scholarly journals Development of an Omnidirectional-Image-Based Data Model through Extending the IndoorGML Concept to an Indoor Patrol Service

2017 ◽  
Vol 2017 ◽  
pp. 1-14 ◽  
Author(s):  
Hyo-jin Jung ◽  
Jiyeong Lee
Keyword(s):  
Data Model ◽  
Indoor Navigation ◽  
Location Based Services ◽  
Indoor Location ◽  
Indoor Space ◽  
Omnidirectional Image ◽  
Space Data ◽  
Omnidirectional Images ◽  
Indoor Spaces ◽  
Topological Data

Different indoor representation methods have been studied for their ability to provide indoor location-based services (LBS). Among them, omnidirectional imaging is one of the most typical and simple methods for representing an indoor space. However, a georeferenced omnidirectional image cannot be used for simple attribute searches, spatial queries, and spatial awareness analyses. To perform these functions, topological data are needed to define the features of and spatial relationships among spatial objects including indoor spaces as well as facilities like CCTV cameras considered in patrol service applications. Therefore, this study proposes an indoor space application data model for an indoor patrol service that can implement functions suited to linking indoor space data and service objects. In order to do this, the study presents a method for linking data between omnidirectional images representing indoor spaces and topological data on indoor spaces based on the concept of IndoorGML. Also, we conduct an experimental implementation of the integrated 3D indoor navigation model for patrol service using GIS data. Based on the results, we evaluate the benefits of using such a 3D data fusion method that integrates omnidirectional images with vector-based topological data models based on IndoorGML for providing indoor LBS in built environments.

scholarly journals DEVELOPING A DATA FUSION STRATEGY BETWEEN OMNIDIRECTIONAL IMAGE AND INDOORGML DATA

2019 ◽  
Vol XLII-4/W19 ◽  
pp. 117-124
Author(s):  
A. R. C. Claridades ◽  
D. Ahn ◽  
J. Lee
Keyword(s):  
Data Conversion ◽  
Position Information ◽  
Indoor Location ◽  
Indoor Space ◽  
3D Space ◽  
Experimental Implementation ◽  
Omnidirectional Image ◽  
Omnidirectional Images ◽  
Relationship Of ◽  
Topological Data

Abstract. As the interest in indoor spaces increases, there is a growing need for indoor spatial applications. As these spaces grow in complexity and size, research is being carried out towards effective and efficient representation. Omnidirectional images give a snapshot of interiors and give visually rich content, but only contain pixel data. For it to be used in providing indoor services, its limitations must be overcome. First, the images must be connected to each other to represent indoor space continuously based on spatial relationships that may be provided by topological data. Second, the objects and spaces that we see in these images must also be recognized. This paper presents a study on how to link omnidirectional images and an IndoorGML data without the need for data conversion, provision of reference data, or use of different data models in order to provide Indoor Location-Based Service (LBS). We introduce the use of the Spatial Extended Point (SEP) to characterize the relationship between the omnidirectional image and the topological data. Position information of the object is used to define a region of 3D space, to determine the inclusion relationship of an IndoorGML node. We conduct an experimental implementation of the integrated data in the form of a 3D Virtual Tour. The connection of the Omnidirectional images is demonstrated by a visualization of navigation through a hallway towards a room’s interior delivered to the user through a clicking action on the image.

scholarly journals Developing a Data Model of Indoor Points of Interest to Support Location-Based Services

2020 ◽  
Vol 2020 ◽  
pp. 1-16
Author(s):  
Alexis Richard C. Claridades ◽  
Jiyeong Lee
Keyword(s):  
Spatial Data ◽  
Data Model ◽  
Unified Modeling Language ◽  
Location Based Services ◽  
Accurate Information ◽  
Indoor Location ◽  
Unified Modeling ◽  
Points Of Interest ◽  
Sample Data ◽  
Indoor Spaces

