38,126 research outputs found

    From Sensor to Observation Web with Environmental Enablers in the Future Internet

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    This paper outlines the grand challenges in global sustainability research and the objectives of the FP7 Future Internet PPP program within the Digital Agenda for Europe. Large user communities are generating significant amounts of valuable environmental observations at local and regional scales using the devices and services of the Future Internet. These communities’ environmental observations represent a wealth of information which is currently hardly used or used only in isolation and therefore in need of integration with other information sources. Indeed, this very integration will lead to a paradigm shift from a mere Sensor Web to an Observation Web with semantically enriched content emanating from sensors, environmental simulations and citizens. The paper also describes the research challenges to realize the Observation Web and the associated environmental enablers for the Future Internet. Such an environmental enabler could for instance be an electronic sensing device, a web-service application, or even a social networking group affording or facilitating the capability of the Future Internet applications to consume, produce, and use environmental observations in cross-domain applications. The term ?envirofied? Future Internet is coined to describe this overall target that forms a cornerstone of work in the Environmental Usage Area within the Future Internet PPP program. Relevant trends described in the paper are the usage of ubiquitous sensors (anywhere), the provision and generation of information by citizens, and the convergence of real and virtual realities to convey understanding of environmental observations. The paper addresses the technical challenges in the Environmental Usage Area and the need for designing multi-style service oriented architecture. Key topics are the mapping of requirements to capabilities, providing scalability and robustness with implementing context aware information retrieval. Another essential research topic is handling data fusion and model based computation, and the related propagation of information uncertainty. Approaches to security, standardization and harmonization, all essential for sustainable solutions, are summarized from the perspective of the Environmental Usage Area. The paper concludes with an overview of emerging, high impact applications in the environmental areas concerning land ecosystems (biodiversity), air quality (atmospheric conditions) and water ecosystems (marine asset management)

    Continuous maintenance and the future – Foundations and technological challenges

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    High value and long life products require continuous maintenance throughout their life cycle to achieve required performance with optimum through-life cost. This paper presents foundations and technologies required to offer the maintenance service. Component and system level degradation science, assessment and modelling along with life cycle ‘big data’ analytics are the two most important knowledge and skill base required for the continuous maintenance. Advanced computing and visualisation technologies will improve efficiency of the maintenance and reduce through-life cost of the product. Future of continuous maintenance within the Industry 4.0 context also identifies the role of IoT, standards and cyber security

    Heterogeneous information integration for mountain augmented reality mobile apps

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    Mobile Augmented Reality (AR) applications offer a new way to promote the collection of geo-referenced information, by engaging citizens in a useful experience and encouraging them to gather environment data, such as images of plant species or of mountain snow coverage. The distinctive characteristic of mobile AR applications is the overlay of information directly on top of what the user sees, based on the user’s context estimated from the device sensors. The application analyzes the sensor readings (GPS position, phone orientation and motion, and possibly also the camera frame content), to understand what the user is watching and enriches the view with contextual information. Developing mobile AR applications poses several challenges related to the acquisition, selection, transmission and display of information, which gets more demanding in mountain applications where usage without Internet connectivity is a strong requirement. This paper discusses the experience of a real world mobile AR application for mountain exploration, which can be used to crowdsource the collection of mountain images for environmental purposes, such as the analysis of snow coverage for water availability prediction and the monitoring of plant diseases

    Studienlandschaft Schwingbachtal: an out-door full-scale learning tool newly equipped with augmented reality

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    This paper addresses education and communication in hydrology and geosciences. Many approaches can be used, such as the well-known seminars, modelling exercises and practical field work but out-door learning in our discipline is a must, and this paper focuses on the recent development of a new out-door learning tool at the landscape scale. To facilitate improved teaching and hands-on experience, we designed the Studienlandschaft Schwingbachtal. Equipped with field instrumentation, education trails, and geocache, we now implemented an augmented reality App, adding virtual teaching objects on the real landscape. The App development is detailed, to serve as methodology for people wishing to implement such a tool. The resulting application, namely the Schwingbachtal App, is described as an example. We conclude that such an App is useful for communication and education purposes, making learning pleasant, and offering personalized options

    Deep Thermal Imaging: Proximate Material Type Recognition in the Wild through Deep Learning of Spatial Surface Temperature Patterns

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    We introduce Deep Thermal Imaging, a new approach for close-range automatic recognition of materials to enhance the understanding of people and ubiquitous technologies of their proximal environment. Our approach uses a low-cost mobile thermal camera integrated into a smartphone to capture thermal textures. A deep neural network classifies these textures into material types. This approach works effectively without the need for ambient light sources or direct contact with materials. Furthermore, the use of a deep learning network removes the need to handcraft the set of features for different materials. We evaluated the performance of the system by training it to recognise 32 material types in both indoor and outdoor environments. Our approach produced recognition accuracies above 98% in 14,860 images of 15 indoor materials and above 89% in 26,584 images of 17 outdoor materials. We conclude by discussing its potentials for real-time use in HCI applications and future directions.Comment: Proceedings of the 2018 CHI Conference on Human Factors in Computing System

    MOSAIC vision and scenarios for mobile collaborative work related to health and wellbeing

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    The main objective of the MOSAIC project is to accelerate innovation in Mobile Worker Support Environments by shaping future research and innovation activities in Europe. The modus operandi of MOSAIC is to develop visions and illustrative scenarios for future collaborative workspaces involving mobile and location-aware working. Analysis of the scenarios is input to the process of road mapping with the purpose of developing strategies for R&D leading to deployment of innovative mobile work technologies and applications across different domains. This paper relates to one specific domain, that of Health and Wellbeing. The focus is therefore is on mobile working environments which enable mobile collaborative working related to the domain of healthcare and wellbeing services for citizens. This paper reports the work of MOSAIC T2.2 on the vision and scenarios for mobile collaborative work related to this domain. This work was also an input to the activity of developing the MOSAIC roadmap for future research and development targeted at realization of the future Health and Wellbeing vision. The MOSAIC validation process for the Health and Wellbeing scenarios is described and one scenario – the Major Incident Scenario - is presented in detail
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