Energon: A Data Acquisition System for Portable Building Analytics
Energon: A Data Acquisition System for Portable Building Analytics
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DOI：
10.1145/3447555.3464850
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发表时间：
2021-06
期刊：
影响因子：
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通讯作者：
Fang He;Yang Deng;Yanhui Xu;Cheng Xu;Dezhi Hong;Dan Wang
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文献类型：
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作者：
Fang He;Yang Deng;Yanhui Xu;Cheng Xu;Dezhi Hong;Dan Wang
新兴的建筑分析依赖于数据驱动的机器学习算法。然而，编写这些分析仍然具有挑战性-开发人员不仅需要知道分析需要什么数据，而且还需要知道如何在每个建筑中获取数据，尽管现有的解决方案可以标准化建筑中的数据和资源管理。为了弥合分析开发与获取每栋建筑实际数据的具体细节之间的差距，我们推出了Energon，这是一个开源系统，可以实现便携式建筑分析。Energon的核心是建筑数据的新数据组织，以及可以有效管理建筑数据和支持建筑分析开发的工具。更具体地说，我们提出了一个新的“逻辑分区”的数据资源的建筑物，这种抽象普遍适用于所有的建筑物。我们开发了一种声明式查询语言，在这种新的逻辑视图中查找数据资源，并进行高级查询，从而大大减少了开发工作量。我们还开发了一个查询引擎，通过遍历广泛存在于建筑物中的建筑本体自动提取数据。通过这种方式，Energon能够以与建筑物无关的方式将分析需求映射到建筑物资源。使用四种类型的现实世界的建筑分析，我们展示了能源的使用，以及它在减少开发工作的有效性。
Emerging building analytics rely on data-driven machine learning algorithms. However, writing these analytics is still challenging---developers not only need to know what data are required by the analytics but also how to reach the data in each individual building, despite the existing solutions to standardizing data and resource management in buildings. To bridge the gap between analytics development and the specific details of reaching the actual data in each building, we present Energon, an open-source system that enables portable building analytics. The core of Energon is a new data organization of building data, as well as the tools that can effectively manage building data and support building analytics development. More specifically, we propose a new "logic partition" of data resources in buildings, and this abstraction universally applies to all buildings. We develop a declarative query language to find data resources in this new logic views with high-level queries, thus substantially reducing development efforts. We also develop a query engine with automatic data extraction by traversing building ontology that widely exists in buildings. In this way, Energon enables analytics requirements to be mapped to building resources in a building-agnostic manner. Using four types of real-world building analytics, we demonstrate the use of Energon as well as its effectiveness in reducing development efforts.