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http://dx.doi.org/10.12672/ksis.2015.23.1.049

Generation of Indoor Network by Crowdsourcing  

Kim, Bo Geun (Dept. of Computer Science, Pusan National University)
Li, Ki-Joune (Dept. of Computer Science, Pusan National University)
Kang, Hae-Kyong (KRIHS)
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Abstract
Due to high density of population and progress of high building construction technologies, the number of high buildings has been increasing. Several information services have been provided to figure out complex indoor structures of building such as indoor navigations and indoor map services. The most fundamental information for these services are indoor network information. Indoor network in building provides topological connectivity between spaces unlike geometric information of buildings. In order to make indoor network information, we have to edit network manually or derive network properties based on the geometric data of buildings. This process is not easy for complex buildings. In this paper, we suggest a method to generate indoor network automatically based on crowdsourcing. From the collected individual trajectories, we derive indoor network information with crowdsourcing. We validate our method with a sample set of trajectory data and the result shows that our method is practical if the indoor positioning technology is reasonably accurate.
Keywords
Indoor Network; Cellular Space; State; Transition; IndoorGML;
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  • Reference
1 Alzantot, M; Yousself, M. 2012, Crowdinside: Automatic construction of indoor floorplans, ACM SIGSpatial Conference, Nov. 2012, pages 99-108.
2 Cao, L.; Krumn, J. 2009, From GPS traces to a routable road map, ACM SIGSpatial Conference, Nov. 2009. pages 3-12.
3 Karagiorgou, S.; Pfoser, D. 2012, On vehicle tracking data-based road network generation, ACM SIGSpatial Conference, Nov. 2012, pages 89-98.
4 Kim, Y. G; Shin, H. J; Cha H. J. 2012, Smartphone-based Wi-fi Pedestrian-tracking System Tolerating the RSS Variance Problem, IEEE International Conference, March 19-23, 2012, pages 11-29.
5 Kreveld, M. V; Wiratma, L. 2011, Median trajectories using well-visited regions and shortest paths, ACM SIGSpatial Conference, Nov. 2011, pages 241-240.
6 OGC, IndoorGML, http://www.opengeospatial.org/standards/indoorgml
7 Ojeda, L; Borenstein, J. 2007, Non-GPS navigation with the personal dead-reckoning system, SPIE Defemse and Security Conference 2007.