scholarly journals A SEMANTIC MODEL TO DEFINE INDOOR SPACE IN CONTEXT OF EMERGENCY EVACUATION

2016 ◽  
Vol XLI-B4 ◽  
pp. 313-318
Author(s):  
Nishith Maheshwari ◽  
K. S. Rajan
Keyword(s):  
Data Model ◽  
Semantic Information ◽  
Emergency Evacuation ◽  
Facility Management ◽  
Semantic Model ◽  
Real World Data ◽  
Geometric Information ◽  
Indoor Space ◽  
Syntactic Features ◽  
And Function

There have been various ways in which the indoor space of a building has been defined. In most of the cases the models have specific purpose on which they focus such as facility management, visualisation or navigation. The focus of our work is to define semantics of a model which can incorporate different aspects of the space within a building without losing any information provided by the data model. In this paper we have suggested a model which defines indoor space in terms of semantic and syntactic features. Each feature belongs to a particular class and based on the class, has a set of properties associated with it. The purpose is to capture properties like geometry, topology and semantic information like name, function and capacity of the space from a real world data model. The features which define the space are determined using the geometric information and the classes are assigned based on the relationships like connectivity, openings and function of the space. The ontology of the classes of the feature set defined will be discussed in the paper.

scholarly journals A SEMANTIC MODEL TO DEFINE INDOOR SPACE IN CONTEXT OF EMERGENCY EVACUATION

2016 ◽  
Vol XLI-B4 ◽  
pp. 313-318 ◽  
Author(s):  
Nishith Maheshwari ◽  
K. S. Rajan
Keyword(s):  
Data Model ◽  
Semantic Information ◽  
Emergency Evacuation ◽  
Facility Management ◽  
Semantic Model ◽  
Real World Data ◽  
Geometric Information ◽  
Indoor Space ◽  
Syntactic Features ◽  
And Function

There have been various ways in which the indoor space of a building has been defined. In most of the cases the models have specific purpose on which they focus such as facility management, visualisation or navigation. The focus of our work is to define semantics of a model which can incorporate different aspects of the space within a building without losing any information provided by the data model. In this paper we have suggested a model which defines indoor space in terms of semantic and syntactic features. Each feature belongs to a particular class and based on the class, has a set of properties associated with it. The purpose is to capture properties like geometry, topology and semantic information like name, function and capacity of the space from a real world data model. The features which define the space are determined using the geometric information and the classes are assigned based on the relationships like connectivity, openings and function of the space. The ontology of the classes of the feature set defined will be discussed in the paper.

scholarly journals Incorporating Topological Representation in 3D City Models

2019 ◽  
Vol 8 (8) ◽  
pp. 347 ◽  
Author(s):  
Stelios Vitalis ◽  
Ken Ohori ◽  
Jantien Stoter
Keyword(s):  
Data Structure ◽  
Data Model ◽  
Semantic Information ◽  
Semantic Representation ◽  
Geometric Analysis ◽  
Computationally Efficient ◽  
Real World Data ◽  
3D City Models ◽  
Map Data ◽  
City Models

3D city models are being extensively used in applications such as evacuation scenarios and energy consumption estimation. The main standard for 3D city models is the CityGML data model which can be encoded through the CityJSON data format. CityGML and CityJSON use polygonal modelling in order to represent geometries. True topological data structures have proven to be more computationally efficient for geometric analysis compared to polygonal modelling. In a previous study, we have introduced a method to topologically reconstruct CityGML models while maintaining the semantic information of the dataset, based solely on the combinatorial map (C-Map) data structure. As a result of the limitations of C-Map’s semantic representation mechanism, the resulting datasets could suffer either from semantic information loss or the redundant repetition of them. In this article, we propose a solution for a more efficient representation of geometry, topology and semantics by incorporating the C-Map data structure into the CityGML data model and implementing a CityJSON extension to encode the C-Map data. In addition, we provide an algorithm for the topological reconstruction of CityJSON datasets to append them according to this extension. Finally, we apply our methodology to three open datasets in order to validate our approach when applied to real-world data. Our results show that the proposed CityJSON extension can represent all geometric information of a city model in a lossless way, providing additional topological information for the objects of the model.

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.

scholarly journals Development of an Indoor Space Semantic Model and Its Implementation as an IndoorGML Extension

2019 ◽  
Vol 8 (8) ◽  
pp. 333 ◽  
Author(s):  
Nishith Maheshwari ◽  
Srishti Srivastava ◽  
Krishnan Sundara Rajan
Keyword(s):  
Semantic Information ◽  
Classification Model ◽  
Semantic Model ◽  
Data Format ◽  
Building Evacuation ◽  
Indoor Space ◽  
Physical Representation ◽  
History Of ◽  
Space Semantic ◽  
Indoor Spaces

