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Open AccessArticle

Development of an Indoor Space Semantic Model and Its Implementation as an IndoorGML Extension

Lab for Spatial Informatics, International Institute of Information Technology, Hyderabad 500032, India
Authors to whom correspondence should be addressed.
This paper is an extended version of our paper published in ISPRS Technical Commission IV Symposium 2018, 1–5 October 2018, Delft, The Netherlands.
ISPRS Int. J. Geo-Inf. 2019, 8(8), 333;
Received: 6 May 2019 / Revised: 15 June 2019 / Accepted: 20 July 2019 / Published: 27 July 2019
(This article belongs to the Special Issue Multidimensional and Multiscale GIS)
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Geospatial data capture and handling of indoor spaces is increasing over the years and has had a varied history of data sources ranging from architectural and building drawings to indoor data acquisition approaches. While these have been more data format and information driven primarily for the physical representation of spaces, it is important to note that many applications look for the semantic information to be made available. This paper proposes a space classification model leading to an ontology for indoor spaces that accounts for both the semantic and geometric characteristics of the spaces. Further, a Space semantic model is defined, based on this ontology, which can then be used appropriately in multiple applications. To demonstrate the utility of the model, we also present an extension to the IndoorGML data standard with a set of proposed classes that can help capture both the syntactic and semantic components of the model. It is expected that these proposed classes can be appropriately harnessed for use in diverse applications ranging from indoor data visualization to more user customised building evacuation path planning with a semantic overtone. View Full-Text
Keywords: classification; IndoorGML; indoor space; modeling; ontology; schema definition; semantics classification; IndoorGML; indoor space; modeling; ontology; schema definition; semantics

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This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited (CC BY 4.0).

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Maheshwari, N.; Srivastava, S.; Rajan, K.S. Development of an Indoor Space Semantic Model and Its Implementation as an IndoorGML Extension. ISPRS Int. J. Geo-Inf. 2019, 8, 333.

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