Interruptibility prediction for ubiquitous systems: conventions and new directions from a growing field

Turner, Liam D. ORCID: https://orcid.org/0000-0003-4877-5289, Allen, Stuart Michael ORCID: https://orcid.org/0000-0003-1776-7489 and Whitaker, Roger Marcus ORCID: https://orcid.org/0000-0002-8473-1913 2015. Interruptibility prediction for ubiquitous systems: conventions and new directions from a growing field. Presented at: 2015 ACM International Joint Conference on Pervasive and Ubiquitous Computing, Osaka, Japan, 7-11 September 2015. Proceedings of the 2015 ACM International Joint Conference on Pervasive and Ubiquitous Computing. New York, USA: ACM, 10.1145/2750858.2807514

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Abstract

When should a machine attempt to communicate with a user? This is a historical problem that has been studied since the rise of personal computing. More recently, the emergence of pervasive technologies such as the smartphone have extended the problem to be ever-present in our daily lives, opening up new opportunities for context awareness through data collection and reasoning. Complementary to this there has been increasing interest in techniques to intelligently synchronise interruptions with human behaviour and cognition. However, it is increasingly challenging to categorise new developments, which are often scenario specific or scope a problem with particular unique features. In this paper we present a meta-analysis of this area, decomposing and comparing historical and recent works that seek to understand and predict how users will perceive and respond to interruptions. In doing so we identify research gaps, questions and opportunities that characterise this important emerging field for pervasive technology.

Item Type:	Conference or Workshop Item (Paper)
Date Type:	Publication
Status:	Published
Schools:	Computer Science & Informatics Systems Immunity Research Institute (SIURI)
Subjects:	Q Science > QA Mathematics > QA75 Electronic computers. Computer science
Uncontrolled Keywords:	Interruptibility; Ubiquitous computing; Context-aware computing; Meta-analysis
Publisher:	ACM
ISBN:	978-1-4503-3574-4
Date of First Compliant Deposit:	30 March 2016
Last Modified:	26 Jun 2024 01:13
URI:	https://orca.cardiff.ac.uk/id/eprint/75404

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