Poster: Enhanced collaborative sensing scheme for user activity recognition

  • Authors:

  • Yuki Nishida;Yoshihiro Kawahara;Tohru Asami

  • Affiliations:

  • The University of Tokyo, Hongo, Bunkyo-ku, Tokyo, Japan;The University of Tokyo, Hongo, Bunkyo-ku, Tokyo, Japan and Georgia Institute of Technology, Atlanta, Georgia;The University of Tokyo, Hongo, Bunkyo-ku, Tokyo, Japan

  • Venue:
  • Proceedings of the 9th ACM Conference on Embedded Networked Sensor Systems
  • Year:
  • 2011

Quantified Score

Hi-index 0.00

Visualization

Abstract

Accelerometer data on a user's mobile phone contains abundant information that can be employed for user activity recognition. However, the existing schemes cannot provide accurate inference results under moving environments (e.g. on a train). This is because raw sensor data changes with the motion of the environment as well as the user. In this paper, we propose an enhanced collaborative recognition scheme that exploits neighborhood sensor data shared over a wireless network. Our preliminary experiment showed that the acceleration data of two different subjects on the same train was highly correlated. Further, it was possible to detect whether two subjects were on the same train with an accuracy of 69%. This result indicates that raw sensor data shared by spatially neighboring users can be used to detect transportation modes and enrich social networking applications.