Activity Recognition and Crowd Sensing

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As humans, we are always engaged in activity and it has been considered to be one of the most important ingredients of context awareness and ubiquitous computing. At the lab we pursue the goal of capturing the activity of individuals, groups and crowds on a city scale.

Group members

Former members

  • Dr. Kilian Förster
  • Dr. Daniel Roggen
  • Dr. Mirco Rossi
  • Dr. Martin Wirz
  • Dr. Michael Hardegger
  • Catherine Ikae
  • Dr. Sinziana Mazilu
  • Dr. Julia Seiter
  • Dr. Amir Muaremi
  • Dr. Zack Zhu
  • Dr. Long-Van Nguyen-Dinh

Sensing the Activities of Individuals

  • ActionSLAM (infrastructure-free indoor location tracking)
  • Topic models for activity routine discovery
  • Activity recognition with noisy crowdsourced annotation
  • Less supervision in activity recognition
  • Ambient sensing in activity recognition and semantic location awareness

Sensing Urban Behaviour

  • Urban activity recognition
  • Social media as a probe for activity
  • Collective behavior on city scale events
  • Crowd sourcing activity models

Research projects

Current projects

  • CuPiD
  • iCareNet
  • Smart-DAYs

Completed projects

  • Opportunity
  • Socionical
  • Sensei
  • e-Sense
  • Titan
  • WearIT@Work
  • Hajj Pilgrimage
  • Micro-level behavior and team performance
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