Spatial Information Research

Korea Spatial Information Society (대한공간정보학회)
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Basic Concepts of Indoor Spatial Information Candidate Standard IndoorGML and its Applications

실내공간 표준안 IndoorGML의 개념 및 활용

  • Li, Ki Joune (Dept. Computer Science and Engineering, Pusan National Univ.) ;
  • Lee, Ji Yeong (Dept. Geoinformatics, University of Seoul)
  • Received : 2013.05.03
  • Accepted : 2013.06.24
  • Published : 2013.06.30
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Abstract

Indoor space is a new horizon of spatial information services. With recent progress of indoor positioning technologies and mobile devices such as smart phones, indoor spatial information services become available and an emerging market. Accordingly, exchanging and sharing indoor spatial information between independent services become an important issue. For this reason, a standardization working group, called IndoorGML has been launched last year in OGC with the aim of publishing IndoorGML standard by September, 2013. Its primary goal is to provide a framework for representing network topology in indoor space, which is a fundamental element of indoor LBS. In this paper, we will explain the basic concepts of indoorGML and discuss the modeling issues. And several application use-cases of IndoorGML will be also presented in this paper.

실내공간은 공간정보 서비스의 새로운 대상이다. 최근 실내공간 측위 기술의 발달과 스마트폰 등 이동기기의 보편화로 실내공간도 위치기반 서비스와 같은 서비스가 가능하여지고 있다. 따라서 실내공간 정보의 교환 및 공유를 위한 표준화도 중요한 요구사항으로 떠오르고 있다. 이러한 배경에서 국제공간정보 표준화기구인 OGC에서는 실내공간정보 표준인 IndoorGML 표준화 작업반을 2012년에 조직하고 2013년 9월 표준화를 목적으로 현재 작업 중이다. IndoorGML은 특히 실내공간의 위치기반 서비스를 제공하기 위하여 가장 기초가 되는 네트워크 위상을 표현하는 것을 목적으로 한다. 본 논문에서는 첫 번째로 현재 표준화되고 있는 IndoorGML의 기본 개념을 설명한다. 두 번째로 IndoorGML의 모델의 구체적 사항을 살펴보고, 세 번째 간단한 응용 사례를 제시한다.

Keywords

References

  1. Becker, C; Durr F. 2005, On location models for ubiquitous computing. Personal and Ubiquitous Computing 9(1): 20-31 https://doi.org/10.1007/s00779-004-0270-2
  2. Becker, T; Nagel C; Kolbe, H. T. 2009, A Multilayered Space-Event Model for Navigation in Indoor Spaces, Proc. 3D Geo-Info Symposium, Lecture Nodes in Geoinformation and Cartography 2009: 61-77, Springer-Verlag
  3. Becker, T; Nagel, C; Kolbe, T. 2010, Discussion of Euclidean space and cellular space and proposal of an integrated indoor space data mpdel, Technical Report. Institute of Geodesy and Geoinformation Science, TU Berlin
  4. buildingSMART, IFC4 (Industrial Foundation Classes XML 4) RC4, http://www.buildings mart-tech.org/specifications/ ifcxml-releases/ifcxml4-release, 2012
  5. Open Geospatial Consortium, City Geographic Markup Language (CityGML) Encoding Standard 2.0, Document Number 12-019 OGC, https://portal.opengeospatial.org/files/?artifact_ id=47842
  6. ISO/TC211, ISO 19107:2003, Geographic Information - Spatial Schema
  7. ISO/TC211, ISO 19109:2005, Geographic Information - Rules for Application Schema, 2005
  8. Jensen, C. S; Lu, H; Yang, B. 2009, Graphic Model Based Indoor Tracking, Proc. 10th MDM Conf. May, 2009, Taipei, Taiwan
  9. Jensen, C. S; Lu, H; Yang, B. 2010, Indoor-A New Data Management Frontier, IEEE Data Eng. Bulletin, 33(2): 12-17
  10. Kang, H. Y; Kim, J. S; Li, K. J. 2010, sTrack: Tracking in indoor symbolic spacewith RFID sensors, Proc. 18th SIGSPATIAL Conf. 2010, San Jose, USA, pp. 502-505
  11. Kim, J. S; Li, K. J. 2012, K-Anonymity using Hierarchical Graph Structure in Indoor Space, KSIS Journal 20(4): 93-101
  12. Lee, J. 2004, A Spatial Access Oriented Implementation of a Topological Data Model for 3D Urban Entities. GeoInformatica 8(3): 235-262
  13. Lee, K. J; Lee, J. 2013, A Geocoding Method on Character Matching in Indoor Spaces, KSIS Journal 21(5): 87-100 https://doi.org/10.12672/ksis.2013.21.1.087
  14. Li, K. J. 2008, Indoor space: A new notion of space, Proc. 8th International Symposium Web and Wireless Geographical Information Systems (W2GIS), Shangahi, China, 2008, pp. 1-3.
  15. Li, K. J. 2012, IndoorGML - an Overview, IndoorGML Workshop, http://stem.cs.pnu.kr/ indoorGMLWorkshop/Program.html, Oct. 2012, Seoul Korea
  16. Nagel, C; Becker, T; Li, K. J; Lee, J; Kaden, R; Kolbe, T. 2010, Requirements and space-event modeling for indoor navigation. Discussion Paper, OGC 10-191r1, Open Geospatial Consortium http://portal.myogc.org/files/41727, .
  17. Open Geospatial Consortium, 2013, IndoorGML v.0.6.4, OGC https://portal.opengeospatial.org/ index.php?m=projects&a=view& project_id=399&tab=2&artifact_id=52528,
  18. Yang, B; Lu, H; Jensen, C. S. 2009, Scalable Continuous Range Monitoring of Moving Objects in Symbolic Indoor Space, Proc. 18th ACM CIKM Conf. 671-680, Nov. 2009, Hong Kong.

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