94,587 research outputs found

    Furniture models learned from the WWW: using web catalogs to locate and categorize unknown furniture pieces in 3D laser scans

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    In this article, we investigate how autonomous robots can exploit the high quality information already available from the WWW concerning 3-D models of office furniture. Apart from the hobbyist effort in Google 3-D Warehouse, many companies providing office furnishings already have the models for considerable portions of the objects found in our workplaces and homes. In particular, we present an approach that allows a robot to learn generic models of typical office furniture using examples found in the Web. These generic models are then used by the robot to locate and categorize unknown furniture in real indoor environments

    Social Intelligence Design in Ambient Intelligence

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    This Special Issue of AI and Society contains a selection of papers presented at the 6th Social Intelligence Design Workshop held at ITC-irst, Povo (Trento, Italy) in July 2007. Being the 6th in a series means that there now is a well-established and also a growing research area. The interest in this research area is growing because, among other things, current computing technology allows other than the traditional efficiency-oriented applications associated with computer science and interface technology. For example, in Ambient Intelligence (AmI) applications we look at sensor-equipped environments and devices (robots, smart furniture, virtual humans and pets) that support their human inhabitants during their everyday activities. These everyday activities also include computer-mediated communication, collaboration and community activities

    A conceptual approach to determine optimal indoor air quality: A mixture experiment method

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    Achieving good air quality in large residential and commercial buildings continues to be a top priority for owners, designers, building managers and occupants. The challenge is even greater today. There are many new materials, furnishing, products and processes used in these buildings that are potential source of contaminations and pollutants. A common problem to the indoor and outdoor environments is that of exposure to mixtures of air pollutants. Researchers and practitioners tend to focus on single pollutants (e.g. CO2, PM2.5) ignoring the mixtures combined effect. Fashion dictates to study the pollutant most thoroughly talked about. Distinguishing the effects of such co-pollutants is difficult. The conclusions about which component of a mixture is actually producing a given effect are sometimes less soundly based than could be wished. It is especially important in considering the indoor mixture of air pollutants as this mixture may be entirely different from those found outside. Exposures to raised levels of air pollutants can damage health, for example carbon monoxide can cause death and significant lasting disability. Controlling levels of indoor air pollutants is therefore important, as good indoor air quality is essential to health. There are three strategies for achieving acceptable indoor air quality: ventilation, source control and cleaning/filtration. Depending on the building and the specific characteristics of the location, these strategies can be used singly or in combination. However, mixture experiment would throw more light and understanding into indoor air composition and interaction properties and the combine effects it has on human health. Mixture experiments have been used extensively in other industries, for example the pharmaceutical industry and the agrochemical industry, for the production of tablets and the control of plant diseases and pests. Developing a mixture model for the internal microclimate for a particular building type and/or location may help us in developing better indicators, standards and policy document in the near future, when the levels of pollutants concentration can be successfully predicted

    “No powers, man!”: A student perspective on designing university smart building interactions

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    Smart buildings offer an opportunity for better performance and enhanced experience by contextualising services and interactions to the needs and practices of occupants. Yet, this vision is limited by established approaches to building management, delivered top-down through professional facilities management teams, opening up an interaction-gap between occupants and the spaces they inhabit. To address the challenge of how smart buildings might be more inclusively managed, we present the results of a qualitative study with student occupants of a smart building, with design workshops including building walks and speculative futuring. We develop new understandings of how student occupants conceptualise and evaluate spaces as they experience them, and of how building management practices might evolve with new sociotechnical systems that better leverage occupant agency. Our findings point to important directions for HCI research in this nascent area, including the need for HBI (Human-Building Interaction) design to challenge entrenched roles in building management

    Interoperability and Standards: The Way for Innovative Design in Networked Working Environments

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    Organised by: Cranfield UniversityIn today’s networked economy, strategic business partnerships and outsourcing has become the dominant paradigm where companies focus on core competencies and skills, as creative design, manufacturing, or selling. However, achieving seamless interoperability is an ongoing challenge these networks are facing, due to their distributed and heterogeneous nature. Part of the solution relies on adoption of standards for design and product data representation, but for sectors predominantly characterized by SMEs, such as the furniture sector, implementations need to be tailored to reduce costs. This paper recommends a set of best practices for the fast adoption of the ISO funStep standard modules and presents a framework that enables the usage of visualization data as a way to reduce costs in manufacturing and electronic catalogue design.Mori Seiki – The Machine Tool Compan
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