Indoor Route Planning with Volunteered Geographic Information on a (Mobile) Web-Based Platform

  • Marcus Goetz
  • Alexander Zipf
Part of the Lecture Notes in Geoinformation and Cartography book series (LNGC)


Route planning services for a priori route planning on computers or on-demand planning on mobile devices are omnipresent, not only for vehicles but also for bicyclists or pedestrians. Furthermore, public or commercial buildings such as hospitals, hotels or shopping malls are getting bigger and their inner complexity increases. Additionally, most of the time of our lives is spent indoors, apparently quite often in unknown and foreign buildings. Consequently, the need for mature indoor route planning applications emerged and both academia and economy are now trying to adapt well known outdoor routing services to complex indoor spaces. Contrary to the outdoors, where typically commercial data providers or professional surveyors capture spatial data, it is unlikely that commercial institutes are able to capture indoor information on a large-scale. In the last couple of years, Volunteered Geographic Information (VGI) or crowdsourced geodata has increasingly gained attractiveness and the manifoldness and quality of such data has already been demonstrated in different (outdoor) applications. Trying to gain traction in the emerging field of indoor applications, OpenStreetMap (OSM) as one of the most popular VGI communities aims at taking the lead in capturing information about indoor spaces. Trying to satisfy the demand for indoor services, this chapter presents an extensive application for indoor environments. By providing indoor maps and route planning services with indoor OSM data, the here conducted work on the one hand demonstrates the possibilities arising from VGI and on the other hand provides a mature indoor application. In particular, the developed application can be used for a priori route planning at home on a personal computer as well as for on-demand route planning on a mobile device. A prototypical implementation for BlackBerry smartphones is also presented, whereas the application, due to its design and technology, can be easily ported to other mobile platforms such as Android smartphones, iPhones or iPads.


Crowdsourced geodata Indoor routing Indoor route planning OpenStreetMap Volunteered geographic information 



The authors of this chapter would like to express their thankfulness to the anonymous reviewers. By providing their valuable comments on this chapter they contributed towards the improvement of our work. Furthermore we would like to thank all the members of our group for their proofreading and comments. This research has been partially funded by the Klaus-Tschira Foundation (KTS) Heidelberg.


