Please use this identifier to cite or link to this item: https://hdl.handle.net/10356/138380
Title: Cloud asset-enabled integrated IoT platform for lean prefabricated construction
Authors: Xu, Gangyan
Li, Ming
Chen, Chun-Hsien
Wei, Yongchang
Keywords: Engineering::Mechanical engineering
Issue Date: 2018
Source: Xu, G., Li, M., Chen, C.-H., & Wei, Y. (2018). Cloud asset-enabled integrated IoT platform for lean prefabricated construction. Automation in Construction, 93, 123-134. doi:10.1016/j.autcon.2018.05.012
Journal: Automation in Construction
Abstract: Prefabricated construction has become increasingly popular over the recent years, given its benefits including higher construction speed, lower cost, and improved quality. To facilitate the operations of prefabricated construction, various technologies have in parallel been introduced. However, due to its project-based feature and the involvement of numerous Small and Medium Enterprises (SMEs), the adoption of information technologies is insufficient and varies between SMEs, thereby hindering the improvement of the efficiency of prefabricated construction. Considering these issues and aiming at realizing lean prefabricated construction, this paper proposes an integrated cloud-based Internet of Things (IoT) platform through exploiting the concept of cloud asset. Its operation model has also been worked out to enable SMEs to adopt IoT technologies economically and flexibly. Besides, to make the platform compatible and scalable on managing diverse physical assets in different companies and scenarios, a unified cloud asset data model is proposed. Furthermore, an IoT service-sharing module is developed to support different levels of service-sharing on the platform. Finally, a real-life prefabricated construction project in Hong Kong and several lab-based LEGO construction models are adopted to verify the feasibility and effectiveness of the proposed platform.
URI: https://hdl.handle.net/10356/138380
ISSN: 0926-5805
DOI: 10.1016/j.autcon.2018.05.012
Schools: School of Mechanical and Aerospace Engineering 
Rights: © 2018 Elsevier B.V. All rights reserved. This paper was published in Automation in Construction and is made available with permission of Elsevier B.V.
Fulltext Permission: none
Fulltext Availability: No Fulltext
Appears in Collections:MAE Journal Articles

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