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)@en

Intelligent navigation and facility management in complex indoor environments are issues at the forefront of geospatial information science. Indoor spaces with fine geometric and semantic descriptions provide a solid foundation for various indoor applications, but it is difficult to comprehensively extract free multi-floor indoor spaces from complex three-dimensional building models, such as those described using CityGML LoD4, with existing methods for the subdivision or extraction of indoor spaces based on vector topology processing. Therefore, this paper elaborates a new voxelbased approach for extracting free multi-floor indoor spaces from 3D building models. It transforms the complicated vector processing tasks into a simple raster process that consists of three steps: voxelization with semantic enhancement, voxel classification, and boundary extraction. Experiments illustrate that the proposed method can automatically and correctly extract free multi-floor indoor spaces, especially two typical kinds of open indoor spaces, namely, lobbies and staircases.@en

In this study, an electro-optical simulation method is developed to predict the light intensity distribution and luminous flux of an in-house fabricated GaN based blue LED chip. The entire modeling process links an electrical simulation with ANSYS and optical simulation with LightTools, by assuming a proportional relation between the distributed current density and light emission energy on the multiple quantum well (MQW) layer. Experimental results show that the proposed simulation method can give a good prediction on the light intensity distribution for a semi-packaged GaN based blue LED chip. Further analysis on the simulation results reveals that an increase of at most 8% of the luminous flux can be achieved when the current density is controlled to evenly distribute on the MQW layer whereas the chip structure and electro pattern remains the same.@en