  1. Abowd GD, Atkeson CG, Hong J, Long S, Kooper R, Pinkerton M (1997) Cyberguide: a mobile context-aware tour guide. Wirel Netw 3(5):421–433CrossRefGoogle Scholar
  2. APS (2008) Energy future: think efficiency. A report of the american physical society (APS). WashingtonGoogle Scholar
  3. Bing 2011: Bing Maps venue maps now feature nine largest US malls, 148 total. Accessed 31 Mar 2012
  4. Dijkstra EW (1959) A note on two problems in connexion with graphs. Numer Math 1(1):267–271CrossRefGoogle Scholar
  5. Gilliéron P-Y, Bertrand M (2003) Personal navigation system for indoor applications. In: 11th IAIN world congress, Berlin, p 15Google Scholar
  6. Goetz M, Lauer J, Auer M (2012) An algorithm based methodology for the creation of a regularly updated global online map derived from volunteered geographic information. chapter presented at the 4th international conference on advanced geographic information systems, applications and services (GEOProcessing 2012), ValenciaGoogle Scholar
  7. 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. In: 5th 3D geoInfo conference, Berlin, pp 121–124Google Scholar
  8. Goetz M, Zipf A (2011a) Extending openstreetmap to indoor environments: bringing volunteered geographic information to the next level. In: Rumor M, Zlatanova S, Fendel EM, LeDoux H (eds) Urban and regional data management: UDMS annual 2011, Delft, The Netherlands, pp 47–58Google Scholar
  9. Goetz M, Zipf A (2011b) Formal definition of a user-adaptive and length-optimal routing graph for complex indoor environments. Geo Spat Inf Sci 14(2):119–128CrossRefGoogle Scholar
  10. Goodchild MF (2007) Citizens as voluntary sensors: spatial data infrastructure in the World of Web 2.0. Int J Spat Data Infrastruct Res 2:24–32Google Scholar
  11. Google (2011) Go indoors with google maps 6.0 for android. Accessed 31 Mar 2012
  12. Haklay M (2010) How good is volunteered geographical information? A comparative study of OpenStreetMap and ordnance survey datasets. Environ Plan B-Plan Des 37(4):682–703CrossRefGoogle Scholar
  13. Hijazi I, Ehlers M (2009) Web 3D routing in and between buildings. In: Fourth national GIS symposium, Al-Khobar, pp 11–21Google Scholar
  14. Höllerer T, Feiner S, Terauchi T, Rashid G, Hallaway D (1999) Exploring MARS: developing indoor and outdoor user interfaces to a mobile augmented reality system. Comput Graph 23(6):779–785CrossRefGoogle Scholar
  15. Huang H, Gartner G, Schmidt M, LI Y (2009) Smart environment for ubiquitous indoor navigation. In: 4th international conference on new trends in information and service science (NISS), Gyeibgju, pp 176–180Google Scholar
  16. Hubel A (2011) Webbrowser based indoor navigation for mobile devices based on OpenStreetMap. Accessed 21 June 2012
  17. Inoue Y, Ikeda T, Yamamoto K, Yamashita T, Sashima A, Kurumatani K (2008) Usability study of indoor mobile navigation system in commercial facilities. In: 2nd international workshop on ubiquitous systems evaluation (USE ‘08), Seoul, pp 1–6Google Scholar
  18. Jensen C, Li K-J, Winter S (2011) The other 87 %: a report on the second international workshop on indoor spatial awareness (San Jose, California, 2 November, 2010). ACM SIGSPATIAL Newsl 3(1):10–12Google Scholar
  19. Kargl F, Bernauer A (2005) The compass location system. In: Location and context awareness, first international workshop, LoCA 2005 Oberpfaffendorf, p 8Google Scholar
  20. Kargl F,Dannhäuser G, Schlott S, Nagler-Ihlein J (2006) Semantic information retrieval in the compass location system. In: International conference on ubiquitous computing systems (UCS 2006), Seoul, p 4Google Scholar
  21. Kargl F, Geßler S, Flerlage F (2007) The iNAV indoor navigation system. In: 4th international symposium on ubiquitous computing systems (UCS 2007), Tokyo, pp 110–117Google Scholar
  22. Karimi HA, Ghafourian M (2010) Indoor routing for individuals with special needs and preferences. Trans GIS 14(3):299–329CrossRefGoogle Scholar
  23. Krüger A, Butz A, Müller C, Stahl C, Wasinger R, Steinberger K-E, Dirschl A (2004) The connected user interface: realizing a personal situated navigation service. In: 9th international conference on intelligent user interfaces, Funchal, pp 161–168Google Scholar
