Towards attention-aware adaptive notification on smart phones

Tadashi Okoshi, Hiroki Nozaki, Jin Nakazawa, Hideyuki Tokuda, Julian Ramos, Anind K. Dey

Research output: Contribution to journalArticle

23 Citations (Scopus)

Abstract

As the amount of information to users increases with the trends of an increasing numbers of devices, applications, and web services, the new bottleneck in computing is human attention. To minimize users attentional overload, we propose a novel middleware "Attelia" that detects breakpoints of user's mobile interactions to deliver notifications adaptively. Attelia detects such timings in real-time, using only users phones, without any external sensors, and without any modifications to applications. Our extensive evaluation proved Attelias effectiveness. In-the-wild user study with 30 participants for 16 days showed that, specifically for the users with greater sensitivity for interruptive notification timings, notification scheduling in Attelia's breakpoint timing reduced users frustration by 28% in users' real smart phone environments.

Original languageEnglish
Pages (from-to)17-34
Number of pages18
JournalPervasive and Mobile Computing
Volume26
DOIs
Publication statusPublished - 2016 Feb 1

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Middleware
Web services
Scheduling
Timing
Sensors
Frustration
User Studies
Overload
Web Services
Real-time
Minimise
Sensor
Computing
Evaluation
Interaction

Keywords

  • Attention-awareness
  • Interruptibility
  • Middleware
  • Mobile sensing
  • Notification

ASJC Scopus subject areas

  • Computer Science (miscellaneous)
  • Applied Mathematics

Cite this

Towards attention-aware adaptive notification on smart phones. / Okoshi, Tadashi; Nozaki, Hiroki; Nakazawa, Jin; Tokuda, Hideyuki; Ramos, Julian; Dey, Anind K.

In: Pervasive and Mobile Computing, Vol. 26, 01.02.2016, p. 17-34.

Research output: Contribution to journalArticle

Okoshi, Tadashi ; Nozaki, Hiroki ; Nakazawa, Jin ; Tokuda, Hideyuki ; Ramos, Julian ; Dey, Anind K. / Towards attention-aware adaptive notification on smart phones. In: Pervasive and Mobile Computing. 2016 ; Vol. 26. pp. 17-34.
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