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Short Paper

DOI: 10.4230/LIPIcs.COSIT.2022.16

Smart Crowd Management: The Data, the Users and the Solution (Short Paper)

Authors: Laure De Cock, Steven Verstockt, Christophe Vandeviver, and Nico Van de Weghe

Published in: LIPIcs, Volume 240, 15th International Conference on Spatial Information Theory (COSIT 2022)

Abstract

This research project is situated in the domain of smart crowd management, a domain that is gaining importance because of the challenges that arise from urbanization, but also the opportunities that come with smart cities. While our cities become more crowded every day, they also become smarter, for example by employing pedestrian tracking sensors. However, the datasets that are generated by these sensors do not allow smart crowd management yet, because they are sparse and not linked to the perception of the crowd. This research will tackle these issues in three steps. First, pedestrian counts will be estimated on streets that have no tracking data by use of deep learning and space syntax data. Next, the perception of crowdedness within the crowd will be linked to the objective pedestrian counts by conducting two user studies, and finally, the resulting subjective pedestrian counts will be used as weights for a routing algorithm. The last step has already been developed as a proof of concept. The routing algorithm, that uses partly simulated data and partly real-time tracking data, has been embedded in a webtool to show stakeholders the potential and goal of this innovative project.

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Laure De Cock, Steven Verstockt, Christophe Vandeviver, and Nico Van de Weghe. Smart Crowd Management: The Data, the Users and the Solution (Short Paper). In 15th International Conference on Spatial Information Theory (COSIT 2022). Leibniz International Proceedings in Informatics (LIPIcs), Volume 240, pp. 16:1-16:7, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2022)

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@InProceedings{decock_et_al:LIPIcs.COSIT.2022.16,
  author =	{De Cock, Laure and Verstockt, Steven and Vandeviver, Christophe and Van de Weghe, Nico},
  title =	{{Smart Crowd Management: The Data, the Users and the Solution}},
  booktitle =	{15th International Conference on Spatial Information Theory (COSIT 2022)},
  pages =	{16:1--16:7},
  series =	{Leibniz International Proceedings in Informatics (LIPIcs)},
  ISBN =	{978-3-95977-257-0},
  ISSN =	{1868-8969},
  year =	{2022},
  volume =	{240},
  editor =	{Ishikawa, Toru and Fabrikant, Sara Irina and Winter, Stephan},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/LIPIcs.COSIT.2022.16},
  URN =		{urn:nbn:de:0030-drops-169013},
  doi =		{10.4230/LIPIcs.COSIT.2022.16},
  annote =	{Keywords: crowd tracking, crowd modeling, space syntax, deep learning, perception, routing}
}

Document

Short Paper

DOI: 10.4230/LIPIcs.GISCIENCE.2018.55

Novel Models for Multi-Scale Spatial and Temporal Analyses (Short Paper)

Authors: Yi Qiang, Barbara P. Buttenfield, Nina Lam, and Nico Van de Weghe

Published in: LIPIcs, Volume 114, 10th International Conference on Geographic Information Science (GIScience 2018)

Abstract

Multi-scale analysis for spatio-temporal data forms a fundamental challenge for many analytic systems. In geographic information systems, analysis and modeling at pre-defined spatial and temporal scales may miss critical relationships in other scales. Previous studies have investigated the uses of the triangle model as a multi-scale framework in analyzing temporal data. This article demonstrates the utilities of the triangle model and pyramid model for multi-scale spatial analysis through real-world analytical tasks and discusses the potential of developing a unified modeling framework that integrates the two models.

Cite as

Yi Qiang, Barbara P. Buttenfield, Nina Lam, and Nico Van de Weghe. Novel Models for Multi-Scale Spatial and Temporal Analyses (Short Paper). In 10th International Conference on Geographic Information Science (GIScience 2018). Leibniz International Proceedings in Informatics (LIPIcs), Volume 114, pp. 55:1-55:7, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2018)

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@InProceedings{qiang_et_al:LIPIcs.GISCIENCE.2018.55,
  author =	{Qiang, Yi and Buttenfield, Barbara P. and Lam, Nina and Van de Weghe, Nico},
  title =	{{Novel Models for Multi-Scale Spatial and Temporal Analyses}},
  booktitle =	{10th International Conference on Geographic Information Science (GIScience 2018)},
  pages =	{55:1--55:7},
  series =	{Leibniz International Proceedings in Informatics (LIPIcs)},
  ISBN =	{978-3-95977-083-5},
  ISSN =	{1868-8969},
  year =	{2018},
  volume =	{114},
  editor =	{Winter, Stephan and Griffin, Amy and Sester, Monika},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/LIPIcs.GISCIENCE.2018.55},
  URN =		{urn:nbn:de:0030-drops-93832},
  doi =		{10.4230/LIPIcs.GISCIENCE.2018.55},
  annote =	{Keywords: Triangle Model, Pyramid Model, multi-scale spatial and temporal analysis, GIS}
}

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Documents authored by Van de Weghe, Nico

Smart Crowd Management: The Data, the Users and the Solution (Short Paper)

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Novel Models for Multi-Scale Spatial and Temporal Analyses (Short Paper)

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