Development of Intelligent Prefabs Using IoT Technology to Improve the Performance of Prefabricated Construction Projects

Linlin Zhao, Zhansheng Liu, Jasper Mbachu

Research output: Contribution to journalArticleResearchpeer-review

44 Citations (Scopus)
243 Downloads (Pure)

Abstract

Prefabrication (PC) projects have many advantages, such as cost and energy savings and waste reduction. However, some problems still exist that hamper the development of prefabrication projects. To improve PC project performance and advance innovation in construction, this study introduces an innovative method that incorporates Radio Frequency Identification (RFID) and Long Range (LoRa) technologies, sensor networks, the BIM model and cloud computing to automatically collect, analyze and display real-time information about PC components. It can locate PC components on a construction site and monitor their structural performance during the installation process. RFID technology and strain sensors were used to collect the required data on a construction site. All the data was transmitted to a server using LoRa technology. Then, the cloud-based Building Information Modelling (BIM) model of the project was developed to store and vividly present project information and real-time onsite data. Moreover, the cloud-based BIM model enables project team members to access the project information from anywhere by using mobile devices. The proposed system was tested on a real PC project to validate its effectiveness. The results indicate that the sensor network can provide reliable data via LoRa technology, and a PC component can be accurately located on site. Also, the monitoring data of structural performance for the PC component during the installation process is acceptable. The proposed method using innovative technologies can improve PC project performance and help industry professionals by providing sufficient required information.

Original languageEnglish
Article number4131
JournalSensors (Basel, Switzerland)
Volume19
Issue number19
DOIs
Publication statusPublished - 24 Sept 2019

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