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A smart spaces architecture based on heterogeneous contexts, particularly social contexts

机译:基于异构上下文(尤其是社交上下文)的智能空间架构

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Advances in smart technologies, wireless networking, and the increased interest in services have led to the emergence of ubiquitous and pervasive computing as one of the most promising areas of computing in recent years. Researchers have become specifically interested in smart spaces and the significant improvements it can introduce to our lives. Most smart spaces rely on physical components such as sensors to sense and acquire information about the real world environment and surroundings. Although sensor networks can provide useful contextual information, they are known for their high degree of unreliability and limited resources. We believe that it is necessary to augment physical sensors with other kinds of data to create more reliable and truly context-aware smart spaces. In this paper we therefore utilize mobile devices and social networks to acquire more detailed and useful contextual information that can help create smarter spaces. We then propose a smart spaces architecture that utilizes these new contexts and in particular the social context.
机译:随着智能技术,无线网络的发展以及对服务的日益增长的兴趣,无处不在的无处不在的计算技术已成为近年来最有希望的计算领域之一。研究人员对智能空间及其可以为我们的生活带来的重大改进特别感兴趣。大多数智能空间都依赖于传感器等物理组件来感测和获取有关真实世界环境和周围环境的信息。尽管传感器网络可以提供有用的上下文信息,但它们以高度的不可靠性和有限的资源而闻名。我们认为,有必要使用其他类型的数据来扩展物理传感器,以创建更可靠,更真实的上下文感知智能空间。因此,在本文中,我们利用移动设备和社交网络来获取更详细和有用的上下文信息,以帮助创建更智能的空间。然后,我们提出一种利用这些新环境,尤其是社会环境的智能空间架构。

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