scholarly journals Data Model for IndoorGML Extension to Support Indoor Navigation of People with Mobility Disabilities

2020 ◽  
Vol 9 (2) ◽  
pp. 66 ◽  
Author(s):  
Seula Park ◽  
Kiyun Yu ◽  
Jiyoung Kim
Keyword(s):  
Data Model ◽  
Indoor Environment ◽  
Spatial Information ◽  
People With Disabilities ◽  
Indoor Navigation ◽  
Shopping Mall ◽  
Data Generation ◽  
Proposed Model ◽  
Model Features ◽  
Indoor Spaces

The increasing complexity of modern buildings has challenged the mobility of people with disabilities (PWD) in the indoor environment. To help overcome this problem, this paper proposes a data model that can be easily applied to indoor spatial information services for people with disabilities. In the proposed model, features are defined based on relevant regulations that stipulate significant mobility factors for people with disabilities. To validate the model’s capability to describe the indoor spaces in terms that are relevant to people with mobility disabilities, the model was used to generate data in a path planning application, considering two different cases in a shopping mall. The application confirmed that routes for people with mobility disabilities are significantly different from those of ordinary pedestrians, in a way that reflects features and attributes defined in the proposed data model. The latter can be inserted as an IndoorGML extension, and is thus expected to facilitate relevant data generation for the design of various services for people with disabilities.

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 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>

Android-Based Visual Tag Detection for Visually Impaired Users

2014 ◽  
Vol 5 (1) ◽  
pp. 63-80 ◽  
Author(s):  
Hao Dong ◽  
Jieqi Kang ◽  
James Schafer ◽  
Aura Ganz
Keyword(s):  
User Interface ◽  
Visually Impaired ◽  
Indoor Environment ◽  
Detection Algorithm ◽  
Indoor Navigation ◽  
Lighting Conditions ◽  
Sampling Probe ◽  
Indoor Spaces

In this paper the authors introduce PERCEPT-V indoor navigation for the blind system. PERCEPT-V enhances PERCEPT system by enabling visually impaired users to navigate in open indoor spaces that differ in size and lighting conditions. The authors deploy visual tags in the environment at specific landmarks and introduce a visual tag detection algorithm using a sampling probe and cascading approach. The authors provide guidelines for the visual tag size, which is a function of various environmental, and usage scenarios, which differ in lighting, dimensions of the indoor environment and angle of usage. The authors also developed a Smartphone based user interface for the visually impaired users that uses Android accessibility features.

Transport and Mobility

2014 ◽  
pp. 112-132
Keyword(s):  
Assistive Technology ◽  
People With Disabilities ◽  
Indoor Navigation ◽  
Shopping Mall ◽  
Indoor Environments ◽  
Persons With Disabilities ◽  
Large Group ◽  
Smart Wheelchairs ◽  
New Ideas

One of the most common needs for persons with disabilities and elderly is the need for transportation and mobility. It is a need that penetrates many aspects of a person's life. From travelling to another city or country, commuting to work, or travelling within your city and being able to navigate in indoor environments such as a shopping mall, a museum, or even your own home, transportation and mobility are needed. This chapter focuses and discusses issues, technologies, and applications for enhancing the accessibility in transportation and mobility together with new ideas such as the idea and trend of telepresence that could be helpful for a large group of people apart from people with disabilities. Technologies and applications discussed include driverless transportation, indoor navigation, smart assistive technology devices for mobility and navigation such as smart wheelchairs, exoskeletons, smart white canes, etc.

scholarly journals Fast Transfer Navigation for Autonomous Robots

2021 ◽  
Vol 2021 ◽  
pp. 1-7
Author(s):  
Chen Wang ◽  
Xudong Li ◽  
Xiaolin Tao ◽  
Kai Ling ◽  
Quhui Liu ◽  
...  
Keyword(s):  
Reinforcement Learning ◽  
Indoor Environment ◽  
Autonomous Robots ◽  
Indoor Navigation ◽  
Robotic Navigation ◽  
Navigation Algorithm ◽  
Proposed Model ◽  
Interior Environment

Navigation technology enables indoor robots to arrive at their destinations safely. Generally, the varieties of the interior environment contribute to the difficulty of robotic navigation and hurt their performance. This paper proposes a transfer navigation algorithm and improves its generalization by leveraging deep reinforcement learning and a self-attention module. To simulate the unfurnished indoor environment, we build the virtual indoor navigation (VIN) environment to compare our model and its competitors. In the VIN environment, our method outperforms other algorithms by adapting to an unseen indoor environment. The code of the proposed model and the virtual indoor navigation environment will be released.

scholarly journals Android-Based Visual Tag Detection for Visually Impaired Users

Ophthalmology ◽  
2018 ◽  
pp. 317-334
Author(s):  
Hao Dong ◽  
Jieqi Kang ◽  
James Schafer ◽  
Aura Ganz
Keyword(s):  
User Interface ◽  
Visually Impaired ◽  
Indoor Environment ◽  
Detection Algorithm ◽  
Indoor Navigation ◽  
Lighting Conditions ◽  
Sampling Probe ◽  
Indoor Spaces

