5,376 research outputs found

    Reflections on the use of Project Wonderland as a mixed-reality environment for teaching and learning

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    This paper reflects on the lessons learnt from MiRTLE?a collaborative research project to create a ?mixed reality teaching and learning environment? that enables teachers and students participating in real-time mixed and online classes to interact with avatar representations of each other. The key hypothesis of the project is that avatar representations of teachers and students can help create a sense of shared presence, engendering a greater sense of community and improving student engagement in online lessons. This paper explores the technology that underpins such environments by presenting work on the use of a massively multi-user game server, based on Sun?s Project Darkstar and Project Wonderland tools, to create a shared teaching environment, illustrating the process by describing the creation of a virtual classroom. It is planned that the MiRTLE platform will be used in several trial applications ? which are described in the paper. These example applications are then used to explore some of the research issues arising from the use of virtual environments within an education environment. The research discussion initially focuses on the plans to assess this within the MiRTLE project. This includes some of the issues of designing virtual environments for teaching and learning, and how supporting pedagogical and social theories can inform this process

    Preliminary Efforts Directed Toward the Detection of Craving of Illicit Substances: The iHeal Project

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    Many behavioral interventions, whether for the management of chronic pain, overeating, medication adherence, or substance abuse, are ineffective outside of the clinic or office environments in which they are taught. This lack of utility has spawned interest in enabling technologies that are capable of detecting changes in affective state that potentially herald a transition to risky behaviors. We have therefore undertaken the preliminary development of “iHeal”, an innovative constellation of technologies that incorporates artificial intelligence, continuous biophysical monitoring, wireless connectivity, and smartphone computation. In its fully realized form, iHeal can detect developing drug cravings; as a multimedia device, it can also intervene as the cravings develop to prevent drug use. This manuscript describes preliminary data related to the iHeal Project and our experience with its use.United States. American Recovery and Reinvestment Act of 2009National Institutes of Health (U.S.

    Interoperable services based on activity monitoring in ambient assisted living environments

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    Ambient Assisted Living (AAL) is considered as the main technological solution that will enable the aged and people in recovery to maintain their independence and a consequent high quality of life for a longer period of time than would otherwise be the case. This goal is achieved by monitoring human’s activities and deploying the appropriate collection of services to set environmental features and satisfy user preferences in a given context. However, both human monitoring and services deployment are particularly hard to accomplish due to the uncertainty and ambiguity characterising human actions, and heterogeneity of hardware devices composed in an AAL system. This research addresses both the aforementioned challenges by introducing 1) an innovative system, based on Self Organising Feature Map (SOFM), for automatically classifying the resting location of a moving object in an indoor environment and 2) a strategy able to generate context-aware based Fuzzy Markup Language (FML) services in order to maximize the users’ comfort and hardware interoperability level. The overall system runs on a distributed embedded platform with a specialised ceiling- mounted video sensor for intelligent activity monitoring. The system has the ability to learn resting locations, to measure overall activity levels, to detect specific events such as potential falls and to deploy the right sequence of fuzzy services modelled through FML for supporting people in that particular context. Experimental results show less than 20% classification error in monitoring human activities and providing the right set of services, showing the robustness of our approach over others in literature with minimal power consumption

    On the Integration of Adaptive and Interactive Robotic Smart Spaces

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    © 2015 Mauro Dragone et al.. This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 3.0 License. (CC BY-NC-ND 3.0)Enabling robots to seamlessly operate as part of smart spaces is an important and extended challenge for robotics R&D and a key enabler for a range of advanced robotic applications, such as AmbientAssisted Living (AAL) and home automation. The integration of these technologies is currently being pursued from two largely distinct view-points: On the one hand, people-centred initiatives focus on improving the user’s acceptance by tackling human-robot interaction (HRI) issues, often adopting a social robotic approach, and by giving to the designer and - in a limited degree – to the final user(s), control on personalization and product customisation features. On the other hand, technologically-driven initiatives are building impersonal but intelligent systems that are able to pro-actively and autonomously adapt their operations to fit changing requirements and evolving users’ needs,but which largely ignore and do not leverage human-robot interaction and may thus lead to poor user experience and user acceptance. In order to inform the development of a new generation of smart robotic spaces, this paper analyses and compares different research strands with a view to proposing possible integrated solutions with both advanced HRI and online adaptation capabilities.Peer reviewe

