Smart and continuous commissioning (SCCx) of buildings can result in a significant reduction in the gap between design and operational performance. Ontologies play an important role in SCCx as they facilitate data readability and reasoning by machines. A better understanding of ontologies is required in order to develop and incorporate them in SCCx. This paper critically reviews the state-of-the-art research on building data ontologies since 2014 within the SCCx domain through sorting them based on building data types, general approaches, and applications. The data types of two main domains of building information modeling and building management system have been considered in the majority of existing ontologies. Three main applications are evident from a critical analysis of existing ontologies: (1) key performance indicator calculation, (2) building performance improvement, and (3) fault detection and diagnosis. The key gaps found in the literature review are a holistic ontology for SCCx and insight on how such approaches should be evaluated. Based on these findings, this study provides recommendations for future necessary research including: identification of SCCx-related data types, assessment of ontology performance, and creation of open-source approaches.
翻译:建筑的智能和连续调试(SCCx)可显著缩小设计与运行绩效之间的差距。在SCCx中,人类学在促进数据可读性和机器推理方面发挥着重要作用。需要更好地了解本源学,以便开发并将本源学纳入SCCx。本文件批判性地审查了2014年以来在SCCx领域对建立数据学进行的最新研究,根据数据类型、一般方法和应用程序对其进行分类。在现有的大多数关于本源学中,考虑了建筑信息建模和建筑管理系统两大领域的数据类型。从对现有本源学的批判性分析可以看出,三大应用:(1)关键业绩指标的计算,(2)绩效改进,(3)缺陷的检测和诊断。文献审查发现的关键差距是SCCx的整体性肿瘤学,以及关于如何评价这些方法的深入了解。根据这些研究结果,本研究为今后必要的研究提出了建议,包括:确定与SCx相关的数据类型,评估本源绩效,以及创建开放源方法。