A 3D Indoor Routing Service with 2D Visualization Based on the Multi-Layered Space-Event Model

Donaubauer, Andreas; Straub, Florian; Panchaud, Nadia H.; Vessaz, Claude

doi:10.1007/978-3-642-34203-5_25

Cited by 3 publications

(2 citation statements)

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“…To host geospatial data features, the Oracle Spatial and Graph platform has a built-in geocoding and routing engine, allowing the quick implementation of customized solutions in the area of routing and navigation. It is worth noting that Oracle Spatial and the built-in routing engine were successfully utilized for routing within an IndoorGML (MLSEM) dataset in related research [66]. The IndoorGML source data could initially be transformed with FME.…”

Section: Discussionmentioning

confidence: 99%

Big Data in Smart City: Management Challenges

et al. 2021

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Smart cities use digital technologies such as cloud computing, Internet of Things, or open data in order to overcome limitations of traditional representation and exchange of geospatial data. This concept ensures a significant increase in the use of data to establish new services that contribute to better sustainable development and monitoring of all phenomena that occur in urban areas. The use of the modern geoinformation technologies, such as sensors for collecting different geospatial and related data, requires adequate storage options for further data analysis. In this paper, we suggest the biG dAta sMart cIty maNagEment SyStem (GAMINESS) that is based on the Apache Spark big data framework. The model of the GAMINESS management system is based on the principles of the big data modeling, which differs greatly from standard databases. This approach provides the ability to store and manage huge amounts of structured, semi-structured, and unstructured data in real time. System performance is increasing to a higher level by using the process parallelization explained through the five V principles of the big data paradigm. The existing solutions based on the five V principles are focused only on the data visualization, not the data themselves. Such solutions are often limited by different storage mechanisms and by the ability to perform complex analyses on large amounts of data with expected performance. The GAMINESS management system overcomes these disadvantages by conversion of smart city data to a big data structure without limitations related to data formats or use standards. The suggested model contains two components: a geospatial component and a sensor component that are based on the CityGML and the SensorThings standards. The developed model has the ability to exchange data regardless of the used standard or the data format into proposed Apache Spark data framework schema. The verification of the proposed model is done within the case study for the part of the city of Novi Sad.

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Section: Discussionmentioning

confidence: 99%

Big Data in Smart City: Management Challenges

et al. 2021

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“…Route planning implies a great variety of applications as, for example, indoor routing (Goetz 2012) with special preferences (Karimi and Ghafourian 2010) and within a 3D environment (Donaubauer et al 2013;Steuer 2013), maritime routing for ships, routing for disabled people who need more detailed information on the transportation infrastructure for their movement (Neis 2014;Neis and Zielstra 2014) or even routing on a road network by air quality parameters (Karrais, Keler, and Timpf 2014).…”

Section: State Of the Art -Routing Applicationsmentioning

confidence: 99%