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Smart buildings and the human-machine cloud

机译:智能建筑与人机云

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The Human-Robot Cloud has previously been introduced as a framework for the creation of distributed, on-demand, reconfigurable human-machine cognitive systems[1]. These systems are made up of sensing, processing, and actuation components that are not limited to a specific type of application and potentially can be extended to multiple domains and may cover spatially smaller or larger areas. In this paper, we revisit the Human-Robot Cloud architecture and present its pilot deployment on the campus of NCSR Demokritos, a research institution in Greece. In particular, our concrete deployment aims to be demonstrated in three specific application scenarios; namely, Human-Aware Smart Buildings with Energy Optimization, Security and Surveillance, and Smart Tour Guide System. In this paper, we present in detail an example implementation of the Smart Buildings scenario: a real-world application with immediate benefits in energy optimization and energy savings. Environmentally sensitive issues, such as the ground-up development of energy efficient buildings or reducing the environmental impact of the existing infrastructure, has received much attention in the past. However, the traditionally offered solutions are central, non-transferable to other infrastructure, non-scalable and suffer from single points of failure. On the contrary, in this work, which is based on a specialization of the generic Human-Robot Cloud architecture, we attempt to move beyond the industrially available solutions to meet the requirements for scalable, reconfigurable and redistributable sensory, processing, and actuation units within buildings. A set of cameras, laser range finders, and other sensors, together with a number of processing and actuation elements, including face detection, expression recognition, and people trackers, are transformed to a prototypical reconfigurable distributed extended cognitive system, which can support multiple applications in the future.
机译:之前已经引入了人机云作为创建分布式,按需,可重新配置的人机认知系统的框架[1]。这些系统由传感,处理和致动组件组成,这些组件不限于特定类型的应用程序,并且可能会扩展到多个域,并且可能会覆盖空间上较小或较大的区域。在本文中,我们将重新研究人机云架构,并在希腊研究机构NCSR Demokritos的校园中介绍其试点部署。特别是,我们的具体部署旨在在以下三个特定的应用场景中进行演示:即具有能源优化,安全和监视功能的人性化智能建筑,以及智能导游系统。在本文中,我们详细介绍了智能建筑方案的示例实现:在能源优化和节能方面具有直接好处的实际应用。对环境敏感的问题,例如节能建筑的全面开发或减少现有基础设施对环境的影响,在过去已引起广泛关注。但是,传统上提供的解决方案是中央解决方案,不可转移到其他基础架构,不可扩展,并且遭受单点故障的困扰。相反,在这项基于通用人机云架构的专业化基础上的工作中,我们试图超越工业上可用的解决方案,以满足内部对可伸缩,可重新配置和可再分配的感官,处理和驱动单元的要求。建筑物。一组照相机,激光测距仪和其他传感器,以及包括面部检测,表情识别和人物跟踪器在内的许多处理和驱动元素,被转换为可支持多种应用的原型可重构分布式扩展认知系统将来。

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