Defining a Model for Integrating Indoor and Outdoor Network Data to Support Seamless Navigation Applications

Spaces are continuous realms where human beings freely navigate, such as from indoor to outdoor and optionally to another indoor space. However, currently available data models to represent space for navigation do not entirely reflect this continuity of freedom and movement. Data conversion or compl...

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Bibliographic Details
Published inISPRS international journal of geo-information Vol. 10; no. 8; p. 565
Main Authors Claridades, Alexis Richard C., Lee, Jiyeong
Format Journal Article
LanguageEnglish
Published Basel MDPI AG 01.08.2021
Subjects
anchor node
Big Data
Cloud computing
Complications
Data
Data conversion
Data models
Datasets
Decision making
indoor and outdoor integration
Indoor environments
Internet of Things
Location based services
Navigation
OGC IndoorGML
Outdoors
seamless navigation
Smart cities
Spatial data
Urbanization
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Summary:Spaces are continuous realms where human beings freely navigate, such as from indoor to outdoor and optionally to another indoor space. However, currently available data models to represent space for navigation do not entirely reflect this continuity of freedom and movement. Data conversion or complications in implementation hinder current approaches to link indoor space with outdoor space due to the variety of present data models. Furthermore, this representation of indoor–outdoor connection becomes oversimplified during the integration process. Consequently, location-based applications based on these datasets are limited in conveying mobility within these spaces and aiding navigation activity. This paper defines a framework for integrating indoor and outdoor navigable space to enable seamless navigation. This model enables the connection between indoor and outdoor navigation networks. We describe the connections between these networks through spatial relationships, which can be generalized to represent various cases of indoor–outdoor transitional spaces. Using sample datasets, we demonstrate the framework’s potential to provide a seamless connection between indoor and outdoor space in a route analysis experiment.
ISSN:2220-9964
2220-9964
DOI:10.3390/ijgi10080565