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 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.

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 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 Space Subdivision of Indoor Mobile Laser Scanning Data Based on the Scanner Trajectory

2018 ◽  
Vol 10 (11) ◽  
pp. 1815 ◽  
Author(s):  
Ahmed Elseicy ◽  
Shayan Nikoohemat ◽  
Michael Peter ◽  
Sander Oude Elberink
Keyword(s):  
Real World ◽  
Point Cloud ◽  
Laser Scanning ◽  
Semantic Information ◽  
State Of The Art ◽  
Laser Scanner ◽  
Indoor Space ◽  
Laser Scanners ◽  
Real World Datasets ◽  
Indoor Spaces

State-of-the-art indoor mobile laser scanners are now lightweight and portable enough to be carried by humans. They allow the user to map challenging environments such as multi-story buildings and staircases while continuously walking through the building. The trajectory of the laser scanner is usually discarded in the analysis, although it gives insight about indoor spaces and the topological relations between them. In this research, the trajectory is used in conjunction with the point cloud to subdivide the indoor space into stories, staircases, doorways, and rooms. Analyzing the scanner trajectory as a standalone dataset is used to identify the staircases and to separate the stories. Also, the doors that are traversed by the operator during the scanning are identified by processing only the interesting spots of the point cloud with the help of the trajectory. Semantic information like different space labels is assigned to the trajectory based on the detected doors. Finally, the point cloud is semantically enriched by transferring the labels from the annotated trajectory to the full point cloud. Four real-world datasets with a total of seven stories are used to evaluate the proposed methods. The evaluation items are the total number of correctly detected rooms, doors, and staircases.

scholarly journals Automatic Reconstruction of Multi-Level Indoor Spaces from Point Cloud and Trajectory

Sensors ◽  
2021 ◽  
Vol 21 (10) ◽  
pp. 3493
Author(s):  
Gahyeon Lim ◽  
Nakju Doh
Keyword(s):  
Point Cloud ◽  
Dimensional Space ◽  
Three Dimensional ◽  
Reconstruction Method ◽  
Complex Environments ◽  
Indoor Space ◽  
Multi Level ◽  
Level Building ◽  
Indoor Spaces ◽  
Data Term

Remarkable progress in the development of modeling methods for indoor spaces has been made in recent years with a focus on the reconstruction of complex environments, such as multi-room and multi-level buildings. Existing methods represent indoor structure models as a combination of several sub-spaces, which are constructed by room segmentation or horizontal slicing approach that divide the multi-room or multi-level building environments into several segments. In this study, we propose an automatic reconstruction method of multi-level indoor spaces with unique models, including inter-room and inter-floor connections from point cloud and trajectory. We construct structural points from registered point cloud and extract piece-wise planar segments from the structural points. Then, a three-dimensional space decomposition is conducted and water-tight meshes are generated with energy minimization using graph cut algorithm. The data term of the energy function is expressed as a difference in visibility between each decomposed space and trajectory. The proposed method allows modeling of indoor spaces in complex environments, such as multi-room, room-less, and multi-level buildings. The performance of the proposed approach is evaluated for seven indoor space datasets.

scholarly journals TWO NEW PEDESTRIAN NAVIGATION PATH OPTIONS BASED ON SEMI-INDOOR SPACE

2020 ◽  
Vol VI-4/W1-2020 ◽  
pp. 175-182
Author(s):  
J. Yan ◽  
S. Zlatanova ◽  
A. A. Diakite
Keyword(s):  
Path Selection ◽  
Selection Strategy ◽  
Navigation Systems ◽  
Indoor Space ◽  
Pedestrian Navigation ◽  
Navigation Path ◽  
Shortest Distance ◽  
Making Choices ◽  
Navigation Experience ◽  
Indoor Spaces

Abstract. Navigation is very critical for our daily life, especially when we have to go through the unfamiliar areas where the spaces are very complex, such as completely bounded (indoor), partially bounded (semi-indoor and/or semi-outdoor), entirely open (outdoor), or combined. Current navigation systems commonly offer the shortest distance/time path, but it is not always appropriate for some situations. For instance, on a rainy day, a path with as many places that are covered by roofs/shelters is more attractive. However, current navigation systems cannot provide such kinds of navigation paths, which can be explained by that they lack information about such roofed/sheltered-covered spaces. This paper proposes two roofed/sheltered navigation path options by employing semi-indoor spaces in the navigation map: (i) the Most-Top-Covered path (MTC-path) and (ii) path to the Nearest sI-space from departure (NSI-path). A path selection strategy is introduced to help pedestrians in making choices between the two new path options and the traditional shortest path. We demonstrate and validate the research with path planning on two navigation cases. The results show the two path options and the path selection strategy bring in new navigation experience for humans.

scholarly journals Application of thermal comfort assessment models to indoor areas near glazed walls – experimental evaluation

2021 ◽  
Vol 20 (1) ◽  
pp. 106-127
Author(s):  
António Manuel Figueiredo Freitas Oliveira ◽  
◽  
Helena Corvacho ◽  
Keyword(s):  
Solar Radiation ◽  
Thermal Comfort ◽  
Thermal Environment ◽  
National Laboratory ◽  
Environmental Parameters ◽  
Outdoor Environment ◽  
Assessment Model ◽  
Indoor Space ◽  
The Impact ◽  
Indoor Spaces

In this paper, some of the results of an experimental study are presented. Its purpose was to better understand the impact of glazing on thermal comfort of users of indoor spaces (living and working), especially in the areas near glazed walls. Glazed elements, such as windows and glazed doors, allow visual access to the outdoor environment and the entrance of natural light and solar heat gains but they are often the cause of unwanted heat losses and gains and are disturbing elements in obtaining thermal comfort, both in global terms and in what concerns local discomfort due to radiant asymmetries and/or air draughts. Furthermore, solar radiation directly affecting users in the vicinity of glazing can also cause discomfort. These disturbances are recognized by users, both on cold winter days and on hot summer days. To assess thermal comfort or thermal neutrality of a person in a particular indoor space, it is important to know their location within that space. Thus, in order to adequately assess thermal comfort in the areas near the glazing, the indoor thermal environment must be characterized for this specific location. In this study, two indoor spaces (a classroom and an office-room) of a school building were monitored at different periods of the year. The measurements of the environmental parameters were performed both in the center of the rooms and in the areas near the glazing. Five models of thermal comfort assessment were then applied to the results, in order to compare the comfort conditions between the two studied locations and to evaluate the applicability of these models to the areas close to glazed walls. It was observed there was clearly a greater variability of comfort conditions in the vicinity of the glazed walls when compared to the center of the rooms. The application of thermal comfort assessment models to the two studied rooms was able to reveal the differences between the two compared locations within each space. It was also possible to show the effect of incoming solar radiation and the influence of the geometry of the spaces and of the ratio between glazed area and floor area by comparing the results for both spaces. The assessment model proposed by LNEC (Portuguese National Laboratory of Civil Engineering) proved to be the most adapted to Portuguese users’ habits.

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 The Doubling of the Degrees of Freedom in Quantum Dissipative Systems, and the Semantic Information Notion and Measure in Biosemiotics

Proceedings ◽  
2020 ◽  
Vol 47 (1) ◽  
pp. 60
Author(s):  
Gianfranco Basti ◽  
Antonio Capolupo ◽  
GiuseppeVitiello
Keyword(s):  
Degrees Of Freedom ◽  
Semantic Information ◽  
Quantum Dissipative Systems ◽  
Dissipative Systems ◽  
Recent History ◽  
History Of

In the recent history of the effort for defining a suitable. [...]

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