In this paper the authors introduce PERCEPT-V indoor navigation for the blind system. PERCEPT-V enhances PERCEPT system by enabling visually impaired users to navigate in open indoor spaces that differ in size and lighting conditions. The authors deploy visual tags in the environment at specific landmarks and introduce a visual tag detection algorithm using a sampling probe and cascading approach. The authors provide guidelines for the visual tag size, which is a function of various environmental, and usage scenarios, which differ in lighting, dimensions of the indoor environment and angle of usage. The authors also developed a Smartphone based user interface for the visually impaired users that uses Android accessibility features.

scholarly journals AUTOMATIC EXTRACTION OF IndoorGML CORE MODEL FROM OpenStreetMap

2015 ◽  
Vol XL-1-W5 ◽  
pp. 459-462 ◽  
Author(s):  
S. S. Mirvahabi ◽  
R. A. Abbaspour
Keyword(s):  
Spatial Data ◽  
Data Model ◽  
Spatial Information ◽  
Human Life ◽  
Data File ◽  
Automatic Generation ◽  
New Approach ◽  
Indoor Space ◽  
Navigation Data ◽  
Indoor Spaces

Navigation has become an essential component of human life and a necessary component in many fields. Because of the increasing size and complexity of buildings, a unified data model for navigation analysis and exchange of information. IndoorGML describes an appropriate data model and XML schema of indoor spatial information that focuses on modelling indoor spaces. Collecting spatial data by professional and commercial providers often need to spend high cost and time, which is the major reason that VGI emerged. One of the most popular VGI projects is OpenStreetMap (OSM). In this paper, a new approach is proposed for the automatic generation of IndoorGML data core file from OSM data file. The output of this approach is the file of core data model that can be used alongside the navigation data model for navigation application of indoor space.

Generation of a Data Model for Indoor Navigation Based on Volunteered Geospatial Information (VGI)

2017 ◽  
pp. 243-270
Author(s):  
Rahim Ali Abbaspour ◽  
Simin S. Mirvahabi
Keyword(s):  
Data Model ◽  
Indoor Environment ◽  
Human Life ◽  
Indoor Navigation ◽  
Geospatial Data ◽  
Indoor Environments ◽  
Geospatial Information ◽  
Navigation Data ◽  
Suitable Solution

Navigation has been an inseparable part of human life especially in modern days, when the structures of cities and their buildings' indoor environments have been more complex. More than 80% of routine life of a typical citizen is spent in indoor and the indoor environment are getting highly complex due to the increase in sizes of the buildings. An important factor to a successful indoor navigation is the precise suitable map for the inside of the buildings. Collection and generation of indoor geospatial data is very time consuming and costly for a building. Using the concept of volunteered geospatial information might be a suitable solution to deal with this problem. This chapter addresses the extraction of a data model for indoor navigation from VGI. An efficient methodology is proposed and evaluated to extract the navigation data model from OpenStreetMap automatically to use in indoor navigation applications.

scholarly journals Content Dependent Representation Selection Model for Systems Based on MPEG DASH

Electronics ◽  
2021 ◽  
Vol 10 (15) ◽  
pp. 1843
Author(s):  
Jelena Vlaović ◽  
Snježana Rimac-Drlje ◽  
Drago Žagar
Keyword(s):  
Mathematical Model ◽  
Spatial Information ◽  
Relevant Literature ◽  
Video Quality ◽  
Similarity Index ◽  
Video Encoding ◽  
Adaptation Algorithm ◽  
Subjective Testing ◽  
Proposed Model ◽  
The Mathematical Model

A standard called MPEG Dynamic Adaptive Streaming over HTTP (MPEG DASH) ensures the interoperability between different streaming services and the highest possible video quality in changing network conditions. The solutions described in the available literature that focus on video segmentation are mostly proprietary, use a high amount of computational power, lack the methodology, model notation, information needed for reproduction, or do not consider the spatial and temporal activity of video sequences. This paper presents a new model for selecting optimal parameters and number of representations for video encoding and segmentation, based on a measure of the spatial and temporal activity of the video content. The model was developed for the H.264 encoder, using Structural Similarity Index Measure (SSIM) objective metrics as well as Spatial Information (SI) and Temporal Information (TI) as measures of video spatial and temporal activity. The methodology that we used to develop the mathematical model is also presented in detail so that it can be applied to adapt the mathematical model to another type of an encoder or a set of encoding parameters. The efficiency of the segmentation made by the proposed model was tested using the Basic Adaptation algorithm (BAA) and Segment Aware Rate Adaptation (SARA) algorithm as well as two different network scenarios. In comparison to the segmentation available in the relevant literature, the segmentation based on the proposed model obtains better SSIM values in 92% of cases and subjective testing showed that it achieves better results in 83.3% of cases.

Sign in / Sign up

Export Citation Format

Share Document