Focus on indoor spatial applications has been rising with the growing interest in indoor spaces. Along with the widespread use of mobile devices and the internet, it has increased demands for indoor location-based services (LBS), demanding more efficient representation and management of indoor spatial data. Indoor points of interest (Indoor POI) data, representing both spaces and facilities located indoors, provide the infrastructure for these services. These datasets are vital in delivering timely and accurate information to users, such as in cases of managing indoor facilities. However, even though there are studies that explore its use across applications and efforts exerted towards the standardization of the data model, most POI development studies have focused on the outdoors and remain underdeveloped in the indoors. In this paper, we propose a spatial-temporal Indoor POI data model to provide direction for the establishment of indoor POI data and to address limitations in currently available data specifications. By exploring how different Indoor POIs are from its outdoor counterparts, particularly on extending its outdoor counterparts’ functions on searching, sharing, and labeling, we describe the data model and its components using the Unified Modeling Language (UML). We perform an SQL-based query experiment to demonstrate the potential use of the data model using sample data.

scholarly journals EXTRACTING TOPOLOGICAL RELATIONS BETWEEN INDOOR SPACES FROM POINT CLOUDS

2017 ◽  
Vol IV-2/W4 ◽  
pp. 401-406 ◽  
Author(s):  
H. Tran ◽  
K. Khoshelham ◽  
A. Kealy ◽  
L. Díaz-Vilariño
Keyword(s):  
Emergency Management ◽  
Principal Components ◽  
Point Clouds ◽  
3D Models ◽  
Indoor Navigation ◽  
Location Based Services ◽  
Indoor Environments ◽  
Topological Relations ◽  
Indoor Location ◽  
Indoor Spaces

3D models of indoor environments are essential for many application domains such as navigation guidance, emergency management and a range of indoor location-based services. The principal components defined in different BIM standards contain not only building elements, such as floors, walls and doors, but also navigable spaces and their topological relations, which are essential for path planning and navigation. We present an approach to automatically reconstruct topological relations between navigable spaces from point clouds. Three types of topological relations, namely containment, adjacency and connectivity of the spaces are modelled. The results of initial experiments demonstrate the potential of the method in supporting indoor navigation.

scholarly journals Integrating Image and Network-Based Topological Data through Spatial Data Fusion for Indoor Location-Based Services

2020 ◽  
Vol 2020 ◽  
pp. 1-12
Author(s):  
Dasol Ahn ◽  
Alexis Richard C. Claridades ◽  
Jiyeong Lee
Keyword(s):  
Data Fusion ◽  
Spatial Data ◽  
Urban Areas ◽  
Spatial Information ◽  
Indoor Navigation ◽  
Location Based Services ◽  
Data Conversion ◽  
Position Information ◽  
Indoor Space ◽  
Topological Data

Nowadays, the importance and utilization of spatial information are recognized. Particularly in urban areas, the demand for indoor spatial information draws attention and most commonly requires high-precision 3D data. However accurate, most methodologies present problems in construction cost and ease of updating. Images are accessible and are useful to express indoor space, but pixel data cannot be applied directly to provide indoor services. A network-based topological data gives information about the spatial relationships of the spaces depicted by the image, as well as enables recognition of these spaces and the objects contained within. In this paper, we present a data fusion methodology between image data and a network-based topological data, without the need for data conversion, use of a reference data, or a separate data model. Using the concept of a Spatial Extended Point (SEP), we implement this methodology to establish a correspondence between omnidirectional images and IndoorGML data to provide an indoor spatial service. The proposed algorithm used position information identified by a user in the image to define a 3D region to be used to distinguish correspondence with the IndoorGML and indoor POI data. We experiment with a corridor-type indoor space and construct an indoor navigation platform.

scholarly journals INDOORGML – A STANDARD FOR INDOOR SPATIAL MODELING

2016 ◽  
Vol XLI-B4 ◽  
pp. 701-704
Author(s):  
Ki-Joune Li
Keyword(s):  
Spatial Data ◽  
Geometric Model ◽  
Spatial Models ◽  
Cell Number ◽  
Indoor Navigation ◽  
Location Based Services ◽  
Indoor Space ◽  
Outdoor Spaces ◽  
Core Module ◽  
Outdoor Space

With recent progress of mobile devices and indoor positioning technologies, it becomes possible to provide location-based services in indoor space as well as outdoor space. It is in a seamless way between indoor and outdoor spaces or in an independent way only for indoor space. However, we cannot simply apply spatial models developed for outdoor space to indoor space due to their differences. For example, coordinate reference systems are employed to indicate a specific position in outdoor space, while the location in indoor space is rather specified by cell number such as room number. Unlike outdoor space, the distance between two points in indoor space is not determined by the length of the straight line but the constraints given by indoor components such as walls, stairs, and doors. For this reason, we need to establish a new framework for indoor space from fundamental theoretical basis, indoor spatial data models, and information systems to store, manage, and analyse indoor spatial data. In order to provide this framework, an international standard, called IndoorGML has been developed and published by OGC (Open Geospatial Consortium). This standard is based on a cellular notion of space, which considers an indoor space as a set of non-overlapping cells. It consists of two types of modules; core module and extension module. While core module consists of four basic conceptual and implementation modeling components (geometric model for cell, topology between cells, semantic model of cell, and multi-layered space model), extension modules may be defined on the top of the core module to support an application area. As the first version of the standard, we provide an extension for indoor navigation.

scholarly journals INDOOR SPACE ROUTING GRAPHS: VISIBILITY, ENCODING, ENCRYPTION AND ATTENUATION

2018 ◽  
Vol XLII-4 ◽  
pp. 579-585
Author(s):  
G. Sithole
Keyword(s):  
Path Planning ◽  
Indoor Environment ◽  
Indoor Navigation ◽  
Indoor Space ◽  
The Third ◽  
Future Paper ◽  
Spatial Geometry ◽  
Novel Method ◽  
Third Dimension ◽  
Indoor Spaces

<p><strong>Abstract.</strong> The conventional approach to path planning for indoor navigation is to infer routes from a subdivided floor map of the indoor space. The floor map describes the spatial geometry of the space. Contained in this floor map are logical units called subspaces. For the purpose of path planning the possible routes between the subspaces have to be modelled. Typical these models employing a graph structures, or skeletons, in which the interconnected subspaces (e.g., rooms, corridors, etc.) are represented as linked nodes, i.e. a graph.</p><p>This paper presents a novel method for creating generalised graphs of indoor spaces that doesn’t require the subdivision of indoor space. The method creates the generalised graph by gradually simplifying/in-setting the floor map until a graph is obtained, a process described here as chained deflation. The resulting generalised graph allows for more flexible and natural paths to be determined within the indoor environment. Importantly the method allows the indoor space to be encoded and encrypted and supplied to users in a way that emulates the use of physical keys in the real world. Another important novelty of the method is that the space described by the graph is adaptable. The space described by the graph can be deflated or inflated according to the needs of the path planning. Finally, the proposed method can be readily generalised to the third dimension.</p><p>The concept and logic of the method are explained. A full implementation of the method will be discussed in a future paper.</p>

scholarly journals INDOORGML – A STANDARD FOR INDOOR SPATIAL MODELING

2016 ◽  
Vol XLI-B4 ◽  
pp. 701-704 ◽  
Author(s):  
Ki-Joune Li
Keyword(s):  
Spatial Data ◽  
Geometric Model ◽  
Spatial Models ◽  
Cell Number ◽  
Indoor Navigation ◽  
Location Based Services ◽  
Indoor Space ◽  
Outdoor Spaces ◽  
Core Module ◽  
Outdoor Space

With recent progress of mobile devices and indoor positioning technologies, it becomes possible to provide location-based services in indoor space as well as outdoor space. It is in a seamless way between indoor and outdoor spaces or in an independent way only for indoor space. However, we cannot simply apply spatial models developed for outdoor space to indoor space due to their differences. For example, coordinate reference systems are employed to indicate a specific position in outdoor space, while the location in indoor space is rather specified by cell number such as room number. Unlike outdoor space, the distance between two points in indoor space is not determined by the length of the straight line but the constraints given by indoor components such as walls, stairs, and doors. For this reason, we need to establish a new framework for indoor space from fundamental theoretical basis, indoor spatial data models, and information systems to store, manage, and analyse indoor spatial data. In order to provide this framework, an international standard, called IndoorGML has been developed and published by OGC (Open Geospatial Consortium). This standard is based on a cellular notion of space, which considers an indoor space as a set of non-overlapping cells. It consists of two types of modules; core module and extension module. While core module consists of four basic conceptual and implementation modeling components (geometric model for cell, topology between cells, semantic model of cell, and multi-layered space model), extension modules may be defined on the top of the core module to support an application area. As the first version of the standard, we provide an extension for indoor navigation.

scholarly journals INDOOR SPACE LOCATION MODEL BASED ON LOCATION SERVICE

2017 ◽  
Vol XLII-4/W7 ◽  
pp. 49-53
Author(s):  
Y. Zhou ◽  
G. Zeng ◽  
Y. Huang ◽  
X. Yang
Keyword(s):  
Spatial Information ◽  
Indoor Navigation ◽  
Location Model ◽  
Location Information ◽  
Location Based Service ◽  
Location Services ◽  
Indoor Location ◽  
Indoor Space ◽  
Location Service ◽  
Space Model

Location is the basis for the realization of location services, the integrity of the location information and its way of representation in indoor space model directly restricts the quality of location services. The construction of the existing indoor space model is mostly for specific applications and lack of uniform representation of location information. Several geospatial standards have been developed to meet the requirement of the indoor spatial information system, among which CityGML LOD4 and IndoorGML are the most relevant ones for indoor spatial information. However, from the perspective of Location Based Service (LBS), the CityGML LOD4 is more inclined to visualize the indoor space. Although IndoorGML is mainly used for indoor space navigation and has description (such as geometry, topology, and semantics) benefiting for indoor LBS, this standard model lack explicit representation of indoor location information. In this paper, from the perspective of Location Based Service (LBS), based on the IndoorGML standard, an indoor space location model (ISLM) conforming to human cognition is proposed through integration of the geometric and topological and semantic features of the indoor spatial entity. This model has the explicit description of location information which the standard indoor space model of IndoorGML and CityGML LOD4 does not have, which can lay the theoretical foundation for indoor location service such as indoor navigation, indoor routing and location query.

scholarly journals A Simplified CityGML-Based 3D Indoor Space Model for Indoor Applications

2020 ◽  
Vol 10 (20) ◽  
pp. 7218
Author(s):  
Qun Sun ◽  
Xiaoguang Zhou ◽  
Dongyang Hou
Keyword(s):  
Semantic Information ◽  
Indoor Navigation ◽  
Geometric Information ◽  
Indoor Space ◽  
Emergency Rescue ◽  
Interior Spaces ◽  
Topological Relationships ◽  
Building Components ◽  
Relationship Of ◽  
Indoor Spaces

With the continuous development of indoor positioning technology, various indoor applications, such as indoor navigation and emergency rescue, have gradually received widespread attention. Indoor navigation and emergency rescue require access to a variety of indoor space information, such as accurate geometric information, rich semantic information and indoor spatial adjacency information; hence, a suitable 3D indoor model is needed. However, the available models, such as BIM and CityGML, mainly represent geometric and semantic information of indoor spaces, and rarely describe the topological adjacency relationship of interior spaces. To address the requirements of indoor navigation and emergency rescue, a simplified 3D indoor model is proposed in this research. The building components and indoor functional spaces of buildings are described in a simplified way. The geometric and semantic information are described based on CityGML, and the topological relationships of indoor adjacent spaces are represented by CityGML XLinks. While describing the indoor level of detail (LOD) of buildings in detail, the model simplifies building components and indoor spaces, which can preserve the characteristics of indoor spaces to the maximum extent and serve as a basis for indoor applications.

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