Big Data Management and Analytics Metamodel for IoT-Enabled Smart Buildings

IEEE Access

Asif Qumer Gill¹  Muhammad Rizwan Bashir²  Ghassan Beydoun²  Brad Mccusker³ 

[1] Faculty of Engineering and Information Technology, School of Computer Science, University of Technology Sydney, Ultimo, NSW, Australia;Faculty of Engineering and Information Technology, School of Information, Systems, and Modelling, University of Technology Sydney, Ultimo, NSW, Australia;SURROUND Australia Pty Ltd., Sydney, NSW, Australia;

关键词: IoT;    big data management;    metamodel;    smart buildings;   

DOI  :  10.1109/ACCESS.2020.3024066

来源: DOAJ

【 摘 要 】

Big data management and analytics, in the context of IoT (Internet of Things)-enabled smart buildings, is a challenging task. It is a diffused and complex area of knowledge due to the diversity of IoT devices and the nature of data generated by the IoT devices. Many international bodies have developed metamodels for IoT-enabled ecosystems to allow knowledge sharing. However, these are often narrow in focus and deal with only the IoT aspects without taking into account the management and analytics of big data generated by the IoT devices. Hence, in this article we propose a metamodel for the Integrated Big Data Management and Analytics (IBDMA) framework for IoT-enabled smart buildings. The IBDMA Metamodel can be used to facilitate interoperability between existing big data management and analytics ecosystems deployed in smart buildings or other smart environments. We import the metamodel into a knowledge graph management tool and by considering a case study we validate the metamodel using this tool. The evaluation results demonstrate that IBDMA Metamodel is indeed suitable for its intended purpose.

【 授权许可】

Unknown