39,277 research outputs found
Extending a mobile device's interaction space through body-centric interaction
Modern mobile devices rely on the screen as a primary input modality. Yet the small screen real-estate limits interaction possibilities, motivating researchers to explore alternate input techniques. Within this arena, our goal is to develop Body-Centric Interaction with Mobile Devices: a class of input techniques that allow a person to position and orient her mobile device to navigate and manipulate digital content anchored in the space on and around the body. To achieve this goal, we explore such interaction in a bottomup path of prototypes and implementations. From our experiences, as well as by examining related work, we discuss and present three recurring themes that characterize how these interactions can be realized. We illustrate how these themes can inform the design of Body-Centric Interactions by applying them to the design of a novel mobile browser application. Overall, we contribute a class of mobile input techniques where interactions are extended beyond the small screen, and are instead driven by a person's movement of the device on and around the body. Copyright 2012 ACM
Beyond representations: towards an action-centric perspective on tangible interaction
In the light of theoretical as well as concrete technical development, we discuss a conceptual shift from an information-centric to an action-centric perspective on tangible interactive technology. We explicitly emphasise the qualities of shareable use, and the importance of designing tangibles that allow for meaningful manipulation and control of the digital material. This involves a broadened focus from studying properties of the interface, to instead aim for qualities of the activity of using a system, a general tendency towards designing for social and sharable use settings and an increased openness towards multiple and subjective interpretations. An effect of this is that tangibles are not designed as representations of data, but as resources for action. We discuss four ways that tangible artefacts work as resources for action: (1) for physical manipulation; (2) for referential, social and contextually oriented action; (3) for perception and sensory experience; (4) for digitally mediated action
A Role-Based Approach for Orchestrating Emergent Configurations in the Internet of Things
The Internet of Things (IoT) is envisioned as a global network of connected
things enabling ubiquitous machine-to-machine (M2M) communication. With
estimations of billions of sensors and devices to be connected in the coming
years, the IoT has been advocated as having a great potential to impact the way
we live, but also how we work. However, the connectivity aspect in itself only
accounts for the underlying M2M infrastructure. In order to properly support
engineering IoT systems and applications, it is key to orchestrate
heterogeneous 'things' in a seamless, adaptive and dynamic manner, such that
the system can exhibit a goal-directed behaviour and take appropriate actions.
Yet, this form of interaction between things needs to take a user-centric
approach and by no means elude the users' requirements. To this end,
contextualisation is an important feature of the system, allowing it to infer
user activities and prompt the user with relevant information and interactions
even in the absence of intentional commands. In this work we propose a
role-based model for emergent configurations of connected systems as a means to
model, manage, and reason about IoT systems including the user's interaction
with them. We put a special focus on integrating the user perspective in order
to guide the emergent configurations such that systems goals are aligned with
the users' intentions. We discuss related scientific and technical challenges
and provide several uses cases outlining the concept of emergent
configurations.Comment: In Proceedings of the Second International Workshop on the Internet
of Agents @AAMAS201
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A classification of emerging and traditional grid systems
The grid has evolved in numerous distinct phases. It started in the early â90s as a model of metacomputing in which supercomputers share resources; subsequently, researchers added the ability to share data. This is usually referred to as the first-generation grid. By the late â90s, researchers had outlined the framework for second-generation grids, characterized by their use of grid middleware systems to âglueâ different grid technologies together. Third-generation grids originated in the early millennium when Web technology was combined with second-generation grids. As a result, the invisible grid, in which grid complexity is fully hidden through resource virtualization, started receiving attention. Subsequently, grid researchers identified the requirement for semantically rich knowledge grids, in which middleware technologies are more intelligent and autonomic. Recently, the necessity for grids to support and extend the ambient intelligence vision has emerged. In AmI, humans are surrounded by computing technologies that are unobtrusively embedded in their surroundings.
However, third-generation gridsâ current architecture doesnât meet the requirements of next-generation grids (NGG) and service-oriented knowledge utility (SOKU).4 A few years ago, a group of independent experts, arranged by the European Commission, identified these shortcomings as a way to identify potential European grid research priorities for 2010 and beyond. The experts envision grid systemsâ information, knowledge, and processing capabilities as a set of utility services.3 Consequently, new grid systems are emerging to materialize these visions. Here, we review emerging grids and classify them to motivate further research and help establish a solid foundation in this rapidly evolving area
Fall Prediction and Prevention Systems: Recent Trends, Challenges, and Future Research Directions.
Fall prediction is a multifaceted problem that involves complex interactions between physiological, behavioral, and environmental factors. Existing fall detection and prediction systems mainly focus on physiological factors such as gait, vision, and cognition, and do not address the multifactorial nature of falls. In addition, these systems lack efficient user interfaces and feedback for preventing future falls. Recent advances in internet of things (IoT) and mobile technologies offer ample opportunities for integrating contextual information about patient behavior and environment along with physiological health data for predicting falls. This article reviews the state-of-the-art in fall detection and prediction systems. It also describes the challenges, limitations, and future directions in the design and implementation of effective fall prediction and prevention systems
Device-Centric Monitoring for Mobile Device Management
The ubiquity of computing devices has led to an increased need to ensure not
only that the applications deployed on them are correct with respect to their
specifications, but also that the devices are used in an appropriate manner,
especially in situations where the device is provided by a party other than the
actual user. Much work which has been done on runtime verification for mobile
devices and operating systems is mostly application-centric, resulting in
global, device-centric properties (e.g. the user may not send more than 100
messages per day across all applications) being difficult or impossible to
verify. In this paper we present a device-centric approach to runtime verify
the device behaviour against a device policy with the different applications
acting as independent components contributing to the overall behaviour of the
device. We also present an implementation for Android devices, and evaluate it
on a number of device-centric policies, reporting the empirical results
obtained.Comment: In Proceedings FESCA 2016, arXiv:1603.0837
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