various researches are being carried out for the construction and services of indoor spatial information. BIM data is very useful to build indoor spatial information. Accordingly, many studies for the use of BIM data on GIS part are in progress. In order to take advantage of BIM data on GIS part, the conversion technology for building indoor data and visualization techniques are required. However, most of the previous researches are focused on the conversion technology to construct indoor spatial information by importing BIM data into GIS applications while there is few research on visualization. In this study, an indoor LOD(Level of Detail) model is proposed to apply to on indoor facility management system when indoor data was constructed based on BIM data for the linkage between BIM and GIS.

• Spatial Information Research
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• v.22 no.2
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• pp.31-44
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• 2014

According to the purpose of applications, the application program will utilize the most suitable data model and 3D modeling data would be generated based on the selected data model. In these reasons, there are various data sets to represent the same geographical features. The duplicated data sets bring serious problems in system interoperability and data compatibility issues, as well in finance issues of geo-spatial information industries. In order to overcome the problems, this study proposes a spatial data fusion method using topological relationships among spatial objects in the feature classes, called Topological Relation Model (TRM). The TRM is a spatial data fusion method implemented in application-level, which means that the geometric data generated by two different data models are used directly without any data exchange or conversion processes in an application system to provide indoor LBSs. The topological relationships are defined and described by the basic concepts of IndoorGML. After describing the concepts of TRM, experimental implementations of the proposed data fusion method in 3D GIS are presented. In the final section, the limitations of this study and further research are summarized.

• Spatial Information Research
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• v.22 no.1
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• pp.65-73
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• 2014

Recently indoor navigation with indoor map such as Indoor Google Maps is served. For the services, constructing indoor data are required. CityGML and IFC are widely used as standards for representing indoor data. The data models contains spatial information for the indoor visualization and analysis, but indoor navigation requires semantic and topological information like graph as well as geometry. For this reason, IndoorGML, which is a GML3 application schema and data model for representation, storage and exchange of indoor geoinformation, is under standardization of OGC. IndoorGML can directly describe geometric property and refer elements in external documents. Because a lot of data in CityGML or IFC have been constructed, a huge amount of construction time and cost for IndoorGML data will be reduced if CityGML can help generate data in IndoorGML. Thus, this paper suggest practical use of CityGML including deriving from and link to CityGML. We analyze relationships between IndoorGML and CityGML. In this paper, issues and solutions for linkage of IndoorGML and CityGML are addressed.

• Journal of Korean Society for Geospatial Information Science
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• v.17 no.1
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• pp.157-166
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• 2009

There is a growing interest in ubiquitous-related research and applications. Among them, GPS-based LBS have been developed and used actively. Recently, with the increase of large size buildings and disastrous events, indoor spaces are getting attention and related research activities are being carried out. Core technologies regarding indoor applications may include 3D indoor data modeling and localization sensor techniques that can integrate with indoor data. However, these technologies have not been standardized and established enough to be applied to indoor implementation. Thus, in this paper, we propose a method to build a relatively simple 3D indoor data modeling technique that can be applied to indoor location based applications. The proposed model takes the form of 2D-based multi-layered structure and has capability for 2D and 3D visualization. We tested three prototype applications using the proposed model; CA(cellular automata)-based 3D evacuation simulation, network-based routing, and indoor moving objects tracking using a stereo camera.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2021.05a
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• pp.458-459
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• 2021

Recently, researches using deep learning technology based on Wi-Fi fingerprints have been conducted for accurate services in indoor location-based services. Among the deep learning models, an RNN model that can store information from the past can store continuous movements in indoor positioning, thereby reducing positioning errors. At this time, continuous sequential data is required as training data. However, since Wi-Fi fingerprint data is generally managed only with signals for a specific location, it is inappropriate to use it as training data for an RNN model. This paper proposes a path generation method through prediction of a moving path based on Wi-Fi fingerprint data extended to region data through clustering to generate sequential input data of the RNN model.