  24. Liu H, Darabi H, Banerjee P, Liu J (2007) Survey of wireless indoor positioning techniques and systems. IEEE Trans Syst Man Cybern Part C Appl Rev 37(6):1067–1080CrossRefGoogle Scholar
  25. Lyardet F, Grimmer J, Muhlhauser M (2006) CoINS: context sensitive indoor navigation system. In 8th IEEE international symposium on multimedia (ISM’06), San Diego, pp 209–218Google Scholar
  26. Lyardet F, Szeto DW, Aitenbichler E (2008) Context-aware indoor navigation. In: European conference on ambient intelligence (AML 08) Nürnberg, pp 290–307Google Scholar
  27. Mapquest (2012) Mapquest. Accessed 17 June 2012
  28. Mäs S, Reinhardt W, Wang F (2006) Conception of a 3D geodata web service for the support of indoor navigation with GNSS. In: Abdul-Rahman A, Zlatanova S, Coors V (eds) Innovations in 3D geoinformation science, lecture notes in geoinformation and cartography. Springer, Heidelberg, pp 307–316CrossRefGoogle Scholar
  29. Meijers M, Zlatanova S, Pfeifer N (2005) 3D geo-information indoors: structuring for evacuation. In: 1st international ISPRS/EuroSDR/DGPF-workshop on next generation 3D city models (euroSDRbonn), Bonn, p 6Google Scholar
  30. NAVTEQ (2011) NAVTEQ extends the journey beyond the ‘front door’. Accessed 31 Mar 2012
  31. Neis P, Zielstra D, Zipf A (2012) The street network evolution of crowdsourced maps: openstreetmap in Germany 2007–2011. Futur Internet 4(1):1–21Google Scholar
  32. Neis P, Zipf A (2008) is three times “open”: combining opensource, openls and openstreetmaps. In Lambrick D (ed) GIS research UK (GISRUK), ManchesterGoogle Scholar
  33. OSM (2012a) Indoor mapping. Accessed 11 April 2012
  34. OSM (2012b) IndoorOSM. Accessed 31 Mar 2012
  35. OSM (2012c) IndoorOSM. Accessed 11 Mar 2012
  36. Papataxiarhis V, Riga V, Nomikos V, Sekkas O, Kolomvatsos K, Tsetsos V, Papageorgas P, Vourakis S, Xouris V, Hadjiefthymiades S, Kouroupetroglou G (2008) MNISIKLIS: indoor location based services for all. In: Location based services and telecartography: from sensor fusion to ubiquitous LBS. Springer, Berlin pp 263–282Google Scholar
  37. Pateli AG, Giaglis GM, Spinellis DD (2005) Trial evaluation of wireless info-communication and indoor location-based services in exhibition shows. In: Bozanis P, Houstis EN (eds) Advances in informatics. Volas, Greece, pp 199–210Google Scholar
  38. Pfaff T (2007) Entwicklung eines PDA-basierten indoor-navigationssystems. Hochschule für Angewandte Wissenschaften HamburgGoogle Scholar
  39. Privat L (2011) NAVTEQ gets serious about indoor maps. Accessed 2 Mar 2012
  40. Raad M (2009) Thunderhead explorer: indoor routing for UC2009 on iPhone. Accessed 31 Mar 2012
  41. Rehrl K, Göll N, Leitinger S, Bruntsch S (2005) Combined indoor/outdoor smartphone navigation for public transport travellers. In: 3rd symposium on LBS & teleCartography 2005, Vienna, pp 235–239Google Scholar
  42. Rosser J, Morley J, Jackson M (2012) Mobile modelling for crowdsourcing building interior data. chapter presented at the 7th 3D GeoInfo, Quebec CityGoogle Scholar
  43. Ruppel P, Gschwandtner F (2009) Spontaneous and privacy-friendly mobile indoor routing and navigation. In 2nd workshop on services, platforms, innovations and research for new infrastructures in telecommunications (SPIRIT 2009), Lübeck, p 10Google Scholar
  44. Schmidt-Belz B, Hermann F (2004) User validation of a nomadic exhibition guide. In: Brewster S, Dunlop M (eds) Human computer interaction with mobile devices and services (Mobile HCI 2004), Glasgow, Scotland. Springer, Berlin, pp 86–97Google Scholar
  45. TAGWATCH, 2012: Watchlist. Accessed 10 Apr 2012
  46. Winter S (2012) Indoor spatial information. Int J 3-D Inf Model 1(1):25–42Google Scholar
  47. Zielstra D, Zipf A (2010) A comparative study of proprietary geodata and volunteered geographic information for Germany. In: Painho M, Santos YM, Pundt H (eds) 13th AGILE international conference on geographic information science, Guimarães, pp 1–15Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2013

Authors and Affiliations

  1. 1.GIScience Group, Institute of GeographyUniversity of HeidelbergHeidelbergGermany

Personalised recommendations