We propose a gesture recognition technique based on RFID: cheap and unintrusive passive RFID tags can be easily attached to or interweaved into user clothes, which are then read by RFID antennas. These readings can be used to recognize hand gestures, which enable interaction with applications in an RFID-enabled environment. For instance, it allows people to interact with large displays in public collaboration spaces without the need to carry a dedicated device. We propose the use of multiple hypothesis tracking and the use of subtag count information to track the motion patterns of passive RFID tags. To the best of our knowledge, this work is the first on motion pattern tracking using passive RFID tags. Despite the reading uncertainties inherent in passive RFID technology, our experiments show that the proposed gesture recognition technique has an accuracy of up to 93%.

Numerous studies have tracked people's everyday use of digital devices, but without consideration of how such data might be of personal interest to the user. We have developed a personal tracking application that enables users to automatically monitor their 'screen time' on mobile devices (iOS and Android) and computers (Mac and Windows). The application interface enables users to combine screen time data from multiple devices. We trialled the application for 28+ days with 21 users, collecting log data and interviewing each user. We found that there is interest in personal tracking in this area, but that the study participants were less interested in quantifying their overall screen time than in gaining data about their use of specific devices and applications. We found that personal tracking of device use is desirable for goals including: increasing productivity, disciplining device use, and cutting down on use.

Grid is an infrastructure that involves the integrated and collaborative use of computers, networks, databases and scientific instruments owned and managed by multiple organizations. Grid applications often involve large amounts of data and/or computing resources that require secure resource sharing across organizational boundaries. This makes Grid application management and deployment a complex undertaking. Grid middlewares provide users with seamless computing ability and uniform access to resources in the heterogeneous Grid environment. Several software toolkits and systems have been developed, most of which are results of academic research projects, all over the world. This chapter will focus on four of these middlewares-UNICORE, Globus, Legion and Gridbus. It also presents our implementation of a resource broker for UNICORE as this functionality was not supported in it. A comparison of these systems on the basis of the architecture, implementation model and several other features is included.

This paper discusses the ethical dimensions of a research project in which we deployed a personal tracking app on the Apple App Store and collected data from users with whom we had little or no direct contact. We describe the in-app functionality we created for supporting consent and withdrawal, our approach to privacy, our navigation of a formal ethical review, and navigation of the Apple approval process. We highlight two key issues for deployment-based research. Firstly, that it involves addressing multiple, sometimes conflicting ethical principles and guidelines. Secondly, that research ethics are not readily separable from design, but the two are enmeshed. As such, we argue that in-action and situational perspectives on research ethics are relevant to deployment-based research, even where the technology is relatively mundane. We also argue that it is desirable to produce and share relevant design knowledge and embed in-action and situational approaches in design activities.

Abstract. A large range of monitoring applications can benefit from binary sensor networks. Binary sensors can detect the presence or absence of a particular target in their sensing regions. They can be used to partition a monitored area and provide localization functionality. If many of these sensors are deployed to monitor an area, the area is partitioned into sub-regions: each sub-regions is characterized by the sensors detecting targets within it. We aim to maximize the number of unique, distinguishable sub-regions. Our goal is an optimal placement of both omni-directional and directional static binary sensors. We compute an upper bound on the number of unique sub-regions, which grows quadratically with respect to the number of sensors. In particular, we propose arrangements of sensors within a monitored area whose number of unique sub-regions is asymptotically equivalent to the upper bound.

Mobile behaviour change applications should be evaluated for their effectiveness in promoting the intended behavior changes. In this paper we argue that the "gold standard" form of effectiveness evaluation, the randomised controlled trial, has shortcomings when applied to mobile applications. We propose that N-of-1 (also known as single case design) based approaches have advantages. There is currently a lack of guidance for researchers and developers on how to take this approach. We present a framework encompassing three phases and two related checklists for performing N-of-1 evaluations. We also present our analysis of using this framework in the development and deployment of an app that encourages people to walk more. Our key findings are that there are challenges in designing engaging apps that automate N-of-1 procedures, and that there are challenges in collecting sufficient data of good quality. Further research should address these challenges.

Many men stop exercising as they age, engage in risky behaviours such as alcohol misuse, are reluctant to admit to mental health problems, and avoid seeking help. Men are generally hard to reach for community health interventions. However, interventions run at football clubs have successfully engaged men and have led to positive health outcomes. Mobile health technology might similarly be designed to engage and encourage men via connections with football. This technology could be used to augment and extend community programs, or be used to target global fan bases. However, it is not clear if and how what attracts men to community interventions can translate to technology. In this paper we report a design study with 18 middle-age male participants exploring what men find important in football, and connections between football, health and technology. We present five design opportunities to guide and prompt further innovation in this area.

Mobile application usage data has been investigated by many researchers to explore reasoning about users' contexts and their routines. A large number of early studies in this area provide relatively simple analyses, and some more recent works look more deeply at the patterns of logged events. This paper explains a new work on the analysis of interaction logs collected from a pedometer-based mobile app to extract different usage patterns of the app.