Building information modeling–based cyber-physical platform for building performance monitoring

Yun-Yi Zhang, Kai Kang, Jia-Rui Lin, Jian-Ping Zhang and Yi Zhang

International Journal of Distributed Sensor Networks, 2020, vol. 16, issue 2, 1550147720908170

Abstract: Building performance management requires massive data input; however, the relevant data are separated and heterogeneous; thus, it prevents a comprehensive building performance management. Building information modeling brings a new way to capture rich information of a building, and has great potential in data interoperability for building performance management. This article presents a scalable building information modeling–based cyber-physical platform for building performance monitoring to integrate heterogeneous data from different buildings. A smart sensor network based on Arduino and standard protocol is installed for data sensing and collection. A building information modeling–based sensing information model integrating heterogeneous data in a unified structure is proposed, and a scalable NoSQL database is established to store data in a cloud environment. A series of RESTful web services is developed to share data for building performance management applications. The proposed platform is developed taking the advantage of horizontal scalability of NoSQL database, and the data schema and services are generated automatically based on the unified data model. The platform has collected data from 77 buildings in China, and the results of a case study show the platform brings a new paradigm in collecting, storing, integrating, and sharing of sensor data and building information for building performance monitoring and analytics.

Keywords: Building information modeling; building performance; cyber-physical platform; sensor network; NoSQL database; web service; interoperability; system automation (search for similar items in EconPapers)
Date: 2020
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Citations: View citations in EconPapers (2)

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Persistent link: https://EconPapers.repec.org/RePEc:sae:intdis:v:16:y:2020:i:2:p:1550147720908170

DOI: 10.1177/1550147720908170

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