An individual data extraction model for objects used by a number of people

Hitoshi Kawasaki, Ren Ohmura, Hirotaka Osawa, Michita Imai

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

This study investigates people's use of objects and the things they do in their daily lives. This is because interaction with objects can give us valuable insights with regard to behavior. The problem is that in an environment where multiple users interact with the same object, it is difficult to obtain data relating to each individual. To this end, we propose a model that extracts individual data from a data set. We can recognize individual users in environments where multiple users interact with an object. The model consists of 3 policies. As a result of our experiment, we proved that the system could extract individual data that fits an individual examinee's consciousness an average of 85.3% of the time. In addition, by letting each examinee look back on the system results, we could make the examinee conscious of behavior of which they had previously been unaware.

Original languageEnglish
Title of host publication2009 4th International Symposium on Wireless and Pervasive Computing, ISWPC 2009
DOIs
Publication statusPublished - 2009 Apr 27
Event2009 4th International Symposium on Wireless and Pervasive Computing, ISWPC 2009 - Melbourne, VIC, Australia
Duration: 2009 Feb 112009 Feb 13

Publication series

Name2009 4th International Symposium on Wireless and Pervasive Computing, ISWPC 2009

Other

Other2009 4th International Symposium on Wireless and Pervasive Computing, ISWPC 2009
CountryAustralia
CityMelbourne, VIC
Period09/2/1109/2/13

Keywords

  • Activity recognition
  • Context-awareness
  • Individualization
  • Pervasive application

ASJC Scopus subject areas

  • Computer Networks and Communications
  • Computer Science Applications
  • Software

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