Title
Indoor Multi-Dimensional Location GML and Its Application for Ubiquitous Indoor Location Services.
Abstract
The Open Geospatial Consortium (OGC) Geography Markup Language (GML) standard provides basic types and a framework for defining geo-informational data models such as CityGML and IndoorGML, which provide standard information models for 3D city modelling and lightweight indoor network navigation. Location information, which is the semantic engine that fuses big geo-information data, is however, discarded in these standards. The Chinese national standard of Indoor Multi-Dimensional Location GML (IndoorLocationGML) presented in this study can be used in ubiquitous indoor location intelligent applications for people and robots. IndoorLocationGML is intended as an indoor multi-dimensional location information model and exchange data format standard, mainly for indoor positioning and navigation. This paper introduces the standard's main features: (1) terminology; (2) indoor location information model using a Unified Modeling Language (UML) class diagram; (3) indoor location information markup language based on GML; and (4) use cases. A typical application of the standard is then discussed. This standard is applicable to the expression, storage, and distribution of indoor multi-dimensional location information, and to the seamless integration of indoor-outdoor location information. The reference and basis are therefore relevant to publishers, managers, users, and developers of indoor navigation and location-based services (LBS).
Year
DOI
Venue
2016
10.3390/ijgi5120220
ISPRS INTERNATIONAL JOURNAL OF GEO-INFORMATION
Keywords
Field
DocType
indoor location,location-based service,standard,navigation
Geospatial analysis,Data modeling,Computer science,Location-based service,Geography Markup Language,CityGML,Information model,Database,Markup language,Class diagram
Journal
Volume
Issue
ISSN
5
12
2220-9964
Citations 
PageRank 
References 
0
0.34
0
Authors
7
Name
Order
Citations
PageRank
Qing Zhu101.01
Yun Li201.01
Qing Xiong300.34
S. Zlatanova437750.93
Yulin Ding501.01
Yeting Zhang6378.36
Yan Zhou771.83