452 research outputs found

    Internet of things

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    Manual of Digital Earth / Editors: Huadong Guo, Michael F. Goodchild, Alessandro Annoni .- Springer, 2020 .- ISBN: 978-981-32-9915-3Digital Earth was born with the aim of replicating the real world within the digital world. Many efforts have been made to observe and sense the Earth, both from space (remote sensing) and by using in situ sensors. Focusing on the latter, advances in Digital Earth have established vital bridges to exploit these sensors and their networks by taking location as a key element. The current era of connectivity envisions that everything is connected to everything. The concept of the Internet of Things(IoT)emergedasaholisticproposaltoenableanecosystemofvaried,heterogeneous networked objects and devices to speak to and interact with each other. To make the IoT ecosystem a reality, it is necessary to understand the electronic components, communication protocols, real-time analysis techniques, and the location of the objects and devices. The IoT ecosystem and the Digital Earth (DE) jointly form interrelated infrastructures for addressing today’s pressing issues and complex challenges. In this chapter, we explore the synergies and frictions in establishing an efficient and permanent collaboration between the two infrastructures, in order to adequately address multidisciplinary and increasingly complex real-world problems. Although there are still some pending issues, the identified synergies generate optimism for a true collaboration between the Internet of Things and the Digital Earth

    Geospatial information infrastructures to address spatial needs in health: Collaboration, challenges and opportunities

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    Most health-related issues such as public health outbreaks and epidemiological threats are better understood from a spatial–temporal perspective and, clearly demand related geospatial datasets and services so that decision makers may jointly make informed decisions and coordinate response plans. Although current health applications support a kind of geospatial features, these are still disconnected from the wide range of geospatial services and datasets that geospatial information infrastructures may bring into health. In this paper we are questioning the hypothesis whether geospatial information infrastructures, in terms of standards-based geospatial services, technologies, and data models as operational assets already in place, can be exploited by health applications for which the geospatial dimension is of great importance. This may be certainly addressed by defining better collaboration strategies to uncover and promote geospatial assets to the health community. We discuss the value of collaboration, as well as the opportunities that geographic information infrastructures offer to address geospatial challenges in health applications

    Enhancing integrated environmental modelling by designing resource-oriented interfaces

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    Integrated environmental modelling is gaining momentum for addressing grand scientific challenges such as monitoring the environment for change detection and forecasting environmental conditions along with the consequences for society. Such challenges can only be addressed by a multi-disciplinary approach, in which socio-economic, geospatial, and environmental information becomes inter-connected. However, existing solutions cannot be seamlessly integrated and current interaction paradigms prevent mainstream usage of the existing technology. In particular, it is still difficult to access and join harmonized data and processing algorithms that are provided by different environmental information infrastructures. In this paper we take a novel approach for integrated environmental modelling based on the notion of inter-linked resources on the Web. We present design practices for creating resource-oriented interfaces, driven by an interaction protocol built on the combination of valid linkages to enhance resource integration, accompanied by associated recommendations for implementation. The suggested resource-oriented approach provides a solution to the problems identified above, but still requires intense prototyping and experimentation. We discuss the central open issues and present a roadmap for future research
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