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Uniformization, organization, association and use of metadata from multiple content providers and manufacturers: A close look at the Building Automation System (BAS) sector

机译:来自多个内容提供商和制造商的统一化,组织,关联和使用元数据:仔细查看楼宇自动化系统(BAS)扇区

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The Internet of Things (IoT) is creating a renaissance in data analytics by connecting devices in a wide variety of industries, as well as in everyday life. However, data collected from these new and disparate sources are typically non-structured and non-uniform, which has become a significant barrier to developing scalable and repeatable analytics. The more than 5.6 million of commercial buildings in the United States of America are an illustration of this phenomena. Indeed, in the past decade, commercial, industrial, and government buildings have been outfitted with sensors and controllers, fully embracing the modern age. Successful application of analytics to systems controlling indoor building environment is providing an opportunity to realize substantial and widespread gains in energy efficiency and improved comfort as well as reductions in operating costs long after the building's commissioning. As such, Building Automation Systems (BASs), controlling heating, ventilation and air conditioning (HVAC) equipment, provide access to some level of information, often in the form of single and overlaid trends, meter data, and key performance indicators on a dashboard. The BAS, as well as analogous approaches, enables manual analysis by trained personnel, but it is cumbersome and cannot be easily scaled. In addition, the vast diversity of equipment, controllers, and configurations among buildings as well as the heterogeneity of components within single systems have further hindered traditional automated systematic analysis. In this work, a methodology for structuring and uniformizing data applied to building environment control systems is demonstrated. The result is a system that enables scalable and repeatable advanced analytics on a macro scale, abstracting the focus from a specific building and configuration, that is likely unique, to systems of multiple equipment that is generalizable to any building.
机译:物联网(IOT)是通过在各种各样的行业在日常生活中连接设备,以及创建在数据分析的复兴。然而,从这些新的和不同的源收集的数据通常是非结构化的和非均匀的,这已成为一个显著障碍开发可扩展和可重复的分析。超过560万在美国的美国商业楼宇的是这种现象的说明。事实上,在过去的十年里,商业,工业和政府大楼已经配备传感器和控制器,完全拥抱现代。分析来控制室内建筑环境系统的成功应用提供了建筑的调试后不久就意识到能源效率并提高舒适度以及运营成本大幅降低和普遍收益的机会。这样,楼宇自动化系统(低音),控制加热,通风和空调(HVAC)设备,提供访问的信息的一些级,通常在单个和重叠的趋势,计量表数据,并在仪表盘上的关键性能指标的形式。 BAS系统,以及类似的方法,使由专业人员手工分析,但它是累赘,不能很容易地扩展。此外,建筑物中的设备,控制器和配置的广阔多样性以及单系统内的部件的异质性进一步阻碍了传统的自动化系统的分析。在这项工作中,结构化和均匀化数据的方法适用于建筑环境控制系统的论证。其结果是一个系统,能够在宏观尺度上可扩展的和可重复的高级分析,提取从一个特定的建设和配置,这可能是唯一的,到多个设备的系统是普遍适用于任何建筑的焦点。

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