Geospatial data capture and handling of indoor spaces is increasing over the years and has had a varied history of data sources ranging from architectural and building drawings to indoor data acquisition approaches. While these have been more data format and information driven primarily for the physical representation of spaces, it is important to note that many applications look for the semantic information to be made available. This paper proposes a space classification model leading to an ontology for indoor spaces that accounts for both the semantic and geometric characteristics of the spaces. Further, a Space semantic model is defined, based on this ontology, which can then be used appropriately in multiple applications. To demonstrate the utility of the model, we also present an extension to the IndoorGML data standard with a set of proposed classes that can help capture both the syntactic and semantic components of the model. It is expected that these proposed classes can be appropriately harnessed for use in diverse applications ranging from indoor data visualization to more user customised building evacuation path planning with a semantic overtone.

scholarly journals Incorporating Topological Representation in 3D City Models

2019 ◽  
Author(s):  
Stelios Vitalis ◽  
Ken Arroyo Ohori ◽  
Jantien Stoter
Keyword(s):  
Data Structure ◽  
Data Model ◽  
Semantic Information ◽  
Semantic Representation ◽  
Geometric Analysis ◽  
Computationally Efficient ◽  
Real World Data ◽  
3D City Models ◽  
Map Data ◽  
City Models

3D city models are being extensively used in applications such as evacuation scenarios and energy consumption estimation. The main standard for 3D city models is the CityGML data model which can be encoded through the CityJSON data format. CityGML and CityJSON use polygonal modelling in order to represent geometries. True topological data structures have proven to be more computationally efficient for geometric analysis compared to polygonal modelling. In a previous study, we have introduced a method to topologically reconstruct CityGML models while maintaining the semantic information of the dataset, based solely on the combinatorial map (C-Map) data structure. As a result of the limitations of C-Map's semantic representation mechanism, the resulting datasets could suffer either from semantic information loss or the redundant repetition of them. In this article, we propose a solution for a more efficient representation of both geometry, topology and semantics by incorporating the C-Map data structure in the CityGML data model and implementing a CityJSON extension to encode the C-Map data. In addition, we provide an algorithm for the topological reconstruction of CityJSON datasets to append them according to this extension. Finally, we apply our methodology to three open datasets in order to validate our approach when applied to real-world data. Our results show that the proposed CityJSON extension can represent all geometric information of a city model in a lossless way, providing additional topological information for the objects of the model.

scholarly journals A New Approach to Measuring the Similarity of Indoor Semantic Trajectories

2021 ◽  
Vol 10 (2) ◽  
pp. 90
Author(s):  
Jin Zhu ◽  
Dayu Cheng ◽  
Weiwei Zhang ◽  
Ci Song ◽  
Jie Chen ◽  
...  
Keyword(s):  
Similarity Measure ◽  
Semantic Information ◽  
Edit Distance ◽  
Similarity Measures ◽  
Indoor Positioning ◽  
Synthetic Dataset ◽  
Shopping Mall ◽  
Indoor Space ◽  
Trajectory Similarity ◽  
Indoor Spaces

People spend more than 80% of their time in indoor spaces, such as shopping malls and office buildings. Indoor trajectories collected by indoor positioning devices, such as WiFi and Bluetooth devices, can reflect human movement behaviors in indoor spaces. Insightful indoor movement patterns can be discovered from indoor trajectories using various clustering methods. These methods are based on a measure that reflects the degree of similarity between indoor trajectories. Researchers have proposed many trajectory similarity measures. However, existing trajectory similarity measures ignore the indoor movement constraints imposed by the indoor space and the characteristics of indoor positioning sensors, which leads to an inaccurate measure of indoor trajectory similarity. Additionally, most of these works focus on the spatial and temporal dimensions of trajectories and pay less attention to indoor semantic information. Integrating indoor semantic information such as the indoor point of interest into the indoor trajectory similarity measurement is beneficial to discovering pedestrians having similar intentions. In this paper, we propose an accurate and reasonable indoor trajectory similarity measure called the indoor semantic trajectory similarity measure (ISTSM), which considers the features of indoor trajectories and indoor semantic information simultaneously. The ISTSM is modified from the edit distance that is a measure of the distance between string sequences. The key component of the ISTSM is an indoor navigation graph that is transformed from an indoor floor plan representing the indoor space for computing accurate indoor walking distances. The indoor walking distances and indoor semantic information are fused into the edit distance seamlessly. The ISTSM is evaluated using a synthetic dataset and real dataset for a shopping mall. The experiment with the synthetic dataset reveals that the ISTSM is more accurate and reasonable than three other popular trajectory similarities, namely the longest common subsequence (LCSS), edit distance on real sequence (EDR), and the multidimensional similarity measure (MSM). The case study of a shopping mall shows that the ISTSM effectively reveals customer movement patterns of indoor customers.

