Development of CityGML Application Domain Extension for Indoor Routing and Positioning
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CityGML is an open data model for storage and exchange of 3D city models. It is categorised into thirteen thematic classes, i.e., buildings, tunnels, bridges, etc., lacking the other themes such as indoor routing and positioning. With the amplified use of indoor routing and positioning, the need for prerequisite notion of detailed semantic, as well as geometric information of the 3D building data has grown. We intend to extend the CityGML schema to add attributes of indoor features using the facility of Application Domain Extension (ADE) provided by the OGC CityGML 2.0. In this study, we aim to showcase the formation of Indoor Routing and Positioning ADE along with the process concerning its development, such as the 3D model design, network dataset creation, routing, positioning and Unified Modeling Language based ADE application schema generation. This research would help the users to easily store and exchange 3D city data on which they can perform routing and positioning inside the buildings with enhanced semantic and geometric properties.
KeywordsCityGML ADE Indoor routing Indoor positioning 3D city
- Abdul-Rahman, A., & Pilouk, M. (2007). Spatial data modelling for 3D GIS. Berlin: Springer.Google Scholar
- Becker, T., Nagel, C., & Kolbe, T. H. (2011). Integrated 3D modeling of multi-utility networks and their interdependencies for critical infrastructure analysis. In Advances in 3D Geo-Information Sciences (pp. 1–20): Springer, Berlin.Google Scholar
- Coors, V., & Flick, S. (1998). Integrating Levels of Detail in a Web-based 3D-GIS. In Proceedings of the 6th ACM international symposium on Advances in geographic information systems, (pp. 40–45): ACM.Google Scholar
- Cypriani, M., Lassabe, F., Canalda, P., & Spies, F. (2010). Wi-Fi-based indoor positioning: Basic techniques, hybrid algorithms and open software platform. In Indoor Positioning and Indoor Navigation (IPIN), 2010 International Conference on, (pp. 1–10): IEEE.Google Scholar
- Czerwinski, A., Sandmann, S., Stöcker-Meier, E., & Plümer, L. (2007). Sustainable SDI for EU noise mapping in NRW–best practice for INSPIRE. International Journal for Spatial Data Infrastructure Research, 2(1), 90–111.Google Scholar
- Evennou, F., & Marx, F. (2006). Advanced integration of WiFi and inertial navigation systems for indoor mobile positioning. EURASIP Journal on Applied Signal Processing, 2006, 164.Google Scholar
- Gröger, G., Kolbe, T., Nagel, C., & Häfele, K. (2012). OGC City Geography Markup Language (CityGML) En-coding Standard. Open Geospatial Consortium Inc, OGC.Google Scholar
- Hagedorn, B., Trapp, M., Glander, T., & Dollner, J. (2009). Towards an indoor level-of-detail model for route visualization. In Mobile Data Management: Systems, Services and Middleware, 2009. MDM’09. Tenth International Conference on, (pp. 692–697): IEEE.Google Scholar
- Kim, Y., Kang, H., & Lee, J. (2013). Development of indoor spatial data model using CityGML ADE (pp. 41–45). Remote Sensing and Spatial Information Sciences: J. ISPRS-International Archives of the Photogrammetry.Google Scholar
- Kolbe, T. H. (2009). Representing and exchanging 3D city models with CityGML. In 3D geo-information sciences (pp. 15–31): Springer, Berlin.Google Scholar
- Krüger, A., & Kolbe, T. (2012). Building analysis for urban energy planning using key indicators on virtual 3D city models—the energy atlas of Berlin. In Proceedings of the ISPRS Congress. Google Scholar
- Lee, J. (2004). 3D GIS for geo-coding human activity in micro-scale urban environments. In International Conference on Geographic Information Science (pp. 162–178): Springer, Berlin.Google Scholar
- Lee, J., & Zlatanova, S. (2008). A 3D data model and topological analyses for emergency response in urban areas. Geospatial Information Technology for Emergency Response, 143, 168.Google Scholar
- Martí, R. M. (2013). UJI Navigation Network, Development of a pedestrian spatial network within the University Jaume I of Castellón (Spain). https://run.unl.pt/bitstream/10362/9201/1/TGEO0106.pdf. Accessed on 10 January 2016.
- Moshrefzadeh, M., Donaubauer, A., & Kolbe, T. H. (2015). A CityGML-based Façade Information Model for Computer Aided Facility Management.Google Scholar
- Oldevik, J. (2004). UML Model Transformation Tool. Retrieved from UMT-QVT. http://umt-qvt.sourceforge.net/docs/UMT_documentation_v08.pdf. Accessed on 22 February 2016.
- Prasad, K. (2013). 3D Pedestrian Network of UTown. Institute for Transport Planning and Systems, Swiss Federal Institute of Technology Zurich. http://www.ivt.ethz.ch/docs/students/sa371.pdf. Accessed on 15 January 2016.
- Rappaport, T. S. (1996). Wireless Communications: Principles and Practice. Prentice Hall Communications Engineering & Emerging Technologies Series.Google Scholar
- Ting, S., Kwok, S. K., Tsang, A. H., & Ho, G. T. (2011). The study on using passive RFID tags for indoor positioning. International Journal of Engineering Business Management, 3(1), 9–15.Google Scholar
- Van den Brink, L., Stoter, J., & Zlatanova, S. (2012). Modelling an application domain extension of CityGML in UML. In ISPRS Conference 7th International Conference on 3D Geoinformation, The International Archivees on the Photogrammetry, Remote Sensing and Spatial Information Sciences, Volume XXXVIII-4, part C26, 16–17 May 2012, Québec, Canada,: ISPRS.Google Scholar
- Xu, H., Badawi, R., Fan, X., Ren, J., & Zhang, Z. (2009). Research for 3D visualization of digital city based on SketchUp and ArcGIS. In International Symposium on Spatial Analysis, Spatial-Temporal Data Modeling, and Data Mining, (pp. 74920Z–74920Z–74926): International Society for Optics and Photonics.Google Scholar
- Zlatanova, S., & Tempfli, K. (2000). Modelling for 3D GIS: Spatial analysis and visualisation through the web. In International Archives of Photogrammetry and Remote Sensing Vol. XXXIII, XIXth Congress ISPRS, Amsterdam, 2000, Gopher Publishers.Google Scholar