Abstract

This paper presents an approach to build a spatial database for indoor environments. It will be presented the main requirements for the implementation of an object-relational database for the representation and analysis of indoor environments, which considers the solutions for both type of representations, floor plan and schematic map. These representations consider the high number of information found in an indoor environment and the fact that they are disposed in different floors of the structure. The relationship between objects and their attributes defines the links and restrictions between them. Hence, the model should describe the entities and their interrelationships, as well as the attributes of the elements and their characteristics. After the database was developed, it was implemented an algorithm that calculates routes between points in the indoor environment, considering not only the shortest distance but also the floor change. The model was tested by Antunes and Delazari (2019) using an application and some interviews with users to evaluate the elements included in the database considering a navigating task. Some results pointed out the need to insert new information in the database regarding physical characteristics (color, material) of elements found in the indoor environment to assist users during orientation and navigation tasks. Moreover, it is necessary to include elements from the outdoor environment used as reference points in the cartographic representation.

Highlights

  • Kang and Li (2017) presented a review for the indoor spatial models based on the IndoorGML and classify them to both geometric and symbolic approach

  • According to Kang and Li (2017), since each approach has its strengths and weaknesses, it may be recommended to integrate the strengths of multiple approaches into a single indoor spatial data model to compensate the weaknesses

  • The research by Antunes and Delazari (2019) verified whether the model suits positioning and navigation tasks in the indoor environment through user tests. This test used the Indoor Positioning System (IPS) based on QR-Code linked to the model of indoor database to evaluate if this solution helps the spatial orientation process

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Summary

Introduction

The complexity of buildings and the development of indoor positioning technology provided support to the creation of indoor cartography (Schiller & Voisard, 2004). Kang and Li (2017) presented a review for the indoor spatial models based on the IndoorGML and classify them to both geometric and symbolic approach. Kang and Li (2017) presented a review for the indoor spatial models based on the IndoorGML and classify them to both geometric and symbolic approach. The first approach is mainly focused on the geometric representation of indoor features. The symbolic approach emphasizes the semantics and ontology aspects of unit space rather than its geometric properties. According to Kang and Li (2017), since each approach has its strengths and weaknesses, it may be recommended to integrate the strengths of multiple approaches into a single indoor spatial data model to compensate the weaknesses. A hybrid data model may represent geometric properties on one hand, and support symbolic concepts of indoor space on the other

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