arXiv 建筑语义标准论文· Daniel Hugo·· 2023-11-20AI 评分66
「英中对照」论文介绍Data Clearing House语义建筑平台，支持能源分析数据复用
A smart building semantic platform to enable data re-use in energy analytics applications: the Data Clearing House
AI 导读
论文称，Data Clearing House（DCH）语义建筑平台已接入作者所属机构及外部合作伙伴的多栋建筑，可托管传感器数据、建筑模型与分析应用并支持能源分析数据复用。
正文 · 中英逐段对照
Abstract:Systems in the built environment continuously emit time series data about resource usage (e.g., energy and water), embedded electrical generation/storage, status of equipment, patterns of building occupancy, and readings from IoT sensors. This presents opportunities for new analytics and supervisory control applications that help reduce greenhouse gas emissions due to energy demand, if the barrier of data heterogeneity can be overcome. Semantic models of buildings -- representing structure, integrated equipment, and the many internal connections -- can help achieve interoperable data re-use by describing overall context, in addition to metadata. In this paper, we describe the Data Clearing House (DCH), a semantic building platform that hosts sensor data, building models, and analytics applications. This fulfills the key phases in the lifecycle of semantic building data, which includes: cost-effective ingestion of Building Management System (BMS), IoT, metering and meteorological time series data from a wide range of open and proprietary systems; importing and validating semantic models of sites and buildings using the Brick Schema; interacting with a discovery API via a high-level domain-specific query language; and deploying applications to modelled buildings. Having onboarded multiple buildings belonging to our own organisation and external partners, we are able to comment on the challenges to success of this approach. As an example use-case of the semantic building platform, we describe a measurement and verification (M&V) application implementing the 'whole facility' (Option C) method of the International Performance Measurement and Verification Protocol (IPMVP) for evaluating electrical metering data. This compares energy consumption between nominated baseline and analysis time periods, to quantify the energy savings achieved after implementing an intervention on a site. 摘要：建筑环境中的系统持续生成有关资源使用（例如能源和水）、内嵌发电/储能、设备状态、建筑占用模式以及物联网传感器读数的时间序列数据。如果能够克服数据异构性这一障碍，这将为新型分析与监督控制应用带来机遇，帮助减少因能源需求产生的温室气体排放。建筑语义模型——表示结构、集成设备以及众多内部连接——除元数据外，还可通过描述整体上下文帮助实现可互操作的数据复用。在本文中，我们描述了 Data Clearing House（DCH），这是一个语义建筑平台，承载传感器数据、建筑模型和分析应用。该平台涵盖语义建筑数据生命周期中的关键阶段，包括：从各种开放和专有系统中高性价比地接入楼宇管理系统（BMS）、物联网、计量和气象时间序列数据；使用 Brick Schema 导入和验证场地与建筑的语义模型；通过高层领域特定查询语言与发现 API 交互；以及向已建模建筑部署应用。在接入我们自身组织和外部合作伙伴的多栋建筑后，我们能够评述这种方法取得成功所面临的挑战。作为语义建筑平台的示例用例，我们描述了一个测量与验证（M&V）应用，该应用实施国际性能测量与验证协议（IPMVP）的“整体设施”（Option C）方法来评估电力计量数据。该应用比较指定基准期与分析期之间的能耗，以量化在某一场地实施干预措施后所实现的节能量。
| Comments:评论： | 13 pages, 4 figures. Accepted for presentation at Climate Smart Engineering 2023 (CSE23)13 页，4 幅图。已获 Climate Smart Engineering 2023（CSE23）接收并做报告。 |
| Subjects:主题分类： | Databases (cs.DB); Systems and Control (eess.SY)数据库 (cs.DB)；系统与控制 (eess.SY) |
| MSC classes:MSC 分类： | 68U35 (primary) 68Q55 (secondary)68U35（主分类）68Q55（次分类） |
| ACM classes:ACM 分类： | I.6.7; J.7; H.2.3I.6.7；J.7；H.2.3 |
| Cite as:引用格式： | arXiv:2311.11630 [cs.DB] |
| (or arXiv:2311.11630v1 [cs.DB] for this version) （或 arXiv:2311.11630v1 [cs.DB] 对应此版本） | |
| https://doi.org/10.48550/arXiv.2311.11630 arXiv-issued DOI via DataCite 由 arXiv 通过 DataCite 发放的 DOI |
Submission history提交历史
From: Daniel Hugo [view email]
[v1]
Mon, 20 Nov 2023 09:33:21 UTC (658 KB)
发件人：Daniel Hugo [查看电子邮件]
[v1]
Mon, 20 Nov 2023 09:33:21 UTC (658 KB)
来源：arXiv 建筑语义标准论文 · arxiv.org