Details of Grant 

EPSRC Reference:	EP/M017133/1
Title:	IDInteraction: Capturing Indicative Usage Models in Software for Implicit Device Interaction
Principal Investigator:	Jay, Dr C
Other Investigators:
Researcher Co-Investigators:
Project Partners:	BBC
Department:	Computer Science
Organisation:	University of Manchester, The
Scheme:	First Grant - Revised 2009
Starts:	01 April 2015	Ends:	15 August 2016	Value (£):	100,299
EPSRC Research Topic Classifications:	Human-Computer Interactions
EPSRC Industrial Sector Classifications:	Creative Industries
Related Grants:
Panel History:	Panel Date Panel Name Outcome 02 Dec 2014 EPSRC ICT Prioritisation Panel - Dec 2014 Announced
Summary on Grant Application Form
The IDInteraction project asks: can we exploit models of human behaviour to move away from direct, unambiguous user commands, towards seamless user-device interaction? It will investigate and develop the techniques to capture 'Indicative Usage Models (IUMs), behavioural patterns or cues that precede a particular activity, and translate these into software-based 'Indicative Usage Patterns' (IUPs), to drive interaction with an app. The project will focus on future television broadcasting, examining the extent to which it is possible to capture IUMs from device sensor and event data, and deploy these as IUPs to pull content (additional information or related activities) to a 'second screen companion app', which a viewer watches on a mobile device alongside a TV programme. The core of the research - investigating the extent to which we can anticipate user commands and requests - will play an important role in shaping the way we use future technology. The Internet of Things is fast becoming a reality, but the appropriate paradigms for interacting with it are far from understood. A rapidly growing number of connected devices means a potentially vast increase in the types of technology which people must use successfully. Whilst a person may be prepared to learn how to use a new home automation system or car, expecting him or her to do this for every machine with which there is a cursory encounter is unrealistic. We have already started to understand that interactive experiences which take fundamental human perception and thought processes into account are more successful than those which require significant learning on the part of the user. Implicit Device Interaction, where devices automatically know what the user wants, before a command is issued, is the next step. The scenario investigated - second screen viewing - is also particularly timely. Broadcasters are keen to exploit the creative potential of a context where people are watching television with a mobile device, not least because it is set to become the principle form of TV viewing in the next few years. At present, however, the scenario is not well understood: whilst some research has focused on social aspects of this situation, very little has examined the perceptual or behavioural aspects of second screen interaction. Current companion apps, designed to complement the main programme, push information to the mobile device at given points in time, and this change on the secondary screen, which occurs in peripheral vision, is potentially distracting. A situation where information flow intuitively stops and starts according to the location of the viewer's attention is a highly desirable goal. IDInteraction is an ambitious research project, investigating an aspect of human behaviour that is crucial to the future development of implicit user interfaces, and has been planned to tackle the problem from end-to-end. By studying a slice of the research problem, from modelling behaviour to testing a new user interface, it will provide an overview of the theoretical and technical challenges that the development of seamless user-device interaction will entail, and flag key areas for further investigation. From the perspective of effective software development, the project entails a considerable degree of risk: IUMs may be difficult to capture and deploy, and seamless information provision may be challenging to implement in this context. From the perspective of building theory in this area, such results would still have significant value, however. Improving our understanding of the limits of implicit interaction is crucial to moving this important, emergent, field forward.
Key Findings
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Potential use in non-academic contexts
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Further Information:
Organisation Website:	http://www.man.ac.uk