APPROACH TO THE EVALUATION OF FILLING BY PEOPLE OF MOBILE MEANS AT EMERGENCY EVACUATION FROM BUILDINGS

2021 ◽  
Vol 3 ◽  
pp. 78-90
Author(s):  
Vladimir Komyak ◽  
◽  
Valentina Komyak ◽  
Kazim Kazimov ◽  
Alexander Pankratov ◽  
...  
Keyword(s):  
Configuration Space ◽  
Spatial Configuration ◽  
Quality Criterion ◽  
Optimization Methods ◽  
Emergency Evacuation ◽  
Shape Parameters ◽  
Complex Objects ◽  
Geometric Information ◽  
Geometric Objects ◽  
Spatial Shape

The tasks of geometric design (of arrangement, cutting, coverage, partitioning) consist in optimization display of geometric information about objects in accordance with a given quality criterion and limitations. Geometric information about a geometric object consists of three components: spatial shape, metric shape parameters, placement parameters, and which, as a rule, is involves in the synthesis of complex systems. The configuration space of geometric objects is based on the formalization of the concept of geometric information. The mapping of objects into their configuration space according to a given set of constraints defines the spatial configuration of geometric objects. The article introduces the concept of a spatial configuration of placement, with the help of which a new model of placement of complex objects is constructed, representing the union of three loosely coupled ellipses, of which one (main) allows continuous translations and rotations, and two of auxiliary ellipses can rotate within acceptable limits (with respect to the angle of rotation of main ellipse) and relative to the points of their “gluing”. As a result of solving the optimization problem, not only the arrangement configuration of such objects is synthesized, but also the spatial form of each of them. Computer modeling of the optimization of the placement of the complex objects considered in the work was carried out and the effectiveness of the proposed approach was shown by comparing the location configurations for objects with a changing spatial shape and with constant shape parameters. Consideration of the parameters of the placement of objects, as well as additional parameters that allow us to synthesize new spatial forms of objects, as independent variables will allow us to offer new mathematical models and optimization methods for the synthesis of spatial configurations. A further direction can also be considered the development of new approaches to modeling the movement of flows of people, robots, to get upper bounds for filling areas with objects. All this increases the range of tasks to be solved according to their functional capabilities and can be used, for example, when dividing the compartments of vehicles for transporting goods and storing them, in pattern recognition systems, in robotics, etc.

Integration of Heterogeneous Product Information for Industrial Cluster

2012 ◽  
Vol 201-202 ◽  
pp. 898-901
Author(s):  
Jun He Yu ◽  
Hong Fei Zhan
Keyword(s):  
Data Model ◽  
Product Information ◽  
Industrial Cluster ◽  
Structure And Properties ◽  
Integration Framework ◽  
Product Data ◽  
Product Data Model ◽  
Model Class ◽  
And Function ◽  
Classification Structure

This paper analyzed the heterogeneous product information for industrial cluster. It plays an important role in collaboration of enterprise and product information inquires in industrial cluster. The paper presented globe product data model based on PLIB standard. The globe classification structure and properties definition were given as the globe ontology for industrial cluster. The product class was expressed by general model class and function model class. The class is defined with the properties. The class and properties for injection machine were described as an example. According to the globe product data model, the integration framework can make the integration of heterogeneous product information and provide the unique inquire interface for the end customer. The integration framework was presented and analyzed.

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.

Dealing with Semantic Heterogeneity of Geographic Concepts: A Geometric Algebra-Based Encoding Method

2020 ◽  
Author(s):  
Fan Wu ◽  
Hong Gao ◽  
Zhaoyuan Yu
Keyword(s):  
Geometric Algebra ◽  
Semantic Information ◽  
Semantic Model ◽  
Semantic Heterogeneity ◽  
Semantic Association ◽  
Multiple Contexts ◽  
Great Heterogeneity ◽  
Core Concepts ◽  
Encoding Method

<p>A conceptual consensus, as well as a unified representation, on a certain geographic concept across multiple contexts, can be of great significance to the communication, retrieval, combination, and reuse of geographic information and knowledge. However, geographic concept is a rich synthesis of semantics, semiotics, quality (e.g., vagueness or approximation). The generation, representation calculation and application of a certain geographic concept, consequently, can be of great heterogeneity, especially considering different interests, domains, language, etc. In light of these semantic heterogeneity problems, to code core concepts uniquely can be a lighter alternative to tradition ontology-based method, the reason for which is numeric codes can be a symbolism of consensus on concept across domains and even languages. Consequently, this paper proposed a unified semantic model as well as an encoding framework for representation, reasoning, and computation of geographic concept based on geometric algebra (GA). In this method, a geographic concept can be represented as a collection of semantic elements, which can be further encoded based on its hierarchy structure, and all the semantic information of the concept can be preserved across the encoding process. On the basis of the encoding result, semantic information can be reasoned backward by some well-defined operators, semantic similarity can also be computed for information inference as well as semantic association retrieval. In the case study, the implementation of the proposed framework shows that this GA-based semantic encoding model of can be a promising method to the unified expression, reasoning, and calculation of geographic concepts, which, reasonably, can be further regarded as a prospect lighter alternative of the solution to semantic heterogeneity.</p>

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