Using Volunteered Geographic Information for an Automated Provision of Indoor Location Based Services
Public buildings such as hotels, airports or shopping malls are becoming bigger and bigger and furthermore
their internal structures are getting more complex. This phenomenon results in the issue, that persons
(especially foreign people) are likely to get lost inside the building or to take circuitous routes when navigating
through the building. In the area of leisure time (e.g. shopping) this might be just disturbing, but in business life
this could result in losing time and money. In the area of emergency situations or rescue forced, the fastest
route is even more crucial, because one second can decide between life and death. Today’s navigation
solutions are becoming more mature and versatile, however they are mainly designed for outdoor areas (e.g.
vehicle navigation, bicycle navigation or pedestrian navigation). That is, there is an increasing demand for
advanced and sophisticated indoor navigation solutions for many different areas (Cf. ).
One of the core problems is, where adequate data could be acquired from for such indoor navigation
applications. A large‐scale data acquisition by commercial data providers (e.g. Navteq etc.) is not likely for
indoor environment. That is, alternative data sources (both internal and external) are required. One example
for such new, alternative data sourced is Volunteered Geographic Information (VGI), describing a collective and
collaborative accumulation of spatial data through a web 2.0 platform. One of the most famous examples for
VGI is OpenStreetMap (OSM), whereby both data quality and quantity steadily increases. Currently, OSM
mainly contains information about the outdoor space, but there are already more than 34 million building
footprints as well as additional building attributes (e.g. height, color, roof shape etc.) available.
The intention of this dissertation project is the usage of VGI data from OSM for the provision of indoor
navigation applications. Thereby, methodologies for the extension of OSM towards indoor environments need
to be defined, so that detailed information about different floor plans and distinct rooms can be acquired and
provided. Based on this data, CityGML LoD4 building models will be generated. CityGML is chosen due to the
fact that it represents an internationally accepted standard for exchanging 3D city models including semantic
information. These (automatically) generated building models will then be used for derivating 3D routing
graphs. By applying diverse routing algorithms (e.g. Dijkstra, A* etc.) on these graphs, optimal routes (according
to distinct requirements) can be calculated. That is, the benefit of this dissertation project is on the one hand
the extension of OSM for indoor environments as well as the automated generation of standardized 3D
building models from OSM. On the other hand, another benefit is also the generation of routing graphs from
standardized city models.
First research on indoor routing graphs has already been developed and published (Cf. ). Additionally, initial
thoughts for generating city models based on OSM are available (Cf. ), as well as extending OSM to indoor
environments (Cf. ).
 Goetz M., Zipf A. (2010): Open Issues in Bringing 3D to Location Based Services (LBS) ‐ A Review Focusing on 3D Data Streaming and 3D Indoor Navigation. 5th 3D GeoInfo Conference. Berlin, Germany.
 Goetz, M., Zipf, A. (2011): Formal Definition of an User‐adaptive and Length‐optimal Routing Graph for Complex Indoor Environments. In: Geo‐spatial Information Science (GSIS), Vol. 14, Issue 2. Springer.
 Goetz, M., Zipf, A. (2011): Towards Defining a Framework for the Automatic Derivation of 3D CityGML Models from Volunteered Geographic Information. Joint ISPRS Workshop on 3D City Modelling & Applications and the 6th 3D GeoInfo Conference. Wuhan, China
 Goetz M., Zipf A. (2011): Extending OpenStreetMap to Indoor Environments: Bringing Volunteered Geographic Information to the Next Level. 28th Urban Data Management Symposium. Delft, the Netherlands