Attelia: Sensing user's attention status on smart phones

Tadashi Okoshi, Jin Nakazawa, Hideyuki Tokuda

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

17 Citations (Scopus)

Abstract

In progressing ubiquitous computing where number of devices, applications and the web services are everincreasing, human user's attention is a new bottleneck in computing. This paper proposes Attelia, a novel middleware that senses user's attention status on user'ssmart phones in real-time, without any dedicated psycho-physiological sensors. To find better delivery timings of interruptive notifications from various applications and services to mobile users, Attelia detects breakpoint[16] of user's activity on the smart phones, with our novel "Application as a Sensor"(AsaS) approach and machine learning technique. Our initial evaluation of Attelia shows it can detect breakpoints of users with accuracy of 80 - 90%.

Original languageEnglish
Title of host publicationUbiComp 2014 - Adjunct Proceedings of the 2014 ACM International Joint Conference on Pervasive and Ubiquitous Computing
PublisherAssociation for Computing Machinery, Inc
Pages139-142
Number of pages4
ISBN (Electronic)9781450330473
DOIs
Publication statusPublished - 2014
Event2014 ACM International Joint Conference on Pervasive and Ubiquitous Computing, UbiComp 2014 - Seattle, United States
Duration: 2014 Sep 132014 Sep 17

Publication series

NameUbiComp 2014 - Adjunct Proceedings of the 2014 ACM International Joint Conference on Pervasive and Ubiquitous Computing

Other

Other2014 ACM International Joint Conference on Pervasive and Ubiquitous Computing, UbiComp 2014
Country/TerritoryUnited States
CitySeattle
Period14/9/1314/9/17

Keywords

  • Interruption
  • Mobile sensing
  • Notification
  • Smart phones, machine learning
  • User attention

ASJC Scopus subject areas

  • Software

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