    Adaptive Architecture:Regulating human building interaction

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    In this paper, we explore the regulatory, technical and interactional implications of Adaptive Architecture (AA) and how it will recalibrate the nature of human-building interaction. We comprehensively unpack the emergence and history of this novel concept, reflecting on the current state of the art and policy foundations supporting it. As AA is underpinned by the Internet of Things (IoT), we consider how regulatory and surveillance issues posed by the IoT are manifesting in the built environment. In our analysis, we utilise a prominent architectural model, Stuart Brand’s Shearing Layers, to understand temporal change and informational flows across different physical layers of a building. We use three AA applications to situate our analysis, namely a smart IoT security camera; an AA research prototype; and an AA commercial deployment. Focusing on emerging information privacy and security regulations, particularly the EU General Data Protection Regulation 2016, we examine AA from 5 perspectives: physical & information security risks; challenges of establishing responsibility; enabling occupant rights over flows, collection, use & control of personal data; addressing increased visibility of emotions and bodies; understanding surveillance of everyday routine activities. We conclude with key challenges for AA regulation and the future of human–building interaction

    Adaptive architecture: Regulating human building interaction

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    In this paper we explore regulatory, technical and interactional implications of Adaptive Architecture, a novel trend emerging in the built environment. We provide a comprehensive description of the emergence and history of the term, with reference to the current state of the art and policy foundations supporting it e.g. smart city initiatives and building regulations. As Adaptive Architecture is underpinned by the Internet of Things (IoT), we are interested in how regulatory and surveillance issues posed by the IoT manifest in buildings too. To support our analysis, we utilise a prominent concept from architecture, Stuart Brand’s Shearing Layers model, which describes the different physical layers of a building and how they relate to temporal change. To ground our analysis, we use three cases of Adaptive Architecture, namely an IoT device (Nest Smart Cam IQ); an Adaptive Architecture research prototype, (ExoBuilding); and a commercial deployment (the Edge). In bringing together Shearing Layers, Adaptive Architecture and the challenges therein, we frame our analysis under 5 key themes. These are guided by emerging information privacy and security regulations. We explore the issues Adaptive Architecture needs to face for: A – ‘Physical & information security’; B – ‘Establishing responsibility’; C – ‘occupant rights over flows, collection, use & control of personal data’; D- ‘Visibility of Emotions and Bodies’; & E – ‘Surveillance of Everyday Routine Activities’. We conclude by summarising key challenges for Adaptive Architecture, regulation and the future of human building interaction

    Human-centred design methods : developing scenarios for robot assisted play informed by user panels and field trials

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    Original article can be found at: http://www.sciencedirect.com/ Copyright ElsevierThis article describes the user-centred development of play scenarios for robot assisted play, as part of the multidisciplinary IROMEC1 project that develops a novel robotic toy for children with special needs. The project investigates how robotic toys can become social mediators, encouraging children with special needs to discover a range of play styles, from solitary to collaborative play (with peers, carers/teachers, parents, etc.). This article explains the developmental process of constructing relevant play scenarios for children with different special needs. Results are presented from consultation with panel of experts (therapists, teachers, parents) who advised on the play needs for the various target user groups and who helped investigate how robotic toys could be used as a play tool to assist in the children’s development. Examples from experimental investigations are provided which have informed the development of scenarios throughout the design process. We conclude by pointing out the potential benefit of this work to a variety of research projects and applications involving human–robot interactions.Peer reviewe
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