A visual analytics design for studying rhythm patterns from human daily movement data

Wei Zeng, Chi Wing Fu, Stefan Müller Arisona, Simon Schubiger, Remo Burkhard, Kwan-Liu Ma

Research output: Contribution to journalArticle

4 Scopus citations

Abstract

Human's daily movements exhibit high regularity in a space–time context that typically forms circadian rhythms. Understanding the rhythms for human daily movements is of high interest to a variety of parties from urban planners, transportation analysts, to business strategists. In this paper, we present an interactive visual analytics design for understanding and utilizing data collected from tracking human's movements. The resulting system identifies and visually presents frequent human movement rhythms to support interactive exploration and analysis of the data over space and time. Case studies using real-world human movement data, including massive urban public transportation data in Singapore and the MIT reality mining dataset, and interviews with transportation researches were conducted to demonstrate the effectiveness and usefulness of our system.

Original languageEnglish (US)
Pages (from-to)81-91
Number of pages11
JournalVisual Informatics
Volume1
Issue number2
DOIs
StatePublished - Jun 1 2017

Keywords

  • Event sequence
  • Movement rhythm
  • Visual analytics

ASJC Scopus subject areas

  • Computer Graphics and Computer-Aided Design
  • Human-Computer Interaction
  • Software

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