A distributed POI data model based on the entity-component approach

Heikkinen, Arto; Okkonen, Ari; Karhu, Antti; Koskela, Timo

doi:10.1109/iscc.2014.6912570

Cited by 5 publications

(3 citation statements)

References 12 publications

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“…Tracing the timeline of POI standard development would begin with nodes in OpenStreetMap (OSM), KML, and Places Library of Google Maps but individually lacks in aspects that are essential to the direction of applications where POIs are going [3,20] place identifiers in ISO 19112 [21] and ISO 19155 [22]. Specifically, the World Wide Web Consortium (W3C) POI Special Working Group (SWG) has become the first step towards the standardization for the definition and exchange with a focus on web architecture and in AR applications.…”

Section: Related Researchmentioning

confidence: 99%

“…Specifically, the World Wide Web Consortium (W3C) POI Special Working Group (SWG) has become the first step towards the standardization for the definition and exchange with a focus on web architecture and in AR applications. SWG has published the Point of Interest Core (POI Core), describing eight categories to describe POI with attributes and various location types [1,3].…”

Section: Related Researchmentioning

confidence: 99%

“…Nowadays, day-to-day human activities have been closely tied with the use of mobile devices and gadgets, most equipped with GPS receivers and cameras, and are continuously improving in terms of features and speeds while decreasing in size [1,2]. With this, the demand for information arose through location-based services (LBS), which aim to give users relevant and timely information based on their positions [1,3], and augmented reality (AR) applications that combine images from the real-world to virtual images in three-dimensions [4]. These services form part of the core requirement of Smart Cities, as localities around the world aim to establish seamless integration of technology to the daily life of its citizens.…”

Section: Introductionmentioning

confidence: 99%

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Developing a Data Model of Indoor Points of Interest to Support Location-Based Services

Claridades

Lee

2020

Journal of Sensors

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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.

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Section: Related Researchmentioning

confidence: 99%

Section: Related Researchmentioning

confidence: 99%