Towards a well-planned, activity-based work environment: Automated recognition of office activities using accelerometers

Seung Hyun Cha, Joonoh Seo, Seung Hyo Baek, Choongwan Koo

Research output: Contribution to journalArticle

4 Scopus citations

Abstract

As work has come to require more dynamic and collaborative settings, activity-based work (ABW) environments have claimed increasing attention. However, without a clear understanding of office-workers’ activity patterns the rash adoption of ABW may entail a variety of adverse effects, such as work-station shortages and inappropriate work-station arrangements. In this regard, the automated recognition of office activities with an accelerometer can help architects to understand activity patterns, thereby enabling effective space planning for the ABW environment. To the best of our knowledge, however, static office tasks requiring mainly manual activities have not yet been recognized. The study thus aims to determine the feasibility of recognizing seven static and non-static office activities simultaneously using an accelerometer. An experimental investigation was carried out to collect acceleration data from the seven activities. The accuracy of five classifiers (i.e. k-Nearest Neighbor, Discriminant Analysis, Support Vector Machine, Decision Tree and Ensemble Classifier), was analyzed with different window sizes. The highest classification accuracy, at 96.1%, was achieved by Ensemble Classifier, with a window size of 4.0 s. In addition, all office activities showed recall and precision greater than 0.9, demonstrating high prediction reliability. These findings help architects to understand static and non-static office activity patterns more systematically and comprehensively.

Original languageEnglish
Pages (from-to)86-93
Number of pages8
JournalBuilding and Environment
Volume144
DOIs
Publication statusPublished - 2018 Oct 15

    Fingerprint

Keywords

  • Accelerometer
  • Action recognition
  • Activity-based working
  • New ways of working
  • Office design
  • Space planning

Cite this