Skip to main content
Kent Academic Repository

MetroBuzz: Interactive 3D visualization of spatiotemporal data

Zeng, Wei and Zhong, Chen and Anwar, Afian and Arisona, Stefan Müller and McLoughlin, Ian Vince (2012) MetroBuzz: Interactive 3D visualization of spatiotemporal data. In: 2012 International Conference on Computer & Information Science (ICCIS). IEEE, pp. 143-147. ISBN 978-1-4673-1937-9. E-ISBN 978-1-4673-1938-6. (doi:10.1109/ICCISci.2012.6297228) (The full text of this publication is not currently available from this repository. You may be able to access a copy if URLs are provided) (KAR id:48927)

The full text of this publication is not currently available from this repository. You may be able to access a copy if URLs are provided.
Official URL:
http://dx.doi.org/10.1109/ICCISci.2012.6297228

Abstract

The rapidly increasing use of mobile devices for sensing applications, and the growing amount of simulated data generated from simulation tools such as agent-based transport simulations results in massive spatiotemporal datasets. Therefore, the demand for applications to manage and to visualize this data effectively in an interactive and easily understandable way increases quickly. Spatiotemporal visualization has long been recognized as being able to provide a suitable solution for creating such applications. However it remains a challenging task to combine such a visualization with interactive operation. In this paper, we describe MetroBuzz, a prototype system designed for visualizing large amounts of spatiotemporal data, and for interacting with the dataset in a way that is both interesting from a scientific viewpoint as well as for a broader non-expert audience. At its core, MetroBuzz generalizes activities in urban networks, specified as origin-destination trip information in terms of series of line segments in 3D space. These 3D elements are stored in a spatial index that allows quick retrieval of relevant data. Based on this, we implemented interactive tools to define queries on the spatial index in an intuitive manner. We show how such tools can be applied in the case of large transport simulation datasets.

Item Type: Book section
DOI/Identification number: 10.1109/ICCISci.2012.6297228
Uncontrolled keywords: biological system modeling; androids; humanoid robots; materials
Subjects: T Technology
Divisions: Divisions > Division of Computing, Engineering and Mathematical Sciences > School of Computing
Depositing User: Ian McLoughlin
Date Deposited: 25 Aug 2015 10:26 UTC
Last Modified: 05 Nov 2024 10:33 UTC
Resource URI: https://kar.kent.ac.uk/id/eprint/48927 (The current URI for this page, for reference purposes)

University of Kent Author Information

McLoughlin, Ian Vince.

Creator's ORCID: https://orcid.org/0000-0001-7111-2008
CReDIT Contributor Roles:
  • Depositors only (login required):

Total unique views for this document in KAR since July 2020. For more details click on the image.