Developing a Data Model of Indoor Points of Interest to Support Location-Based Services
Focus on indoor spatial applications has been rising with the growing interest in indoor spaces. Along with the widespread use of mobile devices and the internet, it has increased demands for indoor location-based services (LBS), demanding more efficient representation and management of indoor spati...
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doaj-62411a1014da474890d7bc700d9acd0d2020-11-25T03:03:34ZengHindawi LimitedJournal of Sensors1687-725X1687-72682020-01-01202010.1155/2020/88853848885384Developing a Data Model of Indoor Points of Interest to Support Location-Based ServicesAlexis Richard C. Claridades0Jiyeong Lee1Department of Geoinformatics, University of Seoul, 163 Seoulsiripdae-ro, Dongdaemun-gu, Seoul 02504, Republic of KoreaDepartment of Geoinformatics, University of Seoul, 163 Seoulsiripdae-ro, Dongdaemun-gu, Seoul 02504, Republic of KoreaFocus on indoor spatial applications has been rising with the growing interest in indoor spaces. Along with the widespread use of mobile devices and the internet, it has increased demands for indoor location-based services (LBS), demanding more efficient representation and management of indoor spatial data. Indoor points of interest (Indoor POI) data, representing both spaces and facilities located indoors, provide the infrastructure for these services. These datasets are vital in delivering timely and accurate information to users, such as in cases of managing indoor facilities. However, even though there are studies that explore its use across applications and efforts exerted towards the standardization of the data model, most POI development studies have focused on the outdoors and remain underdeveloped in the indoors. In this paper, we propose a spatial-temporal Indoor POI data model to provide direction for the establishment of indoor POI data and to address limitations in currently available data specifications. By exploring how different Indoor POIs are from its outdoor counterparts, particularly on extending its outdoor counterparts’ functions on searching, sharing, and labeling, we describe the data model and its components using the Unified Modeling Language (UML). We perform an SQL-based query experiment to demonstrate the potential use of the data model using sample data.http://dx.doi.org/10.1155/2020/8885384 |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
Alexis Richard C. Claridades Jiyeong Lee |
spellingShingle |
Alexis Richard C. Claridades Jiyeong Lee Developing a Data Model of Indoor Points of Interest to Support Location-Based Services Journal of Sensors |
author_facet |
Alexis Richard C. Claridades Jiyeong Lee |
author_sort |
Alexis Richard C. Claridades |
title |
Developing a Data Model of Indoor Points of Interest to Support Location-Based Services |
title_short |
Developing a Data Model of Indoor Points of Interest to Support Location-Based Services |
title_full |
Developing a Data Model of Indoor Points of Interest to Support Location-Based Services |
title_fullStr |
Developing a Data Model of Indoor Points of Interest to Support Location-Based Services |
title_full_unstemmed |
Developing a Data Model of Indoor Points of Interest to Support Location-Based Services |
title_sort |
developing a data model of indoor points of interest to support location-based services |
publisher |
Hindawi Limited |
series |
Journal of Sensors |
issn |
1687-725X 1687-7268 |
publishDate |
2020-01-01 |
description |
Focus on indoor spatial applications has been rising with the growing interest in indoor spaces. Along with the widespread use of mobile devices and the internet, it has increased demands for indoor location-based services (LBS), demanding more efficient representation and management of indoor spatial data. Indoor points of interest (Indoor POI) data, representing both spaces and facilities located indoors, provide the infrastructure for these services. These datasets are vital in delivering timely and accurate information to users, such as in cases of managing indoor facilities. However, even though there are studies that explore its use across applications and efforts exerted towards the standardization of the data model, most POI development studies have focused on the outdoors and remain underdeveloped in the indoors. In this paper, we propose a spatial-temporal Indoor POI data model to provide direction for the establishment of indoor POI data and to address limitations in currently available data specifications. By exploring how different Indoor POIs are from its outdoor counterparts, particularly on extending its outdoor counterparts’ functions on searching, sharing, and labeling, we describe the data model and its components using the Unified Modeling Language (UML). We perform an SQL-based query experiment to demonstrate the potential use of the data model using sample data. |
url |
http://dx.doi.org/10.1155/2020/8885384 |
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AT alexisrichardcclaridades developingadatamodelofindoorpointsofinteresttosupportlocationbasedservices AT jiyeonglee developingadatamodelofindoorpointsofinteresttosupportlocationbasedservices |
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