This paper addresses rule conflicts within wireless sensor networks. The work is situated within psychiatric ambulatory assessment settings where patients are monitored in and around their homes. Detecting behaviours within these settings favours sensor networks, while scalability and resource concerns favour processing data on smart nodes incorporating rule engines. Such monitoring involves personalisation, thereby becoming important to program node rules on the fly. Since rules may originate from distinct sources and change over time, methods are required to maintain rule consistency. Drawing on lessons from Feature Interaction, the paper contributes novel approaches for detecting and resolving rule-conflict across sensor networks.

Journal Article Tailored Scenarios: A Low-Cost Online Method to Elicit Perceptions of Home Technologies Using Participant-Specific Contextual Information Get access Michael Brown, Michael Brown * 1Horizon Digital Economy Research, University of Nottingham, Nottingham, Nottinghamshire, UK2Human Factors Research Group, University of Nottingham, Nottingham, UK *Corresponding author: [email protected] Search for other works by this author on: Oxford Academic Google Scholar Tim Coughlan, Tim Coughlan 1Horizon Digital Economy Research, University of Nottingham, Nottingham, Nottinghamshire, UK3Computer Science, University of Nottingham, Nottingham, Nottinghamshire, UK Search for other works by this author on: Oxford Academic Google Scholar Jesse Blum, Jesse Blum 1Horizon Digital Economy Research, University of Nottingham, Nottingham, Nottinghamshire, UK Search for other works by this author on: Oxford Academic Google Scholar Glyn Lawson, Glyn Lawson 2Human Factors Research Group, University of Nottingham, Nottingham, UK Search for other works by this author on: Oxford Academic Google Scholar Robert Houghton, Robert Houghton 1Horizon Digital Economy Research, University of Nottingham, Nottingham, Nottinghamshire, UK2Human Factors Research Group, University of Nottingham, Nottingham, UK Search for other works by this author on: Oxford Academic Google Scholar Richard Mortier, Richard Mortier 1Horizon Digital Economy Research, University of Nottingham, Nottingham, Nottinghamshire, UK3Computer Science, University of Nottingham, Nottingham, Nottinghamshire, UK Search for other works by this author on: Oxford Academic Google Scholar Murray Goulden, Murray Goulden 1Horizon Digital Economy Research, University of Nottingham, Nottingham, Nottinghamshire, UK Search for other works by this author on: Oxford Academic Google Scholar Unna Arunachalam Unna Arunachalam 1Horizon Digital Economy Research, University of Nottingham, Nottingham, Nottinghamshire, UK Search for other works by this author on: Oxford Academic Google Scholar Interacting with Computers, Volume 27, Issue 1, January 2015, Pages 60–71, https://doi.org/10.1093/iwc/iwu028 Published: 25 July 2014 Article history Received: 02 January 2014 Revision received: 06 June 2014 Accepted: 19 June 2014 Published: 25 July 2014

Ubiquitous and pervasive computing techniques have been used to inform discourses around climate change and energy insecurity, traditionally through data capture and representation for scientists, policy makers and the public. Research into re-engaging the public with sustainability and climate change issues reveals the significance of emotional and personal engagement alongside locally meaningful, globally-relevant and data-informed climate messaging for the public. New ubiquitous and pervasive computing techniques are emerging to support the next generation of climate change stakeholders, including artists, community practitioners, educators and data hackers, to create scientific data responsive artworks and performances. Grounded in our experiences of community based artistic interventions, we explore the design and deployments of the Timestreams platform, demonstrating usages of ubiquitous and pervasive computing within these new forms of discourse around climate change and energy insecurity.

Mobile and environmental sensing technology can be used to assess human behaviour and mental health trajectories outside of laboratories and in ecologically-relevant settings. To achieve maximum benefit, the set of equipment and the monitoring patterns must be personalised to respect individual needs and fit into individual lifestyles. We have developed a sensor network infrastructure for mobile phones and homecare using a rule-oriented programming architecture to monitor the activity signatures of people with Bipolar Disorder (BD). We believe that the use of this rule-based paradigm within the network for a mental health setting to be a contribution of this work. We are evaluating the effectiveness of the technology in an ongoing technical trial with control participants as a precursor to studying the effectiveness of the system for use with people with BD. In this paper, we report the design and development of the monitoring system along with preliminary findings from the technical trial of the system, and discuss future developments.