Evaluation of Clustering and Time Series Features for Point Type Inference in Smart Building Retrofit
Evaluation of Clustering and Time Series Features for Point Type Inference in Smart Building Retrofit
复制标题
智能建筑改造中点类型推理的聚类和时间序列特征评估
DOI：
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发表时间：
2019
期刊：
影响因子：
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通讯作者：
H. Gunay
中科院分区：
文献类型：
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作者：
Zixiao Shi;G. Newsham;Long Chen;H. Gunay
楼宇自动化系统(BAS)的元数据推理是推动智能建筑技术广泛应用的一个日益重要的课题。元数据推理用于自动发现BAS内的语义，如标记传感器、发现控制变量关系等。聚类分析已被应用于许多先前的研究，通过自动或半自动的BAS点标记来实现更快的智能建筑改造。然而，以前使用聚类的研究只使用了两到五栋建筑的小数据集。这项研究在更广泛的范围内检验了这种方法的有效性，调查了40栋商业和机构建筑以及超过65,000个标记的BAS点。研究了具有不同特征空间和聚类算法的不同聚类策略。此外，本研究还比较了哪种时间序列特征和生成方法可以提高标注效率。这项研究的积极结果支持了将聚类应用于点型推理的有效性。结果表明，当来自BAS的现有原始元数据的描述性较差时，额外的时间序列特征具有互补的性质。
Metadata inference for building automation system (BAS) is an increasingly important topic to promote wider adoption of smart building technologies. Metadata inference is used to automatically discover semantics within the BAS, such as labelling sensors, discover control variable relationships, etc. Clustering analysis has been applied in many previous research studies to achieve faster smart building retrofits through automated or semi-automated BAS point labelling. However, previous research using clustering only used small data sets of two to five buildings. This research examines the effectiveness of this approach on a broader scale with 40 commercial and institutional buildings and more than 65,000 labelled BAS points. Different clustering strategies with varying feature space and clustering algorithms are examined. Furthermore, this study compares which time series features and generation approach may enhance labelling efficiency. Positive results from this study support the effectiveness of applying clustering for point type inference. Results show the complimentary nature of additional time series features when the existing raw metadata from the BAS is less descriptive.
Plaster：元数据标准化方法的集成、基准测试和开发框架
DOI：
10.1145/3276774.3276794
发表时间：
2018
期刊：
Proceedings of the 5th Conference on Systems for Built Environments
影响因子：
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作者：
Koh, Jason;Hong, Dezhi;Gupta, Rajesh;Whitehouse, Kamin;Wang, Hongning;Agarwal, Yuvraj
通讯作者：
Agarwal